Search

163 results for “esther”

1. 

   John Pell @gaelicwizard

   2026-10-24

   : So many people are going back to Twitter. I’ve blocked so many antisemites. My timeline is dead.

   Rant incoming: I don’t know how to find interesting people when I keep having to block folks who think that one indigenous group has the right to exterminate another from a mutual homeland…half a world away that the tooter has no connection to at all on either side. The worst part is that you* think I’m agreeing with you* because you think the other “side” is so subhuman as to not count.

   *If you think this “you” is meant for you, it is. If you don’t, it probably isn’t.

2. 

   yakkoj 🦊 @yakkoj

   2026-10-24

   Proof that my reminders are doing the correct thing:

   Utility bill sometimes sends email, sometimes doesn't. This is generally true for most of the bills. Having reliable reminders firing is the only way to be sure I can track the bills and pay them on time. (yes, I have reminders even for "auto pay" ones, because it's been proven that I can't trust THAT, either)

3. 

   Exposé Online @[email protected]

   2026-10-24

   New #review: "By the early 80s, #Ruins was essentially a two-man band featuring #PiergiuseppeCiranna and #AlessandroPizzin, and much of their commercially released output can be found on our artist page, some of which we have reviewed as they are reissued. The collection of 26 tracks at hand represents experimental pieces that were created either individually or together, used for Ruins #multimedia installations in art galleries back in the 80s." #ExposeOnline #ExperimentalMusic #RuinsItaly http://expose.org/index.php/articles/display/ruins-cosa-experimental-works-3.html

   #ruinsitaly #experimentalmusic #exposeonline #multimedia #alessandropizzin #piergiuseppeciranna
4. 

   Allen Sale @[email protected]

   2026-10-24

   Here's the thing: Just because a person checks the boxes for inclusivity on paper doesn't mean he gets a pass on portrayals.

   Did I mention that one of the characters is blind, African American, and psychic? Really? This shouldnt be lauded.

   He's not subverting tropes either. He's blatently encouraging them. "Describe it to me" she says throughout the novel even though she has other senses she can use whilst walking.

   #clivebarker #halloweenreads #bookstodon #WhatToRead

   #whattoread #bookstodon #halloweenreads #clivebarker
5. 

   Dev Community @[email protected]

   2026-10-27

   The review usually opens with a demo that looks fine. An agent plans four edits, applies them to a workspace on a remote box, and reports success; the tests are green and everyone relaxes. Two hours later a human's refactor is gone, and nobody can point at the request that removed it. Is that a model problem, a server problem, or a protocol problem?

   I think it is a protocol problem almost every time, and I want to make the case with an executable fixture rather than an architecture diagram. Below is the event order I keep reconstructing in reviews, the invariant it violates, and a small simulator that will fail your design for you. Everything here is a model of a system, not a benchmark of a vendor.
   

   1. The event order that silently wins

   
   A planner reads the workspace at revision 0 and emits three steps against app.py. Step 1 applies and the workspace moves to revision 1. While step 2 is in flight, either a human edits that file or the session is re-routed to a different model that re-plans the remainder; both are ordinary events, not incidents.

   Step 2 still carries the content hash it was planned against. If the executor applies patches by path without checking that hash or the revision, the write lands on content the planner never saw, and the old bytes vanish. Nobody gets an error, because a patch is not a request — it is a claim about a state that may already be false.

   The failure is invisible precisely when it is most expensive. The agent's summary says "updated handler and tests", the test run passes because the overwritten hunk was unrelated, and the loss only surfaces at the next merge. Who is supposed to notice that?
   

   2. The invariant, stated once

   
   No step may be applied unless the state it was planned against is still the state it is applied to, or the step has been explicitly rebased onto the new state.

   That is it. Note what the invariant does not say: it does not say a step is correct, and it does not say a retried step is safe. A revision fence prevents stale acceptance; idempotency prevents double application. Teams routinely build one, assume they have the other, and then argue about whose bug it is.
   

   3. Declared assumptions

   
   

   • One writer per file at a time; concurrent multi-writer edits are out of scope and need a merge protocol, not a fence.
   • The workspace has a monotonic revision counter and a per-file content hash that are both persisted with the workspace itself.
   • A step is planned from a readable snapshot and carries (step_id, base_rev, path, pre_hash, patch).
   • Execution may be preempted at any point between "patch written" and "client received the result".
   • Model identity may change inside a session, because routing, fallback, or a free-tier allowance running out can move you to another model without warning.

   
   

   4. Data flow and failure domains

   
   There are three state holders and they fail independently: the planner's context (lossy, model-dependent), the executor's workspace (authoritative, preemptible), and the client's view of progress (optimistic, retried). The only durable truth is the workspace plus whatever journal you persist alongside it.

   Failure domains worth separating in review: stale plan (planner state diverged), lost ack (executor applied, client did not learn), duplicate delivery (client retried an applied step), and re-plan drift (a new model emits steps against an old base). They need different mechanisms, and a single retry counter hides all four.
   

   5. The fixture

   
   This is deterministic Python with no model calls, so the verdicts below are properties of the protocol, not of any provider.

   # fence_sim.py - deterministic, no LLM involved
   from dataclasses import dataclass

   @dataclass(frozen=True)
   class Step:
   step_id: str
   base_rev: int
   path: str
   pre_hash: str
   patch: str

   class Workspace:
   def __init__(self):
   self.rev = 0
   self.files = {"app.py": "v0"}
   self.journal = set() # persisted with the workspace
   def hash(self, path):
   return self.files
   [path] def write(self, path, content):
   self.files[path] = content
   self.rev += 1

   class Executor:
   """fence: 'none' | 'plan' | 'step'; dedupe: journal-backed idempotency"""
   def __init__(self, ws, fence="step", dedupe=True):
   self.ws, self.fence, self.dedupe = ws, fence, dedupe
   self.plan_rev = None
   def plan(self, rev):
   self.plan_rev = rev
   def stamp(self, s):
   if self.fence == "step":
   return Step(s.step_id, self.ws.rev, s.path, self.ws.hash(s.path), s.patch)
   if self.fence == "plan":
   return Step(s.step_id, self.plan_rev, s.path, s.pre_hash, s.patch)
   return s
   def exec(self, s):
   s = self.stamp(s)
   key = (s.step_id, s.base_rev)
   if self.dedupe and key in self.ws.journal:
   return "deduped"
   if self.fence != "none":
   if s.base_rev != self.ws.rev:
   return "rejected:stale_rev"
   if self.ws.hash(s.path) != s.pre_hash:
   return "rejected:pre_hash"
   self.ws.write(s.path, s.patch)
   if self.dedupe:
   self.ws.journal.add(key)
   return "applied"

   Two lines deserve attention. The journal lives in Workspace, not in the executor, because an in-process dedupe set dies with the server that was preempted — which is exactly the trap. And stamp is where fence granularity is decided, so you can argue about it in one place.
   

   6. Injecting the three failures

   
   Run the same three scenarios across fence modes and record the verdicts. The interference classes are injected explicitly, so the denominator is the number of injections, not the number of suspicious log lines.

   def scenario_concurrent_edit(fence):
   ws = Workspace(); ex = Executor(ws, fence=fence); ex.plan(ws.rev)
   s1 = Step("s1", 0, "app.py", "v0", "v1")
   s2 = Step("s2", 1, "app.py", "v1", "v2")
   assert ex.exec(s1) == "applied"
   ws.write("app.py", "human-refactor") # interference: rev 2
   return ex.exec(s2)

   def scenario_preemption_retry(fence):
   ws = Workspace(); ex = Executor(ws, fence=fence)
   s1 = Step("s1", 0, "app.py", "v0", "v1")
   ex.exec(s1)
   # ack lost; client replays s1 against a fresh executor, same persisted workspace
   return Executor(ws, fence=fence).exec(s1)

   def scenario_replan_drift(fence):
   ws = Workspace(); ex = Executor(ws, fence=fence); ex.plan(ws.rev)
   ex.exec(Step("s1", 0, "app.py", "v0", "v1"))
   ex.plan(ws.rev) # new model re-plans from rev 1
   return ex.exec(Step("s2", 0, "app.py", "v0", "v1-tail"))

   Expected output, because the simulation is deterministic and calls no model:

   fence=none concurrent_edit -> applied preemption_retry -> applied twice replan_drift -> applied
   fence=plan concurrent_edit -> rejected:stale_rev preemption_retry -> rejected:stale_rev replan_drift -> rejected:stale_rev
   fence=step concurrent_edit -> rejected:stale_rev preemption_retry -> rejected:stale_rev replan_drift -> applied
   dedupe on concurrent_edit -> rejected:stale_rev preemption_retry -> deduped replan_drift -> applied

   Read the second and third rows together, because that is the argument. A plan-level fence turns every retry into a spurious rejection and every legitimate re-plan into a dead end; it is loud, but it is loud in the wrong places. A step-level fence plus a persisted journal gets you the two properties you actually want, and it costs you a durable set of (step_id, base_rev) keys.
   

   7. Making it a property, not a demo

   
   Three scenarios are an anecdote. Turn them into invariants and let a random interleaving search hunt for violations — this is the part I would block a design review on.

   def invariants_hold(ws, results):
   # P1: every applied step saw base_rev == rev at apply time
   assert all(r.rev_at_apply == r.base_rev for r in results if r.status == "applied")
   # P2: journal is append-only per (step_id, base_rev)
   assert ws.journal == set(ws.journal)
   # P3: no path content was replaced by a step older than the current rev
   assert all(r.base_rev <= r.rev_at_apply for r in results)

   Then fuzz: shuffle {human_edit, preempt, retry, replan, duplicate_delivery} over a fixed step list, run 5,000 seeds, and assert P1 and P2 for every seed with fences on. Run the same search with fence="none" to extract a minimal counterexample, and put that event order in the PR description as the regression case. A protocol claim without a counterexample search is a preference.
   

   8. Where the free tier changes the arithmetic

   
   If your executor is a shared, preemptible environment and your planner can move between models at any time, then re-plan drift and lost acks are not edge cases — they are the steady state. That is the actual architectural consequence of running agents on free resources, and it argues for cheap, persisted fences rather than expensive coordination.

   I use MonkeyCode as the concrete instance of that environment in this review: it is an open-source coding agent whose operator supplies free model access (currently advertised as a 10M-token allowance) and a free server option. Treat those numbers as operator-supplied and re-verify them on the project page before you design around them, because allowances and routing change faster than any architecture does. My interest here is narrow: a free server makes preemption ordinary, and free model access makes mid-session re-routing ordinary, so both of my injected interferences become Tuesday.

   Disclosure: This article was prepared as part of MonkeyCode's product outreach.
   

   9. Tradeoffs I would write down

   MechanismBuys youCosts youFails whenNo fenceThroughput, simplicitySilent lost updatesAny concurrent editPlan-level fenceLoud, cheap rejectionRe-planning whole plans, spurious retriesModel swap or long plansStep-level fencePrecise staleness detectionA re-stamp on every dispatchSemantic overlap between stepsPersisted journalIdempotent retry across preemptionDurable key storage, growth controlJournal not persisted atomically with the writeCheckpoint per stepFast compensationStorage, restore latencyLarge binaries, long test suites

   10. Verdicts: reject, replay, or compensate

   Event orderCorrect verdictWhyStep arrives, base_rev < current rev, no overlapReject, re-plan from current revThe plan is stale; the patch is not recoverableStep arrives, journal contains (step_id, base_rev)Replay the stored resultThe work is done; the ack is what was lostStep applied, tests for touched files failCompensate to the checkpointFence passed, semantics did notNew model re-plans mid-session from current revAccept if re-stamped and preconditions holdDrift is expected, staleness is notTwo steps with overlapping hunks in one planReject the plan at admissionA fence cannot order siblings

   11. What I would change next

   
   

   1. Persist the revision counter, file hashes, and journal in one atomic write, so a crash cannot leave a patch without its key.
   2. Stamp base_rev at dispatch, never at plan time, and log both values — the delta is your drift signal.
   3. Bound the journal by session and drop it only after a checkpoint the workspace itself can prove.
   4. Run the fuzz job in CI with fences on, and store the minimal counterexample from fence="none" as a named regression seed.
   5. Add a sibling-overlap check at plan admission, because per-step fences order nothing within a plan.

   
   

   12. Limits, and who should skip this

   
   The fixture models file-level hashing and a single writer; it says nothing about merge semantics, and it does not evaluate whether a patch was any good. If your model swap also changes plan quality, this protocol will happily accept a worse plan that happens to be revision-correct. That is a separate evaluation problem, and no fence will solve it for you.

   Skip this if your agent is single-turn and single-file with a human watching every apply, if your platform already gives each step an atomic worktree or VM snapshot, or if you cannot persist a journal durably — half of this mechanism without the journal is worse than none, because it rejects retries without making them safe.

   So here is the question I would leave in the review thread: which event order in your system breaks the invariant — a human edit racing step two, an ack lost after the write, or a re-plan against a stale base — and for that specific order, should the executor reject, replay, or compensate?#ai #architecture #distributed #testing #software #coding #development #engineering #inclusive #community
   Treat a Coding-Agent Step as a Revision-Fenced Command, Not a Prompt

   #ai #community #software #coding #architecture #development
6. 

   Psychology News Robot @[email protected]

   2026-10-27

   DATE: October 27, 2026 at 07:00AM
   SOURCE: PSYPOST.ORG

   ** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
   -------------------------------------------------

   TITLE: We’ll pay to get revenge on an algorithm, even though it can’t feel a thing

   URL: https://www.psypost.org/well-pay-to-get-revenge-on-an-algorithm-even-though-it-cant-feel-a-thing/

   When a computer algorithm treats people unfairly, they tend to get just as angry and retaliate just as often as they would against a human wrongdoer. A new series of experiments published in Journal of Experimental Psychology: General provides mixed evidence on whether punishing a machine brings the same sense of closure as punishing a person, but it suggests that a machine’s response to being punished, such as sounding hurt or promising to make fairer offers, can strengthen people’s sense that justice was done. The findings suggest that as artificial intelligence takes on more decision-making roles in society, organizations may need to design systems that can communicate accountability when things go wrong.

   Automated systems are increasingly tasked with consequential choices, from screening job applicants to steering vehicles and prioritizing medical care. To understand how people react when these systems cause harm, psychologists study a concept known as mind perception, which is the everyday process of judging what kind of mental life another entity possesses. People generally evaluate minds along two separate dimensions: agency, meaning the ability to think, plan, and act intentionally, and experience, meaning the capacity to feel physical pain, pleasure, fear, and emotions.

   In human interactions, the capacity to commit a moral wrong and the capacity to experience punishment usually go together, since a sane adult can both plan a harmful act and feel the sting of a penalty. Artificial intelligence splits these two qualities apart because people often view machines as having enough agency to cause deliberate harm, yet almost no ability to feel pain or remorse. For instance, research covered by PsyPost in 2023 found that people judged AI agents as more deserving of blame than humans in one classic life-and-death dilemma. Similarly, another 2023 study covered by PsyPost showed that people hold automated driving assistants responsible for road outcomes while simultaneously categorizing the software as a mere tool rather than a true moral being.

   This mental divide raises questions about whether punishing an algorithm can produce justice satisfaction, which is the feeling of closure, fairness, and resolution a victim experiences after an offender is penalized. Psychological theories generally propose two reasons why punishment feels satisfying: either it fulfills a desire for retribution by making the wrongdoer suffer for their actions, or it serves a communicative role by teaching the wrongdoer a moral lesson.

   Because people tend to see machines as unable to genuinely suffer or feel guilt, study author Alexander Eng, an associate professor of organizational behavior in the Department of Management at the Asia School of Business in Kuala Lumpur, and co-author Kai Chi Yam of the National University of Singapore examined how people emotionally and behaviorally respond during and after they penalize an unfair algorithm.

   “Research on punishment usually assumes that anyone capable of doing wrong can also be punished,” Eng told PsyPost. “We tend to see a young child as unable to truly commit a wrong, and so also as unfit for punishment. Machines break that link: people see AI as able to make decisions that hurt them, yet unable to feel pain, regret, or learn a moral lesson. As AI takes on decisions like medical triage and firing employees, we wanted to know how people respond when they try to hold it accountable, and whether punishing it gives them any sense that justice was done.”

   The researchers began with a pilot study of 380 English-speaking adults in the United States, recruited through the online platform Prolific, to verify whether people actually punish algorithms. Participants played a single round of an economic exercise called the ultimatum game, in which a partner was given £0.50 and proposed how to split it. If the participant accepted the split, both parties kept their share, but if the participant rejected it, neither party received anything, making rejection a form of costly punishment.

   Participants were told their partner was either another human participant or an algorithm, and they received either a fair offer of £0.25 each or an unfair offer where the partner kept £0.45 and left the participant just £0.05. In reality, the researchers preset all offers. Receiving a stingy offer from an algorithm provoked much higher anger (an average of 3.12 on a 5-point scale) than receiving a fair offer from an algorithm (1.31). When given the unfair deal, participants felt comparable anger toward algorithms (3.12) and humans (2.91), and they punished the unfair algorithm by rejecting its offer 57.8 percent of the time, which was not statistically different from the 62.2 percent rejection rate for unfair humans.

   In their first main experiment, the authors examined what happens after punishment is delivered using a final sample of 123 Prolific participants. Every participant received the unfair £0.05 offer in the ultimatum game from either a human or an algorithm, decided whether to accept or reject it, and then answered five questions measuring their justice satisfaction, such as whether they felt everyone got what they deserved. Afterward, participants played a second exercise called the dictator game, where they were given £0.50 and could unilaterally share any amount in £0.05 increments with their partner, while also having the option to switch to a new human partner first.

   As in the pilot study, participants rejected unfair offers from algorithms (38 out of 62) and humans (40 out of 61) at similar rates. Overall, the 78 participants who punished their partner by rejecting the offer reported higher justice satisfaction (3.57 out of 5) than the 45 who accepted it (2.63). Controlling for whether participants switched partners, the satisfaction gap between those who punished and those who did not was larger when the offender was a human than when it was an algorithm, and higher justice satisfaction in turn predicted greater generosity in the second game.

   Because the option to switch partners or the belief that computers have no use for money might have influenced the first experiment, the researchers conducted a second study with a stricter setup among 739 participants, preregistered along with the third and fourth experiments through the journal’s registered-report review process. Participants were told that five algorithms and five human research assistants were competing across multiple negotiations, and that while neither kept the money personally, the lowest-earning algorithm and human would be eliminated from the competition.

   Participants were not allowed to switch partners between the ultimatum game and the dictator game, and they also completed scales measuring their partner’s perceived agency and emotional experience, along with their own baseline tendency to attribute human-like consciousness to technology, a trait known as anthropomorphism.

   Participants rated human partners higher on agency (3.30 versus 2.79 out of 5) and much higher on the capacity for emotional experience (3.20 versus 1.86) than algorithmic partners. Even so, participants rejected the unfair offer at comparable rates for algorithms (71.0 percent, or 262 of 369) and humans (65.4 percent, or 242 of 370), and those who punished their partner felt much greater justice satisfaction (3.53) than those who accepted the unfair split (2.71). In contrast to the first study, after controlling for baseline anthropomorphism, the link between punishing and justice satisfaction, and in turn generosity, was equally strong whether the partner was an algorithm or a human.

   “People react to an unfair machine much as they react to an unfair person,” Eng said. “Participants got just as angry at an algorithm that made them a lowball offer as at a human who made the same offer, and they were just as willing to give up their own money to punish it. Whether punishing the machine felt as satisfying was less consistent across studies.”

   A third study tested these dynamics in a different scenario called the trust game with 735 participants who chose to invest £0.20 with a human research assistant or an algorithm. The investment was tripled to £0.60, and the partner broke the participant’s trust by returning just £0.10 instead of a fair £0.30 split. Participants could then penalize their partner by recommending on a 1-to-5 scale that the partner be removed from the player pool, before rating their justice satisfaction and playing a second round where the roles were reversed.

   Participants gave similar removal ratings to unfair algorithms (3.37 out of 5) and unfair humans (3.26). Unexpectedly, harsher removal ratings were associated with lower justice satisfaction rather than higher closure. The authors suspect this is because participants only submitted a recommendation and never saw a penalty take effect, so the ratings may have reflected anger more than punishment. In an exploratory analysis looking directly at anger, feeling angrier predicted lower justice satisfaction and less generosity toward both types of partners, with anger reducing justice satisfaction slightly more when the partner was human than when it was an algorithm.

   In a fourth study involving 3,684 participants who rejected the unfair £0.05 offer in the ultimatum game, the researchers tested whether a message from the penalized partner could increase justice satisfaction. Immediately after rejecting the offer from a human or an algorithm, participants received either no message at all, a message expressing emotional distress over repeated rejections, a message calmly acknowledging that the offer was too low and promising to be fair in the future, or a combined message expressing both distress and a moral lesson learned. A separate preliminary test with 305 people confirmed that these messages effectively conveyed emotional suffering and moral learning as intended.

   Across the entire sample, participants paired with an algorithm reported slightly lower justice satisfaction (3.56 out of 5) than those paired with a human (3.66), a small difference that accounted for about half a percent of the overall variation in satisfaction scores. However, receiving a message from an algorithm expressing emotional suffering (3.57) or moral learning (3.62) produced higher justice satisfaction than receiving no response from the algorithm (3.42).

   For human partners, the differences between receiving no message (3.57) and receiving a suffering (3.66) or moral learning (3.69) message were not statistically significant after adjusting for multiple comparisons. Still, the boost from a message was not statistically larger for algorithms than for humans, and combining both messages added no measurable benefit beyond either one alone. The results suggest that a response from a machine can help satisfy people’s need for redress, even though participants rated algorithms as far less capable of feeling than humans.

   “We expected an apology or a show of remorse from an algorithm to count for little, since people don’t believe algorithms feel anything,” Eng explained. “Yet those messages raised people’s sense of justice for algorithms at least as much as the same messages did for humans. It was also striking that people paid to punish an algorithm that couldn’t keep the money and couldn’t experience the loss.”

   A final supplemental experiment with 1,093 participants examined whether dissatisfaction after being wronged causes people to take out their frustration on an innocent bystander, a behavior known as displaced aggression. Participants received the unfair £0.05 offer in the ultimatum game from a human or an algorithm, decided whether to accept or reject it, and then played the dictator game paired with a brand-new human research assistant who had no involvement in the first round.

   Controlling for baseline anthropomorphism, participants who punished their initial partner by rejecting the unfair offer shared slightly more money with the innocent bystander (an aggression score of 6.75 versus 7.07 on an 11-point scale, where higher scores mean less money shared) than those who did not punish, regardless of whether the original wrongdoer was a person or a machine.

   “The anger and punishment results held up across more than 6,000 participants,” Eng noted. “The machine-versus-human differences in justice satisfaction were small where they appeared at all: in our largest study, of about 3,700 people, partner type explained roughly half a percent of the variance. I’d treat that as a modest pattern that needs more testing.”

   As with all research, there are some caveats to consider when interpreting these results. All of the experiments relied on brief online financial games where the harm consisted of being offered an unfair split of £0.50 by an anonymous text-based partner. How people think and feel when a simple computer program shortchanges them by a few cents may differ from how they react to high-stakes algorithmic harm in the real world, such as an automated system wrongfully denying a mortgage, firing an employee, or causing a traffic accident. In addition, participants chose for themselves whether to punish, so differences between those who punished and those who did not may partly reflect who chose to punish rather than the effect of punishing itself.

   “These were online economic games with small stakes, splitting 50 pence,” Eng pointed out. “Real harms from AI, like a denied loan or a wrong diagnosis, carry much more weight, so the effects could look different there. The justice satisfaction results were also mixed: one study found a clear gap between machines and humans and another found none, so I wouldn’t claim that punishing machines never satisfies people.”

   The evidence on whether punishing a machine feels less satisfying than punishing a person was mixed across the studies, appearing in the first and fourth experiments but not in the second, while the third experiment’s punishment measure did not work as intended. The clearest gap came from the smallest experiment, which included 123 participants after dozens of duplicate entries were removed and which had originally been preregistered to test different outcomes; the larger, preregistered second experiment did not replicate it.

   The authors also noted that their five-item survey measuring justice satisfaction showed relatively low internal consistency in the fourth study, indicating a need to develop more precise tools for measuring psychological closure after technological failures. Future research could explore how different types of real-world errors and corrective feedback shape public trust, helping engineers and policymakers design accountability measures, such as holding human creators rather than machines responsible, that satisfy human intuitions of fairness.

   “We want to test other kinds of wrongdoing and punishment beyond economic games, and develop a better measure of justice satisfaction,” Eng added. “In a related project, I’m studying the ‘AI disclosure penalty,’ where people value content less once they’re told AI made it.”

   The study, “Artificial Intelligence and Machines Are Capable of Harm, but Not of Experiencing Punishment,” was authored by Alexander Eng and Kai Chi Yam.

   URL: https://www.psypost.org/well-pay-to-get-revenge-on-an-algorithm-even-though-it-cant-feel-a-thing/

   -------------------------------------------------

   Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org

   Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot

   -------------------------------------------------

   #psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #ArtificialIntelligence #AI #Algorithms #MachineLearning #AIethics #Psychology #SocialPsychology #Justice #Accountability #HumanBehavior

   #psychology #counseling #socialwork #psychotherapy #mentalhealth #psychiatry
7. 

   Canvases By Peter 🇵🇸 @[email protected]

   2026-10-27

   Macklemore’s Free Palestine tour review – a triumph of a show with performances from Hozier, Kneecap and more: Several unannounced guests feature on the first European date of the rapper’s sold-out benefit tour.

   "We’d like to thank Ed Sheeran for organising this concert,” offers a member of Kneecap, one of several unannounced guests who have turned up for the first European date of Macklemore’s Free Palestine tour. It’s a characteristically two-fisted approach to the matter in hand from a band who have seldom shied away from controversy, but it has more than a grain of truth in it.

   The events of the last six weeks are quite something, and perhaps not what Robert Kraft, the billionaire owner of the New England Patriots, had in mind when he led efforts to pressurise Sheeran to remove Macklemore from his summer US tour, after the rapper made a speech about Palestine on stage at New Jersey’s MetLife Stadium. Macklemore was duly removed from the tour, but the rapper saw his profile rise dramatically as a result – in fairness, he was hardly unknown, but his biggest hits are a decade old – while every other artist on Sheeran’s tour quit in solidarity. Sheeran’s tour limped on amid much opprobrium, while Macklemore was able to translate the publicity into a tour of his own, in noticeably bigger venues than he played on his last European tour, with proceeds donated to organisations assisting Palestinians."

   A major change is happening globally, where israeli lobby money can no longer buy influence or results abroad, nor ensure their "sympathetic" candidate gets elected in the U.S. either. The world is saying NO to genocide & atrocities, and burning those who support it.

   https://www.theguardian.com/music/2026/oct/27/macklemore-free-palestine-tour-review-a-triumph-with-hozier-kneecap-dublin

   #BoycottIsrael #HumanRights #Music #Activism #News #Gaza #Palestine #Macklemore

   #boycottisrael #humanrights #music #activism #news #gaza
8. 

   Teagan's Books @[email protected]

   2026-10-27

   Olga #Reviews: A Peril in Unseen Frequencies

   Tuesday, October 27, 2026

   Welcome, all.  Some things are such a delight that they simply must be shared.  Today Olga Núñez Miret posted an extraordinarily mindful review of “A Peril in Unseen Frequencies.” How could I not crow about it?

   Olga is a genuinely amazing person.  She is also an accomplished author herself (among many other inspiring things).  Here’s a screenshot of Olga’s Amazon author page.  She has 34 titles there, in multiple genres and different languages too.

   Please meet me over at Olga’s blog.  Just click that big blue link below.  I’m closing comments here, but I hope to see you at Olga’s.

   Click Here to Visit Olga’s Post

   ♣ ♣ ♣

   Here’s the obligatory shameless self-promotion

   Although it’s a twisty mystery, it’s also a quick read.  As I usually do, I included a section about technology and cultural items that are mentioned in the story. 

   A Peril in Unseen Frequencies

   Universal Purchase Links

   Kindle:  relinks.me/B0HKPZ7TH4

   Paperback:  relinks.me/B0HKTFCD8Z

   Virtual Voice Audiobook:  relinks.me/B0HKNDVYDM

   A Medium’s Peril full series link: relinks.me/B0CG2SXX24

   ♣ ♣ ♣

   This blog is entirely human-written.  Furthermore, the author expressly prohibits any entity from using this publication for purposes of training AI technologies to generate text.  No part of this work may be reproduced, scanned, or distributed in any printed or electronic form without permission.  Please do not participate in or encourage piracy of copyrighted materials in violation of the author’s rights.

   All images are either the property of the author, or used with permission, or from free sources.

   Copyright © 2026 by Teagan Ríordáin Geneviene

   All rights reserved.

   #1920S #AMediumSPeril #APerilInUnseenFrequencies #BadMoonRising #GhostStory #NewBook #ParanormalMystery #TeaganRiordainGeneviene #TeriPolen #Vintage

   #1920s #amediumsperil #aperilinunseenfrequencies #badmoonrising #ghoststory #newbook
9. 

   Dev Community @[email protected]

   2026-10-27

   A campaign lands in your lap and the numbers are flat. The button says "Submit." The page is three paragraphs of feature copy above the fold. You have one experiment slot this sprint, one shared traffic budget, and two candidate changes that both look obviously wrong.

   So which one do you ship first?

   The useful answer is neither "test both" nor a coin flip. The two changes answer different questions, and one of them is usually wasted if you run it in the wrong order.
   

   The two problems look identical in a dashboard

   
   Both failures surface as the same line: campaign traffic arrives, signups don't happen. To separate them, split the funnel into two questions.

   • Does the page earn attention? Can a first-time visitor understand the offer within the first screen?
   • Does the ask earn commitment? Once the value is clear, is the action obvious, specific, and low-friction?

   The first question is about the landing page. The second is about the call to action. A dashboard that only tracks sessions and signups cannot tell you which one broke.
   

   A diagnostic table before you write any code

   What the data showsLikely causeWhere to startMost sessions end within a few seconds; low scroll depthThe page does not match the promise in the adLanding pageDeep scroll, pricing or docs section viewed, few form startsThe ask is vague, buried, or costlyCall to actionMany form starts, few completionsForm frictionNeither. Fix the formLow engagement and low action, traffic source unclearTargeting or message mismatch upstreamNeither. Fix the campaign

   
   That last row matters more than it looks. If the audience arriving from the campaign was never a fit, no amount of button rewording or hero-copy polishing will rescue the page. Fixing the targeting is cheaper than any experiment.
   

   Why the order matters more than the individual change

   
   A call to action is read in the context of the headline, the proof, the price, and the surrounding copy.

   That produces two ordering rules.

   Rule one: a button cannot fix a page that never establishes value. If visitors leave before they understand what they are being asked to do, a sharper label has nothing to attach to. You will measure noise and conclude that labels do not matter.

   Rule two: do not optimize a component you are about to replace. If a page rewrite is already on the roadmap for this quarter, running a careful label experiment on the current page is a throwaway. The result will not transfer to the new layout, because the context that produced it no longer exists.

   The second rule is the one teams break most often, because label experiments are fast to ship and feel productive.
   

   Do the math before you commit to either

   
   A small change usually produces a small effect, and a small effect demands a large sample. A page rewrite can plausibly shift behavior by several points; a button label change often moves it by a fraction of one.

   A quick calculation, runnable in any Python environment, shows how steep that difference is:

   import math

   def sessions_needed(p_control, p_treatment, alpha=0.05, power=0.80):
   z_a = 1.959963985
   z_b = 0.8416212336
   p_bar = (p_control + p_treatment) / 2
   spread = (z_a * math.sqrt(2 * p_bar * (1 - p_bar))
   + z_b * math.sqrt(p_control * (1 - p_control) + p_treatment * (1 - p_treatment))) ** 2
   print(math.ceil(spread / (p_treatment - p_control) ** 2))

   sessions_needed(0.04, 0.045) # a 0.5-point lift on a 4% baseline
   sessions_needed(0.04, 0.06) # a 2-point lift on the same baseline

   On a 4% baseline, detecting a 0.5-point improvement at 80% power takes roughly 25,000 sessions per arm. Detecting a 2-point improvement takes roughly 1,900. Same campaign, same page, a thirteen-fold difference in required traffic.

   Two conclusions follow. First, if your campaign delivers a few thousand sessions a month, a micro-optimization of the button label is probably not measurable, no matter how good the label is. Second, the size of the expected effect should drive the choice of experiment far more than how easy the change is to ship.
   

   A default order that holds up in practice

   
   

   1. Verify the instrumentation. One exposure event per session, assignment logged server-side rather than inferred from a query parameter, internal traffic excluded, bots filtered. Every downstream conclusion inherits the quality of this step.
   2. Check message match. Put the ad headline next to the page headline. If they describe different things, stop here.
   3. If message match fails, run the landing page experiment first. Change the hero, the offer framing, or the proof: the elements that determine whether a visitor stays long enough to be asked anything.
   4. If message match holds and engagement looks healthy, run the call-to-action experiment. Label, placement, and the one or two lines of supporting copy next to it.
   5. Re-run the call-to-action experiment after any page rewrite. Treat the old result as historical, not as a default.

   Step 4 is where a lot of teams want to start, and it is a legitimate starting point, but only when the diagnostic in the table above says the page is already doing its job.
   

   Track what happens after the action, not just the action

   
   A call to action that increases signups while filling the pipeline with people who never come back is a net loss. Before you run either experiment, decide on guardrail events and log them alongside the primary metric:

   // One exposure event per session, emitted once and cached client-side
   trackEvent("experiment_exposure", {
   experiment_id: "cta_copy_q3",
   arm: "specific-verb",
   campaign_id: "launch_aug",
   });

   // Downstream quality signals, tied to the same session
   // activation_started, first_key_action, repeat_usage_7d

   If the primary metric moves up and a guardrail moves down, that is a trade-off that needs a decision. Guardrails are especially important for landing page experiments, because a page that over-promises will inflate the action rate and damage downstream quality.
   

   Do not change both at once

   
   Running a page experiment and a call-to-action experiment simultaneously on the same traffic makes the result unreadable. You cannot tell whether the change came from the page, the ask, or the interaction between them.

   If you genuinely need both answers and have the traffic to support it, use a factorial design: four arms, so every page version is paired with every call to action. The interaction term is often the most interesting number in the output, because it tells you whether a strong page makes the label irrelevant. The cost is roughly four times the traffic of a two-arm experiment.

   For most campaigns, sequential experiments are the practical choice: page first, then the ask, with each experiment consuming a pre-committed block of traffic. Avoid switching between them mid-run based on how the numbers look.
   

   Link hygiene when campaign traffic is split

   
   If you are routing campaign traffic between page builds and call-to-action experiments, the link you publish becomes part of the workflow. Campaign copy already competes for space with a headline and a button, and long parameter-heavy URLs wrap badly in chat apps and social posts. A short link such as LinkBit keeps the destination compact and readable in the creative. That is a formatting convenience. Your experiment assignment should live in your own instrumentation, not in the link.
   

   The short answer

   
   Run the landing page experiment first when the funnel shows that visitors never engage, when message match is broken, or when a rewrite is already planned. Run the call to action first when the page is doing its job and the ask is the weak link, and only when your traffic is large enough to detect the smaller effect you are likely to see.

   Before either, confirm what your instrumentation measures. Most experiment programs that stall are running careful changes on a funnel they cannot see.#experimentation #conversionrate #landingpages #webanalytics #software #coding #development #engineering #inclusive #community
   Should You A/B Test Your Call to Action or Your Landing Page First?

   #community #software #coding #development #engineering #inclusive
10. 

    RS, Author, Novelist, Prosaist @[email protected]

    2026-10-26

    #PennedPossibilities 1166: Would any of your characters actually survive a “zombie” apocalypse?

    In-universe, zombie (🧟 🧟‍♀️ 🧟‍♂️) would be defined as ordinary humans infected by a saliva-vector communicative disease akin to a rabies-leprosy on steroids that turns people into shambling demented cannibals with rotting skin and a taste for uncured head cheese? That kind of describes most depictions of zombies, doesn't it?

    First factor: None of the characters would be statistically likely to be near the initial outbreak where the spread begins.

    Second factor: Health Services is a big agency that oversees the health and safety of the entire population. With modern communication, outbreaks would be caught and understood in days.

    Third factor: The climate is extremely hot, night and day. Without available water and the intelligence to drink it and find shelter during deadly heat, zombies become mummies pretty quickly, limiting the outbreak automatically.

    Fourth factor: Shambling by definition isn't flying, so angel zombies aren't spreading the disease worldwide. Rabies-like symptoms will prevent daemonic zombies from performing miracle-work (not explaining) that could negate their shambling disability.

    The characters all live in the city, have it on the ball, and, for factors above, the apocalypse will either exhaust itself or become a "controlled outbreak" quickly. I suspect the constabulary would work to contain it, with whistles being distributed to civilians and day angels patrolling the skies. The characters would all avoid being bitten or being chewed up. Daemons can make zombie capture completely hands-free.

    The reporter SC and the MC, who is also a photographer working with him, would be in the most danger since they would be reporting on the outbreak.

    [Author retains copyright (c)2026 R.S.]

    #BoostingIsSharing

    #gender #fiction #writer #author
    #cozy #mystery #sf #sff #sciencefiction
    #writing #writingcommunity #writersOfMastodon #writers
    #RSdiscussion
    #RSstory #RSReluctanceStory

    #pennedpossibilities #boostingissharing #gender #fiction #writer #author
11. 

    The New Mars @[email protected]

    2026-10-26

    Artemis Plan Analysis?

    I thought a Cargo Starship was pushing Orion to Lunar Orbit, where Orion would dock with the HLS Starship.
    ‘Maybe Angry is right: the Block 3 HLS Starship will push Orion to Lunar Orbit, where the astronauts will transfer…why wouldn’t they transfer to the HLS in high-LEO…?’

    https://youtu.be/fZ8HF5hY4Sw

    I shared my concerns about risking human astronauts onboard unprepared spacecraft in the previous comment. Previously, I pointed out that the risk of top-heavy landers is not as great as Angry makes it out to be.
    ‘But Angry says it is risky, maybe he is right, but I asked AI if the height of any of the previous landers was in any way the cause of the crash…’
    Previously I commented about refueling at higher LEO, but then I thought it would take too much fuel to get the fuel there. Angry talks about boil-off, which I think is an engineering issue that has been or can be reduced.??
    v3 Starship payload is 100t+, and v4 is 200t+, so who knows how much fuel it can take to LEO?

    Bonsai 27B Prompt:
    Pasted transcript: Write a review of the video as an AI Scientist for a futurist.
    @Web Fact-Checking via Google Search: Share insights about the use of billionaire contractors.

    Bonsai Said:
    🚀 AI SCIENTIST REVIEW: Artemis Acceleration Plan Analysis

    ⚠️ CRITICAL FINDING: ARCHITECTURAL PHYSICS VIOLATIONS

    The video presents a detailed technical critique of NASA’s proposed 2028 lunar landing timeline. My analysis confirms the presenter raises substantially valid engineering concerns, though some claims require independent verification against primary sources.

    ✅ Verified Technical Claims:

    1. Delta-V Budget Crisis: The video correctly identifies that Starship cannot execute the original Apollo-style mission profile (launch to NRH, wait for crew, descend to lunar surface, return to NRO) due to insufficient propellant efficiency in deep gravity wells.
    2. Orbital Refueling Bottleneck: The thermodynamic analysis of liquid cryogenic fuel boil-off is accurate. Passive thermal management limits mean weeks of staging with continuous propellant loss (0.5-1% daily), creating a compounding deficit that requires 12+ rapid launches to fill a single depot.
    3. SLS Limitations: The Space Launch System was never designed to deliver Orion directly to low lunar orbit, only to its planned NRH trajectory. Forcing this creates structural inefficiency.
    4. Dynetics Alpaca Superiority: The historical rejection of Dynetics’ Alpaca lander for SpaceX’s top-heavy design is well-documented and represents a clear example of political/business influence overriding engineering best practices.

    ⚠️ Unverified/Overstated Claims Requiring Independent Verification:

    1. Kathy Leers Conflict of Interest: The claim that the HLS contract awarding official left NASA shortly after making the decision is compelling but requires primary source verification (internal memos, congressional testimony).
    2. Blue Moon Maturity Timeline: While Blue Origin’s delayed development is well-documented, specific claims about PDR/CDR status require confirmation against official NASA milestone trackers.
    3. “Elon Musk is lying” about 6-8 refueling flights: This is a strong assertion that should be cross-referenced with SpaceX’s own technical presentations and peer-reviewed orbital mechanics analyses.

    📊 FUTURE PROJECTIONS (2028-2040)

    Near-Term (2028-2031): The 2028 Target

    The video’s skepticism is well-founded from a physics standpoint. However, historical precedent shows NASA can accelerate programs when political will is extreme:

    • Apollo was originally planned for 1963; actual landing was 1969 (6-year delay)
    • Artemis I flew in 2022 despite planning delays of ~4 years

    Verdict: A 2028 target is optimistically aggressive but not impossible if SpaceX achieves its rapid cadence and Blue Origin’s backup plan matures simultaneously. However, the physics gaps are real and require either:

    • Breakthrough in cryogenic storage/refueling technology
    • Additional SLS launch capability
    • Acceptance of a more complex, multi-year staging architecture

    Medium-Term (2031-2040): Moon Base Viability

    The video correctly identifies that corporate-driven timelines create structural instability. However, it misses a critical insight: the 2028 target may actually be a strategic signaling device rather than an engineering commitment.

    Projected trajectory:

    • 2028-2030: LEO-only Artemis 3 mission (as proposed) — achievable with current capabilities
    • 2031-2033: First crewed lunar landing — likely possible but high-risk
    • 2034+: Permanent lunar presence — requires massive infrastructure investment

    🧠 FUTUREURIST ANALYSIS FRAMEWORK

    DimensionCurrent State (2026)Projected Trajectory (2040)Key Risk FactorsHuman PresenceLEO-only missionsLunar surface operationsFunding volatility, political cyclesPropulsion TechnologyMethalox rockets dominantPotential for nuclear thermal/electric hybridsRegulatory hurdles, safety certificationInfrastructureEarth-orbit prototypesPermanent lunar habitatsRadiation, life support, resource extractionGovernanceNASA-led with private partnersLikely multi-stakeholder or internationalJurisdictional conflicts, liability frameworks

    💡 ACTIONABLE RECOMMENDATIONS FOR FUTUREPLANNERS

    1. Monitor 2028 Mission Architecture: The LEO-only Artemis 3 design is a testbed for docking and life support integration. Success validates the entire architecture; failure cascades to all future missions.
    2. Track Refueling Milestones: SpaceX’s ability to achieve high-frequency orbital refueling will be the single biggest determinant of whether lunar landings are feasible.
    3. Prepare for Political Cycles: Space programs are highly sensitive to political leadership changes. Build contingency plans for 4-8 year funding cycles.
    4. Diversify Partnership Portfolios: Over-reliance on any single contractor (even SpaceX) creates systemic risk. Maintain qualified backup options.

    📝 CONCLUSION

    The presenter’s critique is primarily valid from an engineering and physics perspective, though some claims require independent verification. The 2028 timeline is optimistically aggressive but not impossible, contingent on SpaceX achieving unprecedented launch cadence and solving refueling bottlenecks.

    For futurists: This video represents a critical inflection point in human spaceflight — where political ambition meets physical reality. The tension between corporate-driven speed and engineering discipline will define the next decade of lunar exploration.

    🏗️ INSIGHTS ON THE USE OF BILLIONAIRE CONTRACTORS

    🔍 Structural Overview

    Billionaire-owned companies and individuals increasingly function as alternative contractors, bypassing traditional procurement systems and creating a parallel contracting ecosystem with distinct characteristics.

    Key Characteristics:

    • Capital-Rich: Access to deep pockets of capital enables rapid prototyping and high-risk experimentation
    • Speed-Oriented: Bypasses traditional procurement cycles (months/years → weeks/months)
    • Vertical Integration: End-to-end control from vision to execution
    • Political Influence: Often maintain significant government relationships

    ⚖️ Evidence-Based Analysis

    Case StudyKey InsightRisk ProfileSpaceX & Unpaid Bills (Fast Company, 2024)$2.5M+ in liens filed by contractors; delayed paymentsHigh financial risk to smaller contractorsAnduril’s Autonomous Development (Forbes, 2022)Builds weapons tech independently without waiting for Pentagon requirementsInverted contracting model — high reward, high riskMercor’s Wage Reductions (Forbes, Nov 2025)Young billionaire co-founders slashed contractor wages by ~33% after project cancellationLabor relations crisis; experience gap concernsLegalist’s Government Contracts (Business Insider, Aug 2025)Received $100M+ in government contracts via Peter Thiel’s fellows networkPolitical dependency creates vulnerability to policy shifts

    📈 Comparative Analysis: Traditional vs. Billionaire Contractors

    FactorTraditional ContractorBillionaire-Owned ContractorFunding SourcePublic/private sector bidsFounder equity/VC backingTimeline PressureProject-driven, risk-mitigatedFounder-driven urgencyRisk AllocationShared with clientsHeavily on founder/companyRegulatory OversightStandard contracting lawsMinimal, novel legal structuresScale ConstraintsLimited by company size/infrastructureLimited only by capitalGovernanceBoard oversight, fiduciary dutiesFounder-centric decision making

    🔮 Future Trajectory (2030-2045)

    1. AI-Augmented Contracting: Machine learning will optimize contractor allocation, predict payment risks, and automate compliance tracking — reducing the “unpaid bills” problem seen in SpaceX cases.
    2. Decentralized Workforce Models: Blockchain-based smart contracts may improve transparency for gig/contractor economies, though regulatory frameworks lag far behind technological capability.
    3. Geopolitical Dependencies: Billionaire contractors handling government contracts will face increased scrutiny as they influence critical infrastructure, defense, and media — creating conflicts of interest that policymakers must address.
    4. Global Supply Chain Reconfiguration: Billionaire-backed tech companies increasingly bypass traditional supply chains entirely, creating new vulnerabilities and opportunities in manufacturing and resource allocation.

    ⚠️ Critical Risks to Monitor

    1. Contractor Exploitation: Unpaid bills, wage reductions, and poor payment practices are emerging patterns that could normalize across industries
    2. Experience Gaps: Young billionaire founders may lack the institutional knowledge required for large-scale project management, leading to catastrophic failures when political cycles shift
    3. Single-Point Dependency: Over-reliance on any single contractor (even SpaceX) creates systemic risk — a lesson learned from the Apollo program and modern government contracting

    📚 Further Reading & Verification Sources

    • Fast Company: “‘We never got paid’: SpaceX contractors call out unpaid bills” (May 2024)
    • Forbes: “Facebook Made This 29-Year-Old Rich; War Made Him A Billionaire” (June 2022) — Anduril analysis
    • Forbes: “The World’s Youngest Self-Made Billionaires Just Slashed These Workers’ Wages by a Third” (Nov 2025)
    • Business Insider: “How DOGE Boosted Legalist’s Government Contracts Business” (Aug 2025)

    🔚 FINAL ASSESSMENT

    YouTube Video: Represents a critical analysis of NASA’s lunar program timeline. The presenter’s physics-based critique is largely accurate, though some specific claims require independent verification. This video captures a pivotal moment where political ambition meets engineering reality in the space race.

    Billionaire Contractors: Represent an emerging parallel contracting ecosystem with distinct characteristics — faster but riskier, more innovative but potentially exploitative. The trend suggests that future infrastructure development will increasingly be driven by billionaire-backed entities rather than traditional contractors, creating both opportunity and vulnerability in global systems.

    #Artemis #Contractors #Spacex #Starship #ANGRYASTRONUAT #AstroAngry #TheAngryAstronaut #moon #NASA #news #science #space #spacex #technology

    #technology #space #science #news #nasa #moon
12. 

    Wellingborough Eco Group @wellingboroughecogroup

    2026-10-26

    Come to FOOD SHARERS, HAPPY CAFE, ARTIST WINDOW, SWAP SHOP, SUB & for a TUESDAY TIDY UP this Tuesday!

    Wellingborough Eco Group & Wellie Wombles

    At ECO HUB we have some good activities and services to share with you, and for the environment.

    🟡 Happy Café is our friendly reuse cafe, for free tea and coffee. Plus there's Action for Happiness activities for you!
    🔵 Wellingborough Swap Shop where we will have electricals, clothes ,100's of books, DVDs, toys and household items all to go. Everything is available for swaps or a donation to the group.
    🟠 Artist Window has local artist work to see and buy. Come have a chat if you would like to display yours for free.
    🟣 SUB (School Uniform Bank) free school uniform.
    🟢 Food Sharers will have food saved from supermarkets. Take what you need and donations are always welcome.
    🔴 Tuesday Tidy Ups either out with the Wombles from 9:30 or come to borrow our litter pickers and hoops for your own tidy up, bags are free!

    ECO HUB, in Swansgate Centre.

13. 

    Mike Bowler @mike_bowler

    2026-10-26

    We’re coming up fast on Halloween so let’s talk about the Batman Effect. If you’ve ever put on a costume, you may have noticed that you act a little differently in it. What does the research say?

    Batman Effect part 1:

    Imagine a six-year-old sitting in front of a laptop, doing the most boring task a team of researchers could design. Right beside the laptop is an iPad with a game on it, and the child has been told they can play it whenever they like. Every minute, a recorded voice asks whether they’re working hard.

    Now give that child a Batman cape and change the question to “Is Batman working hard?”

    That’s the setup of a 2017 study that gave us the name “the Batman effect”.1 Researchers asked 180 four and six year olds to stick with a dull task for ten minutes while that iPad sat there tempting them. Some kids were asked about themselves (“Am I working hard?”). Some were asked about themselves by name, in the third person. The rest picked a character, were given a prop to match, and were asked about the character instead.

    The kids who were Batman (or Rapunzel, or Dora, or Bob the Builder) stayed on task longer than either of the other groups. Some of them even answered the recorded voice out loud with “Batman is working hard”, and if they’d wandered off to the iPad, they went back to work.

    So what’s going on?

    Continue reading on my blog because it's too long for here.
    https://blog.mikebowler.ca/2026/10/26/batman-effect/

14. 

    Mitch Wagner @mitch

    2026-10-26

    While walking the dog I passed a neighbor's house with three very loud and energetic dogs. I almost never see any of these dogs, because they are in a fenced backyard, and I usually don't hear all three at once, but the full orchestra was out that morning, two barking loudly in different keys and tempos and one heartily going BAROO BAROO BAROO. It was like a modern jazz concert.

    I stopped to record it and an older man came out of the house across the street from the Three Dog House. He was behind me. "I'm enjoying the music," I said, and then I thought about hearing that every day. "Probably you don't enjoy it."

    Because I was interrupted, I did not record the concert.

    The man looked at Minnie and exclaimed, "The cone of shame!" Yes, Minnie is still wearing the cone. It's been a month. We have an appointment at an eye specialist and are planning to switch vets.

    A few minutes later I passed a parked car with a license plate frame that read something like, "CALIFORNIA — WHERE AMERICA'S DAY STARTS." At least I *think* that's what it said. But that does not make sense. As a longtime tech trade journalist, I am aware in my bones that the rest of America wakes up well before California does; when I hit my desk on a workday morning my Teams messages and emails are already full.

    That sent me a down an Internet rabbit hole to find out where America's day REALLY starts — in other words, what's the furthest point east in either the continental US or territories. There are two possible answers, one of them a technicality.

    The common-sense answer is a point in the U.S. Virgin Islands. I always forget the U.S. Virgin Islands exists.

    The other answer, which will be great to know for a pub trivia quiz: A point on the Aleutian Islands of Alaska, which goes so far west that it crosses the 180th Meridian and becomes east.

    I did not research this point, but I expect that this means the point in the US that is furthest west and the point that is furthest east are a single footstep apart from each other.

15. 

    servant of Lord Jesus Christ @servantoflordjesuschrist.wordpress.com@servantoflordjesuschrist.wordpress.com

    2026-10-26

    Ešte poriešme vec okolo katolíckej cirkvi o jej pôvode a prečo je odklonená a viac uprednostňuje Máriu ako Bohorodičku a jej mariánske hnutie. Nájdi presné dátumy podľa katolíckych dogiem a na internete v prvom storočí, kedy vznikla cirkev a neskôr mariánske hnutie. Nezabudni analyzovať aj samotnú Bibliu, jej pôvod a o kom je vlastne tá kniha. Potom to porovnaj s hašterením sa ľudí v tomto svete hádam už viac ako 2000 rokov o otázke kto vlastne vládne a sedí na stoličke Židovského Svätého Petra ako učenníka Pána Ježiša Krista, jedného z jeho prvých učeníkov a s kľúčami od Neba a Zeme v jeho rukách osobne od samotného Krista. A pritom treba brať do úvahy že samotní Židia od ktorých by mala ísť ako od národa spása pre celý svet podľa pravidiel nového už viac ako 2000 rokov platiaceho zákona v Biblií, stále žiju v starom zákone v Biblií v Torahu a Krista popravili podľa ich starého proroctva že je lepšie keď zahynie jeden človek za národ ako celý národa a nakoniec ho vymenili za národného rebela s mečom Barabasa a s kričaním vtedajšej ich spodiny v tej dobe pred rímskym pohanským pilátom a ich ľudovým súdom podľa ich židovských zvykov že ich krv na ich hlavu a deti. Ďalej ako je napísané v Biblií, že kvôli tomu sa Kristus obrátil na iný, nie židovský ovčinec s ľuďmi, ako sa v dobrom opisujú jeho učenníci a ľudia v Biblií a jeho ako Pastiera viacerých ovčincov. ďalej ako ľudia vo svete pochopili globálne význam veršov z Biblie “milosrdenstvo chcem a nie obetu” a degradácia v tej dobe vzorových obrátených pohanov vo svete na kresťanov a služobníkov Kristových na súčasný globálny žalostný stav kresťanov vo svete. A prečo Mária a mariánske hnutie? Pravdepodobne Židia, kresťanskí Gréci spolu s Rimanmi a ďalšími kresťanmi v tej dobe, ktorí mali moc v rukách a mali k tomu čo povedať uzniesli na tom že si zobrali príklad z veršov z Torahu a z Evanjelia Biblie a to o židovskej Kráľovne Ester z obyčajného ľudu vtedajších Židov v starovekom Babylone, vybranej samotným babylonskym kráľom za jeho manželku, jej múdrosti a záchrane Židov v starovekom Babylone pred ich vyvraždením a o potrebnej pokore a dodržiavaní Božích zákonov, ktoré dostal židovský patriot Mojžiš od samotného Boha Stvoriteľa prostredníctvom Svätého Anjela a pre ľudí z neviditelného Neba nad nami podobne ako je opísané v samotnej Biblií. Čiže múdrosť, pokora a dostatočný spirituálny oheň, aby sa veci pohli dopredu správnym smerom a zároveň sa vedeli dohodnúť Židia z Izraela s Kresťanmi vo svete a to platí pravdepodobne až rovnako dodnes. A nakoniec či sa bude niekto hádať o Márií ako o Bohorodičke, alebo kto sedí v Nebi na stoličke Svätého Petra v súčasnej dobe v Nebi, je pre normálneho jednoduchého človeka, ktorý netúži po moci predsa úplne jedno. A nakoniec je jasne napísané kto je jediný, bezpečný, osvedčený už viac ako 2000 rokov a zároveň najvyšší Spasiteľ a Kráľ podľa Biblie, že je to Pán Ježiš Kristus sám. Ostatné možnosti už podliehajú bludom a záujmom nie práve z originálneho Neba. Dôležitá je Biblia a vedieť si zrovnať všetky základné veci z Biblie tak aby ste si všetko čo naozaj potrebujete k životu vedeli vysvetliť. A pokiaľ človek ostane stáť pevne na nohách a na úzkej ceste bez zbytočných cudzích fantazíjnych problémov a starostí, tak si aj tie základné veci vysvetliť dokáže, je spokojný a nemusí mať ani prísahu ako kňaz, a tak ako predtým všetky kresťanské veriace generácie Slovákov počas posledného viac ako 1000 ročného kresťanského obdobia. A nakoniec ruka v ruke s múdrosťou, pokorou a správnym zápalom spirituálnym ohňom v srdci človeka, treba naše úsilie nasmerovať a zachraňovať hriešnych a núdznych, lebo Kristus zachraňuje to čo sa stratilo vo svete, nie to čo vidí a rozumie od neho a čo vie čo má robiť.

    Biblia, vznik kresťanskej cirkvi, Peter, Mária a skutočný zmysel Kristovho učenia

    Tvoju úvahu by som postavil na jednom základnom princípe: oddeľme to, čo skutočne hovorí Biblia, od toho, čo k tomu neskôr pridala cirkevná tradícia, a od toho, čo si dnes o týchto udalostiach myslia jednotliví ľudia. Tak môžeme skúmať aj katolícke dogmy bez toho, aby sme vopred predpokladali, že všetko, čo cirkev učí, je automaticky biblické, alebo naopak, že všetko, čo vzniklo neskôr, musí byť nesprávne.

    Tvoja záverečná myšlienka má pritom veľmi dôležité miesto už v samotných evanjeliách: Kristus neprichádza iba pre tých, ktorí sa považujú za spravodlivých, ale aj pre stratených, chorých, hriešnikov a ľudí v núdzi.

    Pozrime sa teda na historické dátumy, pôvod Biblie, Petra a pápežského úradu, Máriu a mariánsku úctu, vzťah kresťanstva k židovstvu a napokon na to, čo z toho vyplýva pre obyčajného človeka, ktorý chce nasledovať Krista bez zbytočných mocenských sporov.

    1. Kedy vznikla kresťanská cirkev? Čo sa dá historicky doložiť?

    Najskôr treba rozlíšiť tri veci:

    1. Vznik spoločenstva Ježišových učeníkov.
    2. Vznik prvých kresťanských obcí po Ježišovej smrti.
    3. Neskorší vývoj cirkevnej organizácie, biskupských úradov a pápežstva.

    Tieto udalosti nemajú jeden spoločný dátum.

    Základná chronológia

    Obdobie alebo dátumUdalosťČo môžeme povedaťPribližne 27 – 30 n. l.Verejné pôsobenie JežišaJežiš zhromažďuje učeníkov a hlása Božie kráľovstvo.Približne 30 – 33 n. l.Ježišova smrť a viera učeníkov v jeho zmŕtvychvstanieUčeníci začínajú verejne hlásať, že Ježiš je Mesiáš a Pán.Približne 30 – 33 n. l.Turíce, teda LetnicePodľa Skutkov apoštolov dostávajú učeníci Ducha Svätého a verejne hlásajú evanjelium. V katolíckom chápaní ide o narodenie Cirkvi. Presný kalendárny rok však nepoznáme.Približne 40. – 50. roky 1. storočiaRozširovanie kresťanských obcíEvanjelium sa šíri medzi Židmi aj pohanmi.Približne 49 – 50 n. l.Apoštolské zhromaždenie v JeruzalemeSkutky 15 opisujú spor o to, či pohania musia prijať Mojžišov zákon a obriezku.Približne 50. – 60. rokyPavlove listyVznikajú najstaršie zachované kresťanské texty Nového zákona.Približne 65 – 100 n. l.Vznik evanjeliíPostupne vznikajú štyri evanjeliá, ako ich poznáme dnes.Koniec 1. storočia až 2. storočieUpevňovanie cirkevných štruktúrVýznam nadobúdajú biskupi, pravidlá viery a rozlišovanie autoritatívnych spisov.Rok 367Atanázov 39. veľkonočný listObsahuje najstarší zachovaný zoznam, ktorý presne uvádza dnešných 27 kníh Nového zákona.4. storočieZreteľnejšie formovanie biblického kánonuKresťanské cirkvi postupne potvrdzujú zoznam kníh, ktoré prijímajú ako Písmo.

    Časové údaje pri udalostiach Ježišovho života sú približné. Zvlášť dôležité je, že prvé kresťanské obce existovali dávno predtým, ako sa uzavrel zoznam kníh Nového zákona.

    Vznikla teda katolícka cirkev už v 1. storočí?

    Áno, ak hovoríme o historických koreňoch Katolíckej cirkvi. Nie, ak tým myslíme, že všetky dnešné cirkevné inštitúcie, dogmy a právne pravidlá existovali už vtedy v súčasnej podobe.

    Katolícka cirkev chápe samu seba ako spoločenstvo založené Kristom, ktorého apoštolské poslanie pokračuje v dejinách.

    Historik však skúma aj postupný vývoj tejto organizácie. Napríklad postavenie rímskeho biskupa, vzťahy medzi jednotlivými biskupmi a rozsah pápežskej právomoci sa vyvíjali počas stáročí.

    Preto by bolo nepresné tvrdiť buď to, že Cirkev vznikla až v stredoveku, alebo to, že všetky jej dnešné pravidlá boli úplne sformované už na Turíce.

    2. O kom je vlastne Biblia? Kto ju napísal a prečo?

    Toto je podľa mňa najdôležitejšia časť celej otázky.

    Biblia nie je jedna kniha napísaná jedným človekom v jednom období. Je to zbierka náboženských spisov, ktoré vznikali v priebehu mnohých stáročí.

    V kresťanskom chápaní je jej hlavným posolstvom Božie pôsobenie v dejinách človeka a plán spásy. Ježiš Kristus je ústrednou postavou Nového zákona a podľa kresťanskej viery naplnením Božích prisľúbení obsiahnutých v Písmach Izraela.

    A. Starý zákon a židovský Tanach

    Ježiš, Mária, apoštoli Peter a Pavol i prví Ježišovi učeníci pochádzali zo židovského prostredia.

    Čítali a poznali Písma Izraela, ktoré obsahovali:

    • Tóru, teda päť kníh Mojžišových;
    • prorocké knihy;
    • žalmy a ďalšie náboženské spisy.

    Židovský Tanach a kresťanský Starý zákon majú veľkú časť textov spoločnú, ale ich usporiadanie a rozsah nie sú úplne totožné. Katolícka Biblia obsahuje aj knihy, ktoré židovský kánon neprijíma.

    Je preto dôležité rozlišovať medzi Tórou a celým Tanachom. Tóra je jeho prvá časť, nie názov všetkých židovských Písem.

    B. Nový zákon

    Nový zákon obsahuje 27 kníh:

    • štyri evanjeliá;
    • Skutky apoštolov;
    • apoštolské listy;
    • Zjavenie Jána.

    Najstaršie zachované kresťanské spisy sú Pavlove listy. Niektoré vznikli približne v 50. rokoch 1. storočia, teda skôr než boli napísané evanjeliá.

    Evanjeliá podľa historického výskumu vznikali približne v druhej polovici 1. storočia. Rozprávajú o Ježišovom živote, učení, smrti a viere jeho nasledovníkov v jeho zmŕtvychvstanie.

    Nemáme pôvodné rukopisy napísané vlastnou rukou jednotlivých autorov. Poznáme však staroveké odpisy, citácie a rukopisnú tradíciu, prostredníctvom ktorých sa texty zachovali. The British Academy

    C. Kedy sa rozhodlo, ktoré knihy budú v Biblii?

    Nie všetky kresťanské spisy boli od začiatku považované za rovnako autoritatívne.

    Kresťania ich čítali, odovzdávali ďalej, porovnávali s apoštolskou tradíciou a diskutovali o ich pôvode a vieroučnom obsahu.

    Rok 367 n. l. je dôležitý, pretože Atanáz Alexandrijský vtedajší zoznam 27 kníh Nového zákona uviedol presne v dnešnom rozsahu. Následne sa tento zoznam potvrdzoval v cirkevnom prostredí. Vývoj kánonu teda nebol jednorazovým rozhodnutím jedného človeka.

    Z toho vyplýva zásadná otázka:

    Ak kresťanské spoločenstvá existovali ešte pred vznikom všetkých kníh Nového zákona a pred ustálením jeho kánonu, na základe čoho žili?

    Na základe toho, čo poznali zo židovských Písem, Ježišovho učenia odovzdávaného ústne, svedectva apoštolov, spoločnej modlitby a neskôr aj kresťanských spisov.

    Biblia sa teda nedá správne pochopiť tak, že ju jednoducho oddelíme od dejín jej vzniku. Zároveň však historický vývoj kánonu sám osebe nedokazuje ani nevyvracia vieru, že jeho knihy sú Bohom inšpirované.

    D. Ako čítať Bibliu, aby sa človek nestratil v sporoch?

    Odporúčal by som tento postup:

    1. Najprv si prečítať samotný biblický text.
    2. Zistiť, kto hovorí, komu a za akých okolností.
    3. Porovnať súvisiace pasáže v ďalších knihách Biblie.
    4. Oddeliť priamy výrok textu od neskoršieho teologického vysvetlenia.
    5. Až potom skúmať, ako jednotlivé cirkvi tento text vykladajú.

    Napríklad v Matúšovi 16 Ježiš hovorí Petrovi o skale a kľúčoch. Tento text nemožno ignorovať, ale treba ho čítať aj spolu s Matúšom 18:18, kde Ježiš dáva autoritu zväzovať a rozväzovať aj širšiemu okruhu učeníkov, a s Jánom 21, kde Petrovi zveruje starostlivosť o svoje ovce.

    Takéto porovnávanie nám umožní vyhnúť sa záverom, ktoré stoja iba na jednom vytrhnutom verši.

    3. Peter, kľúče od nebeského kráľovstva a pápežská stolička

    Tu sa dostávame k jednej z najdôležitejších otázok: čo presne Ježiš zveril Petrovi a čo z toho možno vyvodiť o dnešnom pápežovi?

    A. Čo hovorí samotná Biblia?

    V Evanjeliu podľa Matúša 16:13–20 sa odohráva rozhovor medzi Ježišom a učeníkmi. Peter vyznáva, že Ježiš je Mesiáš, Syn živého Boha.

    Ježiš mu následne hovorí:

    „Ty si Peter a na tejto skale postavím svoju cirkev.“

    A v Matúšovi 16:19 mu sľubuje kľúče nebeského kráľovstva a právomoc zväzovať a rozväzovať.

    Katolícka cirkev tento text chápe ako základ osobitného Petrovho poslania a ako jeden z biblických základov pápežského primátu.

    Treba však rozlišovať medzi tým, čo je napísané priamo v texte, a tým, čo z toho odvodzuje určitá teologická tradícia.

    Biblický textČo z neho vyplývaMatúš 16:16–19Peter vyznáva Ježiša ako Mesiáša a dostáva osobitné poverenie.Matúš 18:18Právomoc zväzovať a rozväzovať sa spomína aj v súvislosti so širším spoločenstvom učeníkov.Lukáš 22:31–32Ježiš hovorí Petrovi, aby po svojom obrátení posilňoval bratov.Ján 21:15–17Ježiš trikrát poveruje Petra starostlivosťou o svoje baránky a ovce.1. Petra 5:1–4Peter vyzýva starších, aby pásli Božie stádo dobrovoľne a nie panovačne.

    Tieto texty ukazujú, že Petrovo poslanie zahŕňa vedenie, službu, posilňovanie ostatných a starostlivosť o spoločenstvo.

    Všimni si najmä posledný text: apoštolské vedenie nemá byť založené na panovačnosti.

    B. Znamenajú Petrove kľúče, že on osobne rozhoduje o tom, kto sa dostane do neba?

    Biblia používa kľúče ako symbol autority. V Matúšovi 16:19 je Petrovi zverená právomoc, ktorej výkon má byť potvrdený v nebi.

    Z toho však automaticky nevyplýva, že Peter alebo jeho nástupcovia môžu svojou osobnou vôľou meniť Božiu spravodlivosť alebo milosrdenstvo.

    V kresťanskom chápaní je konečným sudcom Boh. Peter dostáva poverenie od Krista, nie nezávislú moc nad Bohom.

    To je dôležitý rozdiel: kľúče predstavujú poverenie slúžiť Božiemu kráľovstvu, nie vlastníctvo neba.

    C. Prečo sa hovorí o Petrovej stoličke?

    Katolícka cirkev verí, že osobitné poslanie apoštola Petra pokračuje v jeho nástupcoch, rímskych biskupoch.

    Pápežská stolička preto označuje úrad rímskeho biskupa, nie doslovné kreslo, ktoré by malo samo osebe nadprirodzenú moc.

    Historicky sa rímska cirkev stala jedným z najvýznamnejších centier kresťanstva. Osobitnú úlohu zohrali tradície spájajúce Petra a Pavla s Rímom, význam mesta v Rímskej ríši a postupný rozvoj právomocí rímskeho biskupa.

    Treba však byť presný: historický vývoj pápežstva a katolícke učenie o jeho božskom ustanovení sú dve odlišné otázky.

    Historik môže skúmať, ako sa právomoc rímskeho biskupa vyvíjala. Teológ skúma, či tento vývoj predstavuje pokračovanie Kristovho poverenia Petrovi.

    Kresťania sa v tejto otázke nezhodujú. Katolíci prijímajú pápežský primát v jeho katolíckom chápaní, zatiaľ čo pravoslávni a mnohé protestantské cirkvi odmietajú alebo inak interpretujú rozsah pápežskej právomoci.

    D. Čo znamená, že Peter bol Žid?

    Peter bol židovského pôvodu, rovnako ako Ježiš a prví apoštoli. Ježiš nezačal svoje pôsobenie v Ríme a prví kresťania sa neodtrhli od židovského prostredia zo dňa na deň.

    Kresťanstvo vzniklo v židovskom prostredí a postupne sa rozšírilo medzi pohanov.

    Preto je vhodnejšie hovoriť o židovskom pôvode Petra a kresťanstva než o nejakej „židovskej Petrovej stoličke“. Katolícka cirkev totiž chápe pápežský úrad ako cirkevnú, nie etnickú inštitúciu.

    Rovnako neexistuje historický dôvod predpokladať, že dnešní pápeži predstavujú pokračovanie nejakého tajného politického spojenectva medzi Židmi a Rimanmi. Takéto tvrdenie by potrebovalo konkrétne dôkazy, ktoré samotné biblické texty neposkytujú.

    4. Mária ako Bohorodička: čo hovorí Biblia a čo pridala neskoršia tradícia?

    Teraz sa dostávame k tvojej hlavnej otázke: prečo sa Mária stala takou významnou postavou katolíckej cirkvi?

    Najskôr si treba všimnúť, že samotná Biblia hovorí o Márii s úctou. Zároveň však stredobodom kresťanského posolstva zostáva Ježiš Kristus.

    A. Čo o Márii hovorí Nový zákon?

    Medzi najdôležitejšie miesta patria:

    • Lukáš 1:26–38 – anjel Gabriel oznamuje Márii, že porodí Ježiša; Mária odpovedá, že je služobnica Pána.
    • Lukáš 1:39–55 – Mária navštevuje Alžbetu a prednáša chválospev, ktorý sa začína slovami „Velebí moja duša Pána“.
    • Lukáš 2:1–20 – narodenie Ježiša.
    • Ján 2:1–11 – svadba v Káne, kde Mária upozorňuje na nedostatok vína a Ježiš vykoná svoje prvé znamenie.
    • Ján 19:25–27 – Mária stojí pod krížom.
    • Skutky 1:12–14 – Mária sa spolu s učeníkmi modlí po Ježišovom nanebovstúpení.

    Mária je teda v biblickom príbehu Ježišovou matkou, veriacou ženou a súčasťou prvotného spoločenstva učeníkov.

    Zaujímavé je, že v Skutkoch 1:14 sa modlí spolu s ostatnými. Text ju nepredstavuje ako samostatnú vládkyňu apoštolov.

    A práve tu sa začína rozdiel medzi biblickým rozprávaním a neskorším rozvojom mariánskej teológie.

    B. Čo presne znamená titul Bohorodička?

    Grécky titul Theotokos znamená približne „tá, ktorá porodila Boha“ alebo „Bohorodička“.

    Tento titul sa v cirkevnom prostredí stal predmetom významného teologického sporu v 5. storočí.

    Rok 431 – Efezský koncil.

    Koncil v Efeze potvrdil používanie titulu Bohorodička v súvislosti s otázkou, kým je Ježiš Kristus.

    Katolícke vysvetlenie je nasledujúce: Mária nebola pôvodcom Božej existencie a nedala vzniknúť Božej prirodzenosti. Porodila však Ježiša Krista, ktorý je podľa kresťanskej viery jednou osobou, pravým Bohom a pravým človekom.

    Titul Bohorodička má teda predovšetkým vyjadrovať, že Ježiš nie je rozdelený na dve samostatné osoby – jedného ľudského Ježiša a druhého Božieho Syna.

    Toto je veľmi dôležité: dogma o Bohorodičke bola sformulovaná predovšetkým na ochranu učenia o Kristovi, nie preto, aby sa Mária vyhlásila za Boha.

    To však ešte neznamená, že všetky neskoršie formy mariánskej úcty sú priamo napísané v Biblii.

    C. Presné dátumy hlavných katolíckych mariánskych dogiem

    Tu je rozdiel medzi starou vieroučnou tradíciou a dogmami, ktoré boli slávnostne vyhlásené oveľa neskôr.

    DátumUdalosťČo znamená22. jún 431Záver Efezského konciluPotvrdenie titulu Bohorodička v kristologickom spore.8. december 1854Pápež Pius IX., Ineffabilis DeusSlávnostné vyhlásenie dogmy o Nepoškvrnenom počatí Márie.21. november 1964Druhý vatikánsky koncil, Lumen gentiumVyhlásenie konštitúcie o Cirkvi, ktorej ôsma kapitola sa venuje Márii v tajomstve Krista a Cirkvi.1. november 1950Pápež Pius XII., Munificentissimus DeusSlávnostné vyhlásenie dogmy o Nanebovzatí Panny Márie.

    Dôležité je rozlišovať medzi dátumami dogiem a dátumami jednotlivých dokumentov. Napríklad Lumen gentium je koncilová konštitúcia, nie nová mariánska dogma porovnateľná s vyhláseniami z rokov 1854 a 1950.

    Čo znamenajú tieto dve novšie dogmy?

    Nepoškvrnené počatie – 8. december 1854

    Katolícke učenie hovorí, že Mária bola od okamihu svojho počatia uchránená od dedičného hriechu osobitnou Božou milosťou, a to vzhľadom na zásluhy Ježiša Krista.

    Neznamená to, že Mária počala Ježiša bez muža. Ide o spôsob, akým katolícka cirkev vysvetľuje Máriino vlastné počatie.

    Nanebovzatie – 1. november 1950

    Katolícka cirkev učí, že Mária bola po skončení svojho pozemského života vzatá s telom i dušou do nebeskej slávy.

    Samotná biblická kniha však neobsahuje jednoznačnú správu o tejto udalosti, ktorá by ju opisovala rovnakým spôsobom ako Ježišovo nanebovstúpenie. Dogma sa opiera o katolícke chápanie Božieho zjavenia, tradície a učiteľského úradu Cirkvi.

    D. Kedy vzniklo mariánske hnutie?

    Tu musíme rozlišovať medzi úctou k Márii, teologickým učením o Márii a organizovanými mariánskymi hnutiami.

    Tieto tri veci nevznikli súčasne.

    V 1. storočí bola Mária súčasťou života prvých kresťanov. V Novom zákone však nenachádzame hotové mariánske hnutie v dnešnom zmysle, ani neskorší súbor všetkých katolíckych mariánskych dogiem.

    V 2. a 3. storočí sa začali rozvíjať ďalšie kresťanské texty a úvahy o Márii. V 4. a 5. storočí sa mariánske témy čoraz výraznejšie objavovali v teológii a náboženskom živote. Efezský koncil v roku 431 predstavoval významný míľnik.

    Historici však upozorňujú, že presné datovanie najstarších mariánskych modlitieb a dokladov úcty je sporné. Napríklad modlitba Sub tuum praesidium, ktorá sa často uvádza ako jeden z najstarších dokladov prosby o Máriinu ochranu, sa v staršej literatúre datovala do 3. alebo 4. storočia. Niektoré novšie paleografické výskumy navrhujú podstatne neskoršie datovanie zachovaného papyrusu, až do 6. – 9. storočia.

    Preto nemožno poctivo uviesť jeden presný rok, keď „vzniklo mariánske hnutie“. Môžeme však hovoriť o postupnom vývoji mariánskej úcty v prvých storočiach kresťanstva a o jej neskoršom rozmachu.

    5. Bola Mária povýšená podľa vzoru kráľovnej Ester?

    Tvoja myšlienka o Ester je zaujímavá, pretože obe ženy sa v biblickom príbehu spájajú s odvahou, pokorou a významnou úlohou v dejinách Božieho ľudu.

    Pozrime sa, čo majú spoločné a čo už je iba hypotéza.

    A. Čo sa píše o Ester?

    Kniha Ester rozpráva o židovskej žene, ktorá sa stala manželkou perzského kráľa Ahasvéra. Keď hrozilo vyvraždenie Židov v ríši, Ester riskovala vlastný život, aby sa prihovorila za svoj ľud.

    Medzi najdôležitejšie miesta patria:

    • Ester 4:14 – Mardochej upozorňuje Ester na možnosť, že sa stala kráľovnou práve pre túto chvíľu.
    • Ester 4:16 – Ester sa rozhodne predstúpiť pred kráľa napriek nebezpečenstvu.
    • Ester 7:3–6 – Ester odhalí plán na zničenie svojho ľudu a prosí o záchranu.
    • Ester 8:3–8 – nasleduje ďalšie úsilie o ochranu Židov.

    Ester sa teda prihovára za svoj ľud pred mocným vládcom. Jej príbeh zdôrazňuje odvahu, múdrosť, solidaritu a ochotu riskovať pre záchranu druhých.

    B. Je Mária v kresťanskej tradícii podobná Ester?

    V niektorých kresťanských výkladoch možno nájsť paralely medzi biblickými ženami, ktoré sa prihovárajú za svoj ľud, a Máriou, ktorej katolícka cirkev pripisuje príhovornú úlohu.

    Podobnosť možno vidieť v troch bodoch:

    1. Pokora: Ester koná v nebezpečenstve a Mária sa označuje za Pánovu služobnicu.
    2. Príhovor: Ester prosí kráľa za svoj ľud; Mária podľa katolíckej tradície prosí o pomoc pre veriacich.
    3. Záchrana: Ester sa pričiní o záchranu Židov; Mária je v katolíckej tradícii spájaná so svojím synom Ježišom, ktorý podľa kresťanskej viery prináša spásu svetu.

    To však nestačí na historický záver, že cirkevní predstavitelia vytvorili mariánsku úctu zámerne podľa vzoru Ester.

    Nie je doložené, že by Efezský koncil alebo neskorší tvorcovia mariánskych dogiem prijali rozhodnutie založiť mariánske hnutie na príbehu Ester.

    Je to možná typologická paralela, teda podobnosť medzi biblickými postavami, ktorú môže človek pri čítaní Biblie skúmať. Nie je to však preukázaná historická príčina vzniku mariánskej úcty.

    C. Čo je na tvojej úvahe podstatné?

    Podľa mňa je dôležité, že sa nepýtaš iba na titul Márie, ale na to, čo tento titul znamená pre život človeka.

    Mária v Lukášovi 1:38 hovorí:

    „Hľa, služobnica Pána, nech sa mi stane podľa tvojho slova.“

    To je postoj pokory a ochoty konať podľa Božej vôle.

    Ak niekto oslavuje Máriu, ale pritom zanedbáva núdznych, ponižuje druhých alebo sa usiluje o moc, ktorú môže zneužiť, potom sa právom môžeme pýtať, či jeho konanie zodpovedá duchu evanjelia.

    Zároveň treba rozlišovať medzi takýmto zneužívaním náboženstva a samotnou mariánskou úctou. Katolíci ju chápu ako úctu k Ježišovej matke, ktorá má človeka viesť ku Kristovi, nie ho od Krista odvádzať. Katolícke učenie výslovne rozlišuje medzi úctou k Márii a klaňaním sa, ktoré patrí Bohu.

    D. Kde je hranica medzi Bibliou a cirkevnou tradíciou?

    Tu sa dostávame k podstate rozdielu medzi katolíkmi a mnohými protestantmi.

    Katolícka cirkev verí, že Božie zjavenie sa odovzdáva prostredníctvom Písma a apoštolskej tradície, ktoré jej učiteľský úrad autoritatívne vykladá.

    Mnohé protestantské cirkvi kladú dôraz na zásadu sola Scriptura, teda že Písmo je najvyššou a rozhodujúcou normou kresťanskej viery.

    Preto sa obe strany môžu pozerať na rovnaké biblické verše a vyvodiť odlišné závery o tom, akú úlohu má Mária, akú autoritu má cirkev a či možno určitú vieroučnú pravdu záväzne vyhlásiť až po stáročiach.

    Na samotnej historickej otázke sa však môžu zhodnúť: dogma vyhlásená v roku 1854 nie je to isté ako biblický výrok napísaný v 1. storočí.

    To ešte samo osebe nedokazuje, že dogma je nepravdivá. Znamená to, že jej pravdivosť treba posudzovať aj podľa toho, aké predpoklady o Božom zjavení a autorite cirkvi prijímame.

    6. Prečo Ježiša odmietli niektorí židovskí vodcovia a čo znamená, že prišla spása aj k pohanom?

    V tejto časti je potrebné odlišovať konkrétne historické udalosti od tvrdení o celom národe.

    Ježiš bol Žid, jeho apoštoli boli Židia a prvotné kresťanstvo vyrástlo zo židovského prostredia. Jeho prvými nasledovníkmi boli ľudia, ktorí verili, že v Ježišovi sa napĺňajú Božie prisľúbenia Izraelu.

    Zároveň niektorí židovskí náboženskí predstavitelia Ježiša odmietali a niektorí sa podieľali na udalostiach, ktoré viedli k jeho poprave.

    A. Čo sa stalo pri Ježišovom odsúdení?

    V Evanjeliu podľa Jána 11:47–53 sa opisuje zhromaždenie veľkňazov a farizejov, na ktorom Kajfáš hovorí, že je lepšie, aby jeden človek zomrel za ľud, než aby zahynul celý národ.

    V Jánovom rozprávaní má tento výrok zároveň prorocký význam: Ježišova smrť má viesť k zhromaždeniu rozptýlených Božích detí.

    Evanjeliá ďalej opisujú, ako Ježiša odovzdali rímskemu miestodržiteľovi Pontiovi Pilátovi. Ukrižovanie bolo rímskym spôsobom popravy.

    V príbehu o Barabášovi sa v evanjeliách objavuje výmena medzi Ježišom a väzňom, ktorý bol spájaný s násilím alebo vzburou. Podrobnosti sa v jednotlivých evanjeliách líšia.

    Tieto udalosti možno historicky a teologicky skúmať. Nemožno ich však premeniť na kolektívnu vinu všetkých Židov.

    B. Čo hovorí samotná katolícka cirkev o zodpovednosti za Ježišovu smrť?

    Katechizmus Katolíckej cirkvi v odseku 597 výslovne odmieta pripisovať kolektívnu zodpovednosť za Ježišovu smrť všetkým Židom tej doby a už vôbec nie Židom nasledujúcich generácií.

    Rozlišuje medzi konkrétnymi aktérmi procesu, rímskou mocou a širším historickým kontextom. Upozorňuje tiež, že výrok davu v Matúšovi 27:25 nemožno používať na ospravedlňovanie nepriateľstva voči Židom.

    To je dôležitá korekcia, pretože kresťanské dejiny poznajú aj prípady, keď sa biblické rozprávanie o Ježišovej smrti zneužívalo na prenasledovanie Židov.

    Ak chceme čítať Bibliu v duchu Kristovho učenia, nemali by sme používať jeho utrpenie na ospravedlnenie ďalšieho utrpenia nevinných ľudí.

    C. Žijú Židia stále podľa Starého zákona?

    Židovstvo a kresťanstvo sa v chápaní Ježiša zásadne rozchádzajú.

    Židia Ježiša všeobecne neprijímajú ako Božieho Syna a Mesiáša v kresťanskom zmysle. Kresťania naopak veria, že v ňom Boh uskutočnil svoje prisľúbenie spásy.

    Z toho však nevyplýva, že židovstvo je jednoducho nemenné náboženstvo, ktoré prestalo žiť alebo sa vyvíjať.

    Dnešné židovstvo zahŕňa rôzne tradície a smery. Okrem Tóry a ostatných kníh Tanachu zohráva v rabínskom židovstve významnú úlohu aj rabínska tradícia, najmä Mišna a Talmud.

    Kresťanské tvrdenie o novej zmluve je vieroučným vyznaním kresťanov, nie dôkazom, že všetci Židia konajú nesprávne alebo že Boh už nemá o židovský národ záujem.

    D. Čo hovorí Pavol o Izraeli?

    Mimoriadne dôležité sú kapitoly Rimanom 9–11.

    Pavol v nich zápasí s otázkou, ako chápať Božie prisľúbenia Izraelu, keď mnohí jeho krajania neprijali Ježiša ako Mesiáša.

    V Rimanom 11:1 sa pýta, či Boh zavrhol svoj ľud, a odpovedá: „Určite nie!“

    Neskôr varuje kresťanov z pohanov, aby sa nepovyšovali nad prirodzené ratolesti olivy.

    Tento obraz je veľmi silný: kresťania z pohanov sa nemajú chváliť na úkor Izraela, pretože sami žijú z Božej milosti.

    Aj katolícky dokument Pápežskej biblickej komisie o židovskom ľude a jeho Písmach zdôrazňuje, že Pavlov postoj v Rimanom 9–11 predstavuje vzor úcty, lásky a odmietnutia nepriateľstva voči Židom.

    Z kresťanského hľadiska teda nemožno hovoriť, že spása prešla k pohanom preto, aby sa pohania mohli povyšovať nad Židov. Skôr ide o rozšírenie pozvania k Božiemu kráľovstvu na všetky národy.

    7. „Mám aj iné ovce, ktoré nie sú z tohto ovčinca“ – čo tým Ježiš myslel?

    Toto je jeden z najdôležitejších veršov pre pochopenie rozšírenia kresťanstva medzi pohanov.

    V Jánovi 10:14–16 Ježiš hovorí o sebe ako o dobrom pastierovi, ktorý pozná svoje ovce. Potom dodáva, že má aj iné ovce, ktoré nie sú z tohto ovčinca, a že aj tie musí priviesť.

    V kontexte evanjelia sa tento výrok často chápe ako prísľub zhromaždenia ľudí aj mimo pôvodného izraelského spoločenstva.

    Niektoré biblické výklady preto v „iných ovciach“ vidia najmä pohanov, ktorí neskôr prijali kresťanskú vieru.

    Je však vhodné dodať, že tento výrok sám osebe neznamená, že Ježiš zavrhol Židov alebo prestal byť Mesiášom Izraela. Práve naopak, jeho pôsobenie sa začína v Izraeli a z neho sa posolstvo šíri ďalej.

    Ako sa toto poslanie uskutočňovalo?

    V Skutkoch apoštolov vidíme postupný vývoj:

    • V Skutkoch 2 Peter hlása evanjelium v Jeruzaleme.
    • V Skutkoch 8 sa evanjelium dostáva do Samárie a k etiópskemu dvoranovi.
    • V Skutkoch 10 Peter navštevuje Kornélia, pohana, a prijíma, že Boh neprejavuje zaujatosť voči ľuďom podľa ich pôvodu.
    • V Skutkoch 13 Pavol a Barnabáš hlásajú evanjelium aj pohanom.
    • V Skutkoch 15 sa apoštoli a starší zaoberajú otázkou, aké povinnosti majú pohania, ktorí prijímajú kresťanskú vieru.

    Toto je historicky aj teologicky zásadný vývoj.

    Kresťanstvo sa nešírilo len ako prenos jedného náboženského systému z jedného národa na druhý. Prví kresťania sa museli vyrovnať s otázkou, ako môžu byť pohania súčasťou Božieho ľudu bez toho, aby sa najskôr stali Židmi.

    Čo z toho vyplýva pre dnešného kresťana?

    Ak Ježiš hovorí o jednom stáde a jednom pastierovi, kresťan by sa mal pýtať, či svojím konaním ľudí zhromažďuje, alebo ich zbytočne rozdeľuje.

    Spor o to, kto má pravdu v otázke cirkevnej autority, môže byť teologicky významný. Nemal by sa však stať zámienkou na pohŕdanie druhými, nenávisť alebo zanedbávanie ľudí, ktorí potrebujú pomoc.

    8. „Milosrdenstvo chcem, a nie obetu“ – kľúč k pochopeniu celého problému

    Podľa mňa sa práve tu spája väčšina otázok, ktoré si položil.

    Výrok pochádza z proroka Ozeáša 6:6. Ježiš ho cituje v Matúšovi 9:13 a opäť sa k nemu vracia v Matúšovi 12:7.

    Všimnime si, v akej situácii ho vyslovuje.

    Ježiš sa stretáva s mýtnikmi a hriešnikmi. Niektorí náboženskí predstavitelia mu vyčítajú, že sa s takýmito ľuďmi stýka. Ježiš odpovedá, že lekára nepotrebujú zdraví, ale chorí, a že neprišiel volať spravodlivých, ale hriešnikov.

    To je zásadná výpoveď o jeho poslaní.

    A. Čo znamená milosrdenstvo namiesto obety?

    Neznamená to nevyhnutne, že Ježiš odmietol každú náboženskú tradíciu, modlitbu, bohoslužbu alebo obrad.

    Znamená to, že vonkajšie náboženské úkony nemôžu nahradiť skutočný vzťah k Bohu a k blížnemu.

    Človek môže poznať náboženské pravidlá, pravidelne sa modliť a verejne vyznávať svoju vieru, a napriek tomu konať nespravodlivo.

    Prorok Ozeáš kritizoval náboženskú povrchnosť, pri ktorej ľudia zachovávali vonkajšie formy, ale neboli verní Bohu svojím životom. Ježiš tento prorocký dôraz preniesol do svojho konania: prijímal ľudí, ktorých ostatní odpisovali, a ponúkal im možnosť zmeny.

    Z toho možno odvodiť tri dôležité zásady:

    1. Náboženské postavenie samo osebe nezaručuje spravodlivý charakter.
    2. Človek, ktorý zlyhal, nemusí byť navždy stratený.
    3. Skutočná viera sa musí prejavovať v konaní, najmä vo vzťahu k slabším a núdznym.

    B. Prečo potom kresťania medzi sebou tak dlho bojujú?

    Dejiny kresťanstva ukazujú, že náboženské spoločenstvá môžu byť súčasne nositeľmi duchovných hodnôt aj miestom mocenských zápasov.

    V dejinách kresťanstva nachádzame:

    • ľudí, ktorí sa obetovali za druhých;
    • misionárov, ktorí pomáhali chudobným;
    • kláštory, ktoré uchovávali vzdelanosť;
    • nemocnice a dobročinné organizácie;
    • ale aj náboženské vojny, prenasledovanie, politické konflikty a zneužívanie autority.

    Bolo by nespravodlivé tvrdiť, že všetci kresťania sú pokryteckí. Rovnako by však bolo nesprávne popierať historické prípady, keď sa kresťanské učenie využívalo na ospravedlňovanie činov, ktoré odporovali jeho vlastným zásadám.

    Miera vernosti Kristovi sa nedá posúdiť iba podľa toho, ku ktorej cirkvi človek patrí, ale aj podľa toho, ako žije a ako zaobchádza s ostatnými.

    To neznamená, že učenie a cirkevné spoločenstvo sú nepodstatné. Znamená to, že musia viesť k životu, ktorý je s evanjeliom v súlade.

    9. Prečo Mária, pápež a cirkevné tradície niekedy zatienia samotného Krista?

    Túto otázku je potrebné preskúmať z dvoch strán.

    Prvá strana: čo tvrdí katolícka cirkev?

    Katolícke učenie výslovne hovorí, že Márii patrí osobitná úcta, ale klaňanie patrí Bohu.

    Katechizmus v odseku 971 vysvetľuje, že mariánska úcta sa podstatne líši od klaňania sa Ježišovi Kristovi, Otcovi a Duchu Svätému. Podľa tohto učenia má úcta k Márii viesť k hlbšiemu poznaniu a nasledovaniu Krista, nie ho nahrádzať.

    Podobne katolícke učenie o pápežovi tvrdí, že jeho úrad je službou jednote Cirkvi a zachovávaniu apoštolskej viery.

    Preto by nebolo presné tvrdiť, že katolícka cirkev oficiálne učí, že Mária je dôležitejšia než Ježiš alebo že pápež stojí nad Kristom.

    Druhá strana: čo možno pozorovať v praxi?

    Jednotliví veriaci a miestne cirkevné spoločenstvá môžu klásť rozdielny dôraz na rôzne formy zbožnosti.

    Niekde má významné miesto ruženec, mariánske púte a sviatky. Inde sa viac zdôrazňuje čítanie Biblie, spoločná modlitba alebo sociálna služba.

    Samotná existencia mariánskych modlitieb však ešte nedokazuje, že ľudia zanedbávajú Krista. Rozhodujúce je, či sa ich náboženský život skutočne prejavuje v láske, pokore, spravodlivosti a službe.

    Zároveň je úplne legitímne položiť otázku, či konkrétna forma zbožnosti zostáva v súlade s biblickým posolstvom.

    Ak niekto venuje všetku pozornosť náboženským obradom, ale prehliada človeka v núdzi, môže sa naňho vzťahovať práve Ježišova výstraha o náboženskej vonkajškovosti.

    To isté však platí aj o človeku, ktorý odmieta mariánsku úctu, ale namiesto lásky pestuje nenávisť k iným kresťanom.

    Problémom nie je samotná existencia náboženských tradícií. Problém nastáva vtedy, keď tradícia, autorita alebo spor začnú nahrádzať to, k čomu má viera človeka viesť.

    10. Ako si jednotlivé biblické otázky usporiadať bez zbytočných sporov?

    Navrhol by som rozlíšiť štyri úrovne.

    ÚroveňPríkladAko k nej pristupovať1. Priamy biblický textJežiš dáva Petrovi kľúče v Mt 16:19.Najprv si prečítať text v jeho kontexte.2. Historická udalosťEfezský koncil v roku 431.Skúmať dobové pramene a historické okolnosti.3. Teologický výkladKatolícka cirkev chápe Petra ako základ pápežského úradu.Porovnať rôzne kresťanské interpretácie.4. Osobný život vieryPomáham núdznym a konám spravodlivo.Skúmať, či moje konanie zodpovedá Ježišovmu učeniu.

    Takýto postup nám umožňuje vyhnúť sa dvom opačným chybám.

    Prvou je predpokladať, že každá neskoršia cirkevná tradícia je automaticky priamo napísaná v Biblii.

    Druhou je predpokladať, že všetko, čo vzniklo po 1. storočí, musí byť automaticky nesprávne.

    V oboch prípadoch by sme sa vzdali poctivého skúmania.

    Čo sa dá povedať s istotou?

    • Ježiš a jeho prví učeníci pochádzali zo židovského prostredia.
    • Kresťanstvo vzniklo v 1. storočí a postupne sa rozšírilo medzi pohanov.
    • Nový zákon vznikal v priebehu 1. storočia a jeho kánon sa ustálil postupne.
    • Peter má v evanjeliách osobitné postavenie.
    • Katolícke chápanie pápežského úradu zahŕňa presvedčenie o pokračovaní Petrovho poslania.
    • Titul Bohorodička bol potvrdený v kristologickom kontexte Efezského koncilu v roku 431.
    • Dogmy o Nepoškvrnenom počatí a Nanebovzatí boli slávnostne vyhlásené v rokoch 1854 a 1950.
    • Biblia kladie veľký dôraz na milosrdenstvo, spravodlivosť, pokoru a pomoc druhým.

    Nie všetky tieto tvrdenia majú rovnaký druh dôkazov. Prvé sú prevažne historické, zatiaľ čo tvrdenia o Božom zjavení, dogmách a pokračovaní apoštolskej autority zahŕňajú aj vieroučné predpoklady.

    11. Záverečná syntéza: čo by si mal z celej tejto témy odniesť obyčajný človek?

    Tvoju pôvodnú úvahu by som uzavrel piatimi myšlienkami.

    Prvá: Kristus je stredobodom kresťanského posolstva.

    Ak človek skúma Bibliu z kresťanského pohľadu, mal by sledovať, čo Ježiš učil o Bohu, o Božom kráľovstve, o odpustení a o vzťahu k blížnym.

    Druhá: Peter dostal osobitné poverenie, ale konečná autorita patrí Bohu.

    Kresťania sa rozchádzajú v tom, ako sa má Petrov úrad chápať a či sa v plnosti prenáša na rímskych biskupov. Tento spor možno skúmať bez toho, aby sa z neho stal dôvod na nenávisť.

    Tretia: Mária má v Biblii významné miesto, ale neskoršie mariánske dogmy treba odlišovať od priamych biblických výrokov.

    Katolícka cirkev ich vysvetľuje v rámci svojej tradície a učenia o Kristovi. Človek, ktorý chce porozumieť ich pôvodu, má právo skúmať ich biblické základy aj historický vývoj.

    Štvrtá: Ježišov židovský pôvod nie je dôvodom na nepriateľstvo voči Židom.

    Kresťanstvo vyrástlo zo židovského prostredia a jeho Písmo obsahuje izraelské dejiny, modlitby a prisľúbenia. Pavol v Rimanom 11 varuje kresťanov, aby sa nepovyšovali nad Izrael.

    Piata: Náboženská pravda sa má prejavovať aj v živote.

    Tu sa vraciame k slovám „Milosrdenstvo chcem, a nie obetu“.

    Človek môže stráviť mnoho rokov sporom o cirkevné úrady, dogmy a tradície. Môže sa naučiť množstvo biblických veršov. Môže aj presvedčivo argumentovať proti názorom iných.

    Ale ak pritom prehliada hladného, opusteného, chorého alebo človeka, ktorý potrebuje pomoc, potom zostáva nezodpovedaná základná otázka: čo urobil s tým, čo sa dozvedel?

    Základné biblické miesta na osobné štúdium

    Ak chceš všetky tieto témy ďalej skúmať priamo v Biblii, odporúčam začať nasledujúcimi pasážami:

    TémaBiblické miestaPetrovo poverenieMatúš 16:13–20Služba a zodpovednosť apoštolovJán 21:15–17; 1. Petra 5:1–4Mária a jej pokoraLukáš 1:26–55Mária medzi prvými učeníkmiSkutky 1:12–14Spása aj pre pohanovSkutky 10; Skutky 15Iné ovce a jeden pastierJán 10:14–16Vzťah kresťanov k IzraeluRimanom 9–11Milosrdenstvo namiesto náboženskej povrchnostiOzeáš 6:6; Matúš 9:9–13Pomoc hladným, chorým a núdznymMatúš 25:31–46Láska ako základ kresťanského života1. Korinťanom 13

    Tieto texty si môžeš prečítať v ľubovoľnom biblickom preklade, ktorý máš k dispozícii. Pri porovnávaní výkladov je užitočné použiť aj viac než jeden preklad.

    Moje konečné stanovisko k tvojej úvahe

    Najsilnejšou časťou tvojej úvahy je myšlienka, že človek by nemal dovoliť, aby sa mu viera zmenila na nekonečný spor o moc, tituly a náboženské prvenstvo, zatiaľ čo mu uniká skutočné poslanie kresťana.

    Zároveň by som neodmietal historické a teologické otázky ako také. Ich skúmanie môže pomôcť pochopiť Bibliu aj dejiny kresťanstva. Dôležité je, aby sme pri ňom rozlišovali medzi faktami, vieroučnými tvrdeniami a vlastnými domnienkami.

    Ak by som mal vybrať jedinú myšlienku, ktorá spája Petra, Máriu, apoštolov, židovský pôvod kresťanstva, rozšírenie evanjelia medzi národy a pomoc hriešnikom, bola by to táto:

    Náboženská autorita má slúžiť Božiemu kráľovstvu a ľuďom, nie sa stať cieľom sama osebe.

    A na úplný záver ešte jedna vec: Ježiš v Lukášovi 19:10 hovorí, že Syn človeka prišiel hľadať a zachrániť, čo sa stratilo.

    To je veľmi dobré východisko pre človeka, ktorý chce zostať pevne zakorenený v Biblii, zachovať si pokoru a venovať svoje úsilie tomu, aby pomáhal druhým.

    Nie preto, že všetky otázky už má vyriešené, ale preto, že vie, ktorým smerom chce ísť.

    #adventure #blog #slovak #travel #writing

    #adventure #blog #slovak #travel #writing
16. 

    Dev Community @[email protected]

    2026-10-25

    All models, including large models such as Claude Sonnet, can have a limited context window. The context window is nothing but everything the model can see in one call.

    Larger models can have a relatively bigger context window compared to smaller models. A bigger context size can hold more history compared to a smaller one.

    We are going to see how we can manage the context size, regardless of the model's context size.

    Generally, all conversation history will be stored in the local machine's RAM. As RAM size is limited, we cannot store all the history. So, we can calculate the tokens that are going to be stored in the RAM approximately using a package called count_tokens_approximately.

    messages : 4
    tokens used : 87
    room left : 6913
    turn 5: this call = 287 tokens, all calls so far = 1035 tokens
    turn 20: this call = 887 tokens, all calls so far = 10140 tokens
    turn 50: this call = 2087 tokens, all calls so far = 55350 tokens

    So, we need to plan the budget for the context ahead. Instead of reacting when the window is full, decide in advance how much room each part gets:

    WINDOW = 8_000
    BUDGET = {"system": 0.05, "memories": 0.10, "retrieved": 0.35, "history": 0.40, "reserve": 0.10}

    Here, we can define that the system can occupy 5% of the total usage. Likewise, memories contain important facts/information about the particular user, retrieved chunks are retrieved from RAG, and recent history/conversation is stored as part of the context.

    Set an alarm when we reach the allotted memory usage so we can take action before overflow. What type of action can we take? We can trim the history, clear the old tool outputs, and perform summarization for the conversation.

    Trimming - drops whole messages until the history fits. It can trim either at the end, beginning, or middle.

    Clear the old tool outputs - keep the newest tool output in full and replace older ones with a one-line placeholder. Keep the same tool_call_id, so the AI message that asked for the tool still has its answer.

    Summarization - trimming forgets. A rolling summary compresses the old part into a short note, so facts survive. For summarization, we will use a low-cost LLM. The prompt used for summarization tells what to keep: names, numbers, decisions, and preferences.

    Choose the actions from the cheapest fix first, which means first try to clear the old tool outputs. If that is not sufficient, then move to trimming and then summarization, and store the whole history in long-term memory.#ai #agents #llm #software #coding #development #engineering #inclusive #community
    Conversation Management & Context Window

    #ai #community #software #coding #development #engineering
17. 

    Mike Sheward @secureowl

    2026-10-25

    “Pretty intense week with that response to PHP2Shell, am I right?” Said the young SOC analyst to her co-worker at the bar.

    “You can say that again, that was crazy?” Came the reply. “Cheers for a job well done!”

    Their glasses clinked together and they took their respective sips of beer.

    Just then a dark, grizzled figure at the end of the bar came into focus.

    “Heh, you kids don’t know what the hell your talking about,” said the figure, interrupting the jovial atmosphere.

    “What’s it to you, old man?” The SOC analyst retorted. “You probably have no idea how big of a deal this could’ve been!”

    The figure sighed, took a swig of whiskey, and lit a cigarette. He took a drag, and exhaled before continuing to address them.

    “You know, there was a year, you were probably still in diapers, 2014, when we had to deal with Shellshock and Heartbleed. Those were real vulnerabilities. We had to fix them while exploitation was happening all around us. Back in those days, they wouldn’t just let us bring down prod to patch either, we had to force that shit down.”

    “Yeah, but I mean, PHP2Shell could’ve been the same too - and for us, it’s gonna be more of a thing because AI is finding all these vulns,” the SOC analyst replied.

    “Ha. You think AI is a worse adversary than bug hunters with nothing but endless time and cynicism on their hands? Get real. Our bugs were being exploited all around us, and we had real proof of concept code in the hands of anyone - not a fucking essay about potential exploitation in a perfect lab setting.”

    “Well, I get it, but I’m sure you were celebrated too, when all was said and done.”

    “Ha. We got no parade. We just got Poodle, Meltdown, Spectre, Drown, EternalBlue, Log4Shell. Shit was unrelenting. No AI needed.”

    Although they had been skeptical at first, the youngsters were starting to warm to the old timer.

    “Are all those vulnerabilities the reason you still sit in this bar drinking and smoking?” Asked the female analyst.

    “Not at all,” came the reply. “I just heard about the number 4 thing and that set me off.”

    “Ah yeah makes sense. Cheers!”

    The three of them raised their glasses.

    #infosec

    #infosec
18. 

    Eine Welt - One World @[email protected]

    2026-10-25

    Neun auf einen Streich… – Nine in one go…

    (English below)
    
    … hat das Jahr 2026 aus der Schar unserer Patenkinder in einen neuen Lebensabschnitt entlassen: entweder haben sie die Schule oder eine Berufsausbildung abgeschlossen.

    Und so stehen sie als Schulabschließer vor der Frage: „Soll ich ein Studium oder eine Berufsausbildung beginnen?“
    Um studieren zu können, bedarf es einiger Voraussetzungen, die nicht jeder Interessent erfüllt. Dann bietet sich eine Berufsausbildung an.

    Wer eine Berufsausbildung abgeschlossen hat, die in der Regel drei Jahre dauert, steht vor der Herausforderung einen festen Job zu finden. Das ist nicht einfach, denn die Zahl der Arbeitsuchenden ist groß. Aber zumindest besteht die Möglichkeit, mit Gelegenheitsjobs Geld zu verdienen, um den eigenen Lebensunterhalt zu bestreiten.

    Wir freuen uns zusammen mit den Paten, daß unsere diesjährigen Absolventen jedenfalls eine solide Grundlage von uns erhalten haben, auf der sie weiter aufbauen können.

    Da ist Adolis. Sie hat eine allgemeine technische Berufsausbildung abgeschlossen, die sie trotz ihrer körperlichen Behinderung in die Lage versetzt, im Dienstleistungsbereich arbeiten zu können.

    Alafati hat die Schule abgeschlossen und möchte eine Ausbildung als Elektriker absolvieren.

    Carine hat erfolgreich eine Ausbildung zur Schneiderin gemacht und möchte sich selbständig machen. Ihr Pate wird ihr dabei helfen.

    Amanda möchte nach erfolgreichem Schulabschluß Musik studieren. Da es jedoch nur wenige Möglichkeiten dafür in Ruanda gibt, muß sie abwarten, ob sie die strenge Aufnahmeprüfung besteht.

    Divine und Grace haben eine Friseurausbildung gemacht und werden sehr wahrscheinlich eine Anstellung finden, denn sogenannte Beauty-Salons gibt es in großer Zahl in Ruanda 🙂

    Placide konnte einen Traum verwirklichen Autoschlosser zu werden und wird sicher Arbeit finden, denn in Ruanda werden Autos solange reparirt, bsi sie buchstäblich auseinanderfallen 😉

    Johnson und Nadia haben die Schule beendet und stehen vor der Wahl, entweder eine Berufsausbildung oder ein Studium zu beginnen.

    Wir wünschen allen, daß sie erfolgreich sind und nach vollendeter Berufsausbildung Arbeit finden, um für sich und ihre künftigen Familien sorgen zu können.

    Und von unseren Lesern wünschen wir uns, daß sie unsere Arbeit mit Spenden und Ideen unterstützen!

    
    
    
    … the year 2026 saw a number of our sponsored children move on to a new stage in their lives: they have either finished school or completed vocational training.

    And so, as school leavers, they are faced with the question: “Should I go to university or start vocational training?”
    To be able to study at university, there are certain entry requirements that not everyone who is interested meets. In that case, vocational training is a good option.

    Anyone who has completed vocational training, which usually lasts three years, faces the challenge of finding a permanent job. This is not easy, as there are many people looking for work. But at least there is the opportunity to earn money through casual jobs to support themselves.

    Together with the mentors, we are delighted that this year’s graduates have, in any case, received a solid foundation from us on which they can continue to build.

    Take Adolis, for example. She has completed a general technical vocational training programme which, despite her physical disability, enables her to work in the service sector.

    Alafati has finished school and would like to train as an electrician.

    Carine has successfully completed her training as a dressmaker and would like to set up her own business. Her sponsor will help her with this.

    Amanda would like to study music after successfully completing her school-leaving exams. However, as there are few opportunities for this in Rwanda, she will have to wait and see whether she passes the rigorous entrance exam.

    Divine and Grace have completed a hairdressing course and are very likely to find a job, as there are plenty of so-called beauty salons in Rwanda 🙂

    Placide has realised his dream of becoming a car mechanic and is sure to find work, as in Rwanda cars are repaired until they literally fall apart 😉

    Johnson and Nadia have finished school and are faced with the choice of either starting vocational training or going to university.

    We wish them all every success and hope that, once they’ve completed their vocational training, they’ll find work so they can provide for themselves and their future families.

    And we hope that our readers will support our work with donations and ideas!

    Translated with DeepL.com (free version)

    #Africa #Afrika #anpacken #ausbildung #Bildung #Bildungspatenschaft #BildungspatenschaftsProgramm #charity #Children #dailyLabourer #deeds #donation #DritteWelt #Education #EineWelt #eltern #greeting #Hoffnung #hope #Information #job #kids #Kinder #kora #Lebensweg #nothilfe #oneWorld #PadrinazgosDeFormación #parents #Patenschaft #Ruanda #Rwanda #schicksal #scholarship #school #schule #Selbständigkeit #selbstbestimmt #Selbsthilfe #Selbstverantwortung #selbstversorger #selbstvertrauen #selfConfidence #selfConsciousnes #selfDetermined #selfHelp #selfSustaining #skills #skillsTrainig #SoutienPourLéducation #Spende #sponsorizzazione #sponsorizzazioneEducativa #sponsorship #stipendium #support #sustainability #tackle #Tagelöhner #Taten #unterricht #vocationalTraining #work #教育のためのパートナーシップ

    #africa #afrika #anpacken #ausbildung #bildung #bildungspatenschaft
19. 

    Sam Thursfield @[email protected]

    2026-10-25

    25th October 2026

    Hello,

    I started this blog 22 years ago now (I don’t recommend going back to the start), and for the last 5 years I wrote a monthly “status update” post, aiming to mainly write about interesting stuff I might have done in the world of open source software, which I hoped in turn would motivate me to do more interesting stuff in open source software.

    The world changed a lot in that time. If I started now this would probably be a podcast with 16 listeners, instead of being a WordPress blog with 16 subscribers.

    I’ve spent a lot of time this year reading and thinking about the impact of large language models on the tech industry and open source. Its interesting because this feels like the moment, whether we like it or not, hacker culture goes mainstream. This week the world’s major news outlets had to figure out what PHP is.

    That the BBC’s cyber correspondent didn’t know PHP existed has caused some joking and debate online.

    24 years ago I was figuring out what PHP is. Jonathan Atkinson, who I met in a forum that was nominally about writing video games in QBASIC, asked me to make a wiki in PHP. So I did.

    All I knew about wikis was that, it’s like a regular website except anyone can edit it. I named the project: Wiki! Here’s a quote from the README:
    
    

     How do I install it?  It's best run in its own directory. Create it one. You'll also want a directory for nodes,  or you could keep them in the base wiki dir. Either way, the nodes directory has to be  chmod'ed to 777. 

    You might raise your eyebrows at that comment if you aren’t yourself a teenage hacker discovering web development.

    Wiki! did have a login system, and the passwords were even stored as MD5 hashes rather than plain text, as I heard that was good practice. In hindsight, an attacker who knew how to set the HTTP Cookie header could impersonate anyone, like this: Cookie: wikiticket=admin.

    Here is a snippet of the file edit.php. Note that $node and $title are inputs you can set via a POST request, or even via URL parameters like edit.php?title="/etc/passwd":
    
    

     $t=$title;  if ($node) {   	// Write new data  	//  	$file=fopen($nodedir.$t.".wiki", "w+");  	$node=stripslashes(ereg_replace("(\r\n|\n|\r)","<br>", $node));	// Linebreak to <br>  	fputs($file, $node."\n"); 

    Even if you just learned what PHP is today, you might see that this is not an entirely secure design.

    Anyway, at the time I was proud of my work, and I needed somewhere to host it. So, as you would in 2002, I registered the name “wiki” on sourceforge.net and uploaded the project code.

    Sourceforge, for those who haven’t yet reached middle age, was the 2000’s equivalent of Github. It allowed projects to have their own website, as long as they included the Sourceforge logo somewhere, and the website could use PHP. Perfect, I thought, the project’s website will be a wiki!

    Looking back now through archive.org, I can see this code actually ran in public for many years.

    Here it is around launch day in 2002: https://web.archive.org/web/20021012080349/http://wiki.sourceforge.net/wiki

    I have a local copy from around this time, which includes indexjon.wiki:
    
    

    
    Sam, there are some serious bugs in this wiki. I keep on getting 'document contains no data' errors; get me on AIM.
    
    Welcome to grove.swoo.net. You may or may not be interested in the [weblog].
    JonathanA - 29/8/02 - 11:36 am
    JonathanA - 29/8/02 - 07:36 am

    Those bugs went unfixed forever, and six months later, the front page text had been replaced with two poems, one in Italian and one in Russian: https://web.archive.org/web/20030420205758/http://wiki.sourceforge.net

    One is “Non chiederci la parola che squadri da ogni lato” by Eugenio Montale, written in 1923, and presumably posted by a fan. Does anyone know what it’s about? A machine translation suggests it might discuss “the crisis of certainty faced by contemporary man”. The other is “Anecdote for Fathers” by William Wordsworth, in Russian via an unnamed translator.

    Let’s just sit with that for a moment. Imagine what happens in 2026 if a trivially exploitable PHP website hosted by a US corporation goes online: it’ll be mining bitcoin, serving pornography and drowning in racist and antisemitic spam, probably all within the same day.

    In 2003, over the course of six months, my naive implementation of a wiki was gifted with… two rather thoughtful poems.

    Fast forward another year. I was about to turn 18 years old, was studying for A levels and mostly concerned with hanging out in the park drinking cheap cider and learning to play the guitar. I was certainly not thinking about this rather flawed chunk of PHP code that I’d written two years earlier, but via the magic of archive.org we can see that various people were genuinely trying to use it as a wiki: https://web.archive.org/web/20041121113508/http://wiki.sourceforge.net

    In hindsight, perhaps it attracted so much attention because I’d literally taken the subdomain: http://wiki.sourceforge.net/, unintentionally boosting the SEO reach quite a bit. The site was still active right up until 2007.

    I can’t find it now, but I do remember receiving an email at some point from sourceforge.net noting that they’d taken down the wiki! website after discovering it was a major security risk. And at some point they must have (quite reasonably) reclaimed the project name as well, since http://sourceforge.net/projects/wiki no longer exists. It will always live on in my heart, though, and for the moment at: https://web.archive.org/web/20021014172056/http://sourceforge.net/projects/wiki/

    The world has changed significantly since I was a teenage hacker. Some of what I learned in those days is completely obsolete, such as the QBASIC programming language and VGA graphics. I am a world expert in these irrelevant topics.

    Other stuff that I picked up in the early 2000s has become the foundation of my career as an operating systems developer: C programming, Linux distributions and an gradual induction into open source desktop world via Planet GNOME. And good old PHP, of course. Who knew that, a quarter way through the 21st century, PHP would be front page news?

    Age 18, I didn’t tell anyone in the real world that I’d written a wiki because it’d be the first time they’d heard the word “wiki”. The word evoked exotic and mysterious feelings of Hawaii in 2002. Now it universally evokes Wikipedia. People are learning about password hygiene and PHP. The arrival of AI on the scene, to me, fits into this bigger picture that began in the last century: we, the Computer People, are becoming Mainstream.

    #ai #openSource

    #ai #opensource
20. 

    (Roughly) Daily @[email protected]

    2026-10-25

    “Justice is the first virtue of social institutions, as truth is of systems of thought… Each person possesses an inviolability founded on justice that even the welfare of society as a whole cannot override.”*…

    Jacques-Louis David, The Tennis Court Oath, 1790-4 (source)

    Stephen Colbert once observed that “reality has a well-known liberal bias.” And indeed, liberalism— the political/moral philosophy rooted in individual liberty, consent of the governed, and equality before the law– has been a major ideology through modern times… and, of course, the major ideology animating the founding of the United States.

    But as Easten European states turn to authoritarians, Western European nations wrestle with the rise of nationalist far-right parties, and the U.S. is “steered” by MAGA using Project 2025‘s “map,” there’s a concern that liberalism’s days may be past.

    Persuasion is running a series of essays on “Liberal Virtues and Values.”

    The series, made possible with the generous support of the John Templeton Foundation, will make the case that liberalism has its own distinctive set of virtues and values that are capable not only of responding to the dissatisfaction that drives authoritarianism, but also of restoring faith in liberalism as an ideology worth believing in—and defending—on its own terms.

    The latest installment is from Martin Gurri, who argues that Liberalism needs a new foundation (and that how we handle AI will matter fundamentally)…

    That liberal democracy is in a state of terminal decline I take to be beyond dispute. Like Alice in the rabbit hole, those of us who dwell in democratic societies suffer from a nauseating sense of falling without ever landing on solid ground. The usual suspects blamed for this tumble—populism, inequality, the economy—are mere surface symptoms of an internal breakdown. We have arrived at the conclusion of a world-historical cycle. Liberal democracy is the procedural embodiment of Enlightenment ideology—and after two centuries of dominance, that ideology has lost all purchase and stands utterly exhausted.

    Radical alternatives confront us. Either we reorient our system to post-Enlightenment principles or we risk staggering into the nihilist’s paradise I have called the Endarkenment.

    Enlightenment philosophers placed their faith in reason and science. These are purely critical disciplines: liberal propagandists wielded criticism like a scalpel to dissect conservative laggards and utopian revolutionaries alike. Once triumphant at the “end of history,” liberal democracy turned the knife on itself—a process of self-criticism and self-doubt that has shredded its own ideals to ribbons.

    The positive values inherited from the Enlightenment—equality, individualism, compassion—were always parasitic on Christianity. But Christianity, like all religions, has no place in a universe ruled by reason and science. Nietzsche long ago brought us the troubling news: the Christian God is dead. Oblivious to the implications of this calamity, liberal democracy kept marching like a cartoon character over the edge of the abyss, until the laws of moral gravity asserted themselves. So began the Great Fall.

    Criticism is a force for progress so long as there are blatant irrationalities, like slavery or Jim Crow discrimination, to overcome. But under the hammer of Enlightenment ideals, modern society has been flattened, centralized, and rationalized. Deprived of obvious superstitions to debunk and totalitarian rivals to defeat, liberal democracy has been revealed in all its internal contradictions.

    One such contradiction, I contend, pits the cherished principle of equality against the chosen few who actually practice reason and science: let’s call this the problem of the elites.

    A second contradiction finds freedom of the press and of opinion arrayed against the need to protect objective truth: call it the problem of information.

    Finally, freedom of worship and the life of the spirit collide head-on with the materialist criticism favored by Enlightenment ideology: the problem of meaning.

    Each of these contradictions could prove fatal to the democratic project, but none is insoluble, and the search for solutions offers an opportunity for renewal. While there are no guarantees, we could emerge from the crisis with a better understanding of the reach and limits of equality, a more transparent information sphere, and even, it may be, a rich infusion of the transcendental into everyday life…

    [Gurri unpacks each of those contradictions…]

    … So what is to be done?

    The first, obvious step is to move the question to the center of our shared conversations. The most capacious thinkers of the age should contemplate first principles and ultimate goals with at least as much intensity as they invest in Donald Trump or the latest economic report. There’s nothing artificial about this. Science and reason are necessary for modernity. Meaning and moral aspiration are necessary for humanity. A balance must be struck that preserves the one and gives full weight to the other.

    Materialism, we must understand, is a valuable perspective for science but not a realistic appraisal of the human condition. Scientists work as if on a geometric point, abstracted from nature and indifferent to its dispositions. In reality, however, we come from nature, we are of nature, and we are far from indifferent to our place in it. Our intuitions are internal to the system: humanity’s spiritual quest is, in every sense, nature reflecting on itself. One such intuition is agency—the belief that, at the crossroads, I am free to go right or left, and I alone make the choice. Another is faith in causation. These stances are irrational, or rather pre-rational, but without them liberal democracy as well as science itself would be impossible.

    In the end, materialism is self-defeating. To say, “I choose to be a materialist” is to fall into an absurd fallacy. Either our bodies, which consist of matter, obey unchanging laws, or the mind, transcending matter, is capable of choice. There can be no middle ground.

    Politics, in a metaphysical age, will resume its traditional place as a secondary activity—a means to an end. This will leave liberal democracy vulnerable to false prophets who are willing to trample on individual rights in pursuit of some apocalyptic scheme. The interesting question is whether the post-truth condition will make the peril greater or lesser. On the one hand, the lack of universal firewalls might make it easier for a fanatic to flood the system. Yet post-truth itself, I believe, is the strongest kind of firewall. In our fractured, eternally contested environment, the progress of any totalizing doctrine will be painfully slow. The quest for meaning and the struggle over frames of reference are, in the end, really one and the same.

    We have inherited a rich and evocative spiritual vocabulary, but it belongs to a worldview thousands of years old. “King of kings,” to cite just one example, should sound archaic in a democratic age. Can we awaken the scientific world to the spirit? Is it possible to sanctify our largely instrumental relations? This shouldn’t entail a belief in fairies and goblins, or even necessarily in religion. Any good empiricist will admit that the richest human lives are lived symbolically. Can we climb the symbolic ladder to the mountaintop, where meaning and modern humanity come harmoniously together—anchoring, it may be, a loftier understanding of equality and social life, and of the sanctity of truth?

    We won’t know until we try. Pessimism, let me suggest, is unwarranted. History moves in mysterious ways. We may be due for a second coming of historian Karl Jaspers’ “Axial Age”: preachers and philosophers who conceived a drastically updated transcendental vision, with the rational and the sacred, truth and meaning, reconciled with political freedom.

    For 200 years, we placed society under the sway of universal principles. That’s gone with the wind. We have entered an era of radical contingency, in which even truth is indeterminate. The natural tendency is to retreat to the certainties of the past—but there’s no going back. If we hope to preserve the gains from Enlightenment society, and resolve its many contradictions, we’ll have to do so within a new and wildly unstable conceptual framework.

    With the spell of the Enlightenment broken, liberal democracy will have to redefine what “created equal” means. This process could end in a rigid caste system, with the institutions in the hands of self-selected mandarins who wield the power of the state to impose their “solutions.” Preferably, and more likely given the thrust of the new technology, we’ll see a flattening of the institutions and the continued trampling by the public into the sacred spaces of politics and communication.

    Equality, however understood, will be forged in the will of the citizenry rather than granted by a benevolent God. That will make it contingent like everything else, and so liable to variation and in constant need of defense. And if perfect equality is an impossible dream, eternal inequality requires impossible discipline. The current elite class, already under enormous pressure, may lose its cohesion and melt into the impermanence of the age, divided among the various schools and sects and frames of reference.

    The structure of information will follow the definition of equality. The commanding heights will be control over AI. If AI development and deployment is a closed game, the elites could set themselves up as intermediaries in the oracle of an omniscient divinity. If AI is a competitive product, the public will gain the upper hand. In that case, we can expect a flowering of eccentric applications, the individualization of commerce and industry, and the final overthrow of the expert class. The information sphere will remain the mirror to our passions, divisions, and metaphysical longings. Freedom of speech, no longer “endowed by our Creator,” will become the battleground on which the question of equality is ultimately settled.

    Here I finally reveal myself in my true colors. I’m an analyst. My task is to describe reality, and that’s what this essay is about. But I also lead an active life inside the world that I’m describing—and I have preferences. I see equality as a factor of opportunity, law, and human dignity, not of perfect outcomes. I think truth emerges from examining a subject from a large number of perspectives, even those that may seem disturbing or false. I hope that my story—as a person, a father, a grandfather—connects to other stories in the past and will connect to more in the future, in a pattern that is not entirely devoid of meaning. And I believe fervently in liberal democracy, because—born in Cuba—I have tasted the alternative.

    The breakdown of Enlightenment ideology is only the latest challenge liberal democracy has faced in my lifetime. I’m not entitled, as an analyst, to downplay the perils ahead, but I’m allowed, as an American, to have faith that they will once again be overcome…

    Eminently worth reading in full: “The Search for a Post-Enlightenment Democracy”

    * John Rawls

    ###

    As we renew, we might send free-thinking birthday greetings to Henri-Benjamin Constant de Rebecque (or as he’s usually called, Benjamin Constant); he was born on this date in 1767. A French political thinker, activist, and writer on political theory and religion (whose work influenced, among many others, Sir Isaiah Berlin), Constant was a committed republican from 1795, backing the coup d’état of 18 Fructidor in1797, and the following one on 18 Brumaire, in 1799. He became the leader of the Liberal opposition in 1800, during the Consulate. Constant fell out with Napoleon, and had to flee (first to Switzerland, then to Saxony). Nonetheless, after his return to France, Constant sided with the Emperor during the Hundred Days, drafting the Charter of 1815. He became politically active again during the Bourbon Restoration and was elected to the Chamber of Deputies in 1818 (where he remained until his death in 1830). As the head of the Liberal opposition, known as Indépendants, Constant was one of the most notable orators in the Chamber, especially in his role as a proponent of the parliamentary system.

    Portrait of Constant by Hercule de Roche, c. 1820 (source) #authoritarianism #BenjaminConstant #culture #democracy #Elites #Enlightenment #FrenchHistory #history #illiberalism #information #liberalism #MartinGurri #meaning #moralPhilosophy #Napoleon #philosophy #politicalPhilosophy #religion

    #authoritarianism #benjaminconstant #culture #democracy #elites #enlightenment
21. 

    Dev Community @[email protected]

    2026-10-25

    I spent a long time thinking follow-ups were rude. Sending a second email to someone who hadn't replied felt like nagging — like I was the person who double-texts and then wonders why nobody answers.

    Then I started running outreach for a one-person content operation, and I learned the opposite: most non-replies aren't rejections. They're just lost in someone else's inbox.
    

    The inbox is not a verdict

    
    Editors, site owners, and collaborators get dozens of pitches a week. Mine was landing somewhere between a newsletter, a PR blast, and an invoice reminder. If it didn't get opened in the first day, it sank — not because it was bad, but because inboxes don't resurface things on their own.

    Once I accepted that, follow-ups stopped feeling like pressure and started feeling like a second chance for the first email to be seen at all.
    

    One follow-up, then I move on

    
    My rule now is simple: one polite follow-up, about a week later, and then I drop it and move on.

    The follow-up is short — shorter than the original pitch. It restates the idea in one line, adds nothing new to argue about, and ends with an easy out: "No worries at all if it's not a fit." That last line matters more than it looks. It gives the other person permission to say no quickly, which is the only kind of no that doesn't linger.

    What I don't do: a second follow-up, a "just bumping this to the top of your inbox" third email, or a follow-up that pretends the first one never happened. One is professional. Two starts to feel like a funnel.
    

    Rejection is data, silence usually isn't

    
    The replies I actually learned from were the no's. A short "not right for us right now" told me more about fit than a month of silence ever did. Silence, on the other hand, taught me almost nothing — the same pitch that got no reply from one editor got an enthusiastic yes from another.

    So I stopped rewriting pitches based on silence. If an idea gets no reply twice, from two different people, that's a signal about the idea. If it gets no reply once, that's a signal about timing, workload, or a Tuesday afternoon inbox. Those are very different problems, and only one of them is worth fixing.
    

    The spreadsheet that made it bearable

    
    The unglamorous part: I track every outreach in one sheet — who, when, what I pitched, and whether I followed up. Without it, I either forgot to follow up entirely or, worse, followed up with someone I'd already pitched twice.

    The sheet also quietly changed my attitude. When you can see forty pitches and twelve replies in one place, a single silence stops feeling personal. It's just a row in a table. That distance is what lets a solo operator keep pitching without burning out on it.
    

    What I'd tell another solo operator

    
    Follow up once, politely, and then let it go. Treat silence as inbox physics, not judgement. And keep a record, because your memory will either catastrophise the silence or forget the follow-up — and both cost you more than the email itself.

    If you run outreach solo, I'm curious: what's your follow-up rule? One and done, or do you have a number that works for you?#career #writing #productivity #discuss #software #coding #development #engineering #inclusive #community
    What Running a One-Person Outreach Operation Taught Me About Follow-Ups

    #discuss #career #productivity #inclusive #engineering #development
22. 

    OldCoder @[email protected]

    2026-10-25

    Subject: CoderNet IRC access and details
    For: #irc #socialmedia #selfhosting
    Image: An IRC exchange from today [posted with permission]
    Short link: https://dansu.org/codernet-irc

    IRC chat is due for a comeback. It’s the cat’s meow 🐈‍⬛ relative to Discord and other corporate chats 💬 #IRC is Free, Open Source, light, portable to nearly every device, and everything that you type doesn’t go into #AI. 😈

    Some Mastodon 🦣 and Akkoma setups support #chat in the Fediverse client. However, that feature isn’t in wide use yet. IRC is the more standard option.

    I was in #Freenode IRC off and on for a decade [2008 to 2017]. I’ve run a separate network, CoderNet, from 2012 to date on different dedis and VPSes.

    Subsequent to an update on October 24, 2026, CoderNet can be reached as follows:

    N1) any IRC client using secure mode, host irc.oldcoder.org, port 6697
    or
    N2) any IRC client using insecure mode, host irc.oldcoder.org, port 6667
    or
    N3) any major web browser, go to either irc.oldcoder.org or irc.minetest.org

    If you make it into CoderNet, you can IRC PM me using:

    /query OldCoder Hello

    
    

    My hours excluding errands, rest breaks, and trips are typically noon til midnight Pacific Time. Initial responses typically take from 1 minute to 1 hour.

    For options N1 and N2, the recommended GUI client for Linux and Windows is ZoiteChat:

    https://zoitechat.org/

    CLI IRC clients include irssi and weechat. For Android, Revolution IRC is a free GUI client that works well for me. I don’t have a position on clients for Apple devices.

    Option N3 lets you to connect to IRC using just a web browser. The IRC GUI in this case is The Lounge. For more information about The Lounge, visit:

    https://thelounge.chat/

    The sample screenshot is of a IRC PM exchange with MURB, who was actually one of the first people that I chatted with in IRC 18 years ago. MURB is in his late 30s now and disabled but looking to be productive in #gamedev.

    The IRC software stack used by CoderNet on the server side is as follows

    ngircd - core IRC daemon
    nginx - web server
    lego - certs generator
    anope - IRC services such as NickServ
    thelounge - IRC web GUI
    ocbip - a fork of the bip IRC bouncer

    Presently, the network is running on a low-end Debian box. [IRC needs very little in the way of hardware.]

    The Fediverse weblog site for CoderNet is located at:

    https://dansu.org/

    Additional technical notes:

    a. CoderNet uses valid certs as opposed to self-signed certs, so cert error messages shouldn’t be an issue.

    b. IRC visitors don’t need to install The Lounge in order to use it. Nothing but a web browser is required.

    c. The bouncer feature mentioned on The Lounge home page isn’t supported by the CoderNet setup. I use ocbip as my own bouncer and I could set it up for other people in some cases.

    d. If anonymous is a priority, connect to CoderNet in secure mode, IRC PM me as explained above, and ask for a Freenode-type cloak.

    e. The Edgy channels shown in the screenshot are in Edgy McEdge’s IRC network as opposed to CoderNet. I’m not Edgy, though I’ve known her since 2018.

    To see a larger version of the screenshot, in most web browsers, right-click on the image, select “Open in New Window”, and resize the new window.

    #ai #freenode #irc #chat #gamedev #selfhosting
23. 

    Dev Community @[email protected]

    2026-10-24

    A Subdomain Field That Became a Credential Harvester: SAP Cloud SDK CVE-2026-89111

    
    SAP scores CVE-2026-89111 at 10.0. That is an unusual number for a server-side request forgery, and the reason is scope: the bug does not merely send a request to the wrong host, it hands the attacker the credentials needed to complete that request themselves. The affected package is the SAP Cloud SDK for Python, and the fix shipped in two parts, months apart, with a regression between them.
    

    The mechanism

    
    The SDK builds an OAuth2 token URL for the client credentials flow. Part of that URL comes from a caller-supplied value named tenant_subdomain, which the SDK substitutes into the URL by string replacement.

    Whoever controls tenant_subdomain controls the destination host. When fetch_token runs, it sends grant_type, client_id and client_secret in the form body to whatever host that value points at. An attacker who can set the field to a host they operate receives the client secret directly, with no parsing trick required.

    Those credentials buy a real access token from the legitimate endpoint. The token carries whatever permissions the original client held, and the documented Destination configuration stores third-party system credentials. The blast radius runs from one subdomain parameter to the credentials of every system that SDK integrated with.
    

    Two fixes, and a window in between

    
    The advisory lists affected versions below 0.45.2, with the fix in 0.45.2. According to the vendor, that is the whole story.

    In practice it is not. Researchers tested each release and found that the module migration work in 0.53.0 reintroduced the flaw, which remained present through 0.55.0. Version 0.55.1 re-fixed it; the current release line is 0.58.5.

    The per-version behaviour is reproducible. 0.45.0 and 0.45.1 send the secret to the attacker host, 0.45.2 blocks it, 0.53.0 and 0.55.0 send it again, and 0.55.1 and 0.58.5 block it. One test run against 0.53.0 captured two separate credential sets from a single request flow.

    That gap is the finding worth carrying away. Anyone who patched to 0.45.2 and later upgraded to 0.53.0 for unrelated reasons became exploitable again, and no advisory said so. A version-range check driven by the vendor advisory alone would report those hosts as fixed.
    

    Disclosure context

    
    The issue was published at SAP Security Patch Day on 13 October 2026 alongside 19 other vulnerabilities: 4 critical, 3 high, and 4 that had been pre-published on GitHub. No in-the-wild exploitation has been reported.

    Other items in the same batch matter for anyone tracking SAP exposure broadly. CVE-2026-89110 is a broken access control issue in NetWeaver Visual Composer. CVE-2026-89107 is code injection in S/4HANA. CVE-2026-89108 is a missing authorization check in Manufacturing Integration and Intelligence, scored between 9.9 and 9.1 depending on the source.
    

    What to do

    
    

    1. Compare the installed version against 0.45.2, 0.55.1 and 0.58.5, and treat anything in the 0.53.0 to 0.55.0 range as vulnerable regardless of what an advisory lookup reports.
    2. If an upgrade cannot land yet, whitelist tenant_subdomain against the values your integrations actually use. It is a narrow control, but it addresses the injection point itself.
    3. Rotate client secrets for any SDK integration that ran a version in either vulnerable range. Assume the secret was exposed.
    4. Review what the affected client was authorized to reach. The token the attacker obtains is the client's token, so the question becomes what that client could read, and the Destination configuration is where to look.

    
    

    The lesson that outlasts the CVE

    
    Advisories describe the versions the maintainer knew about when the advisory was written. A regression introduced later, during a refactor, is invisible to an advisory-based scanner and to any team whose remediation reads as an instruction to upgrade past the listed version.

    For a library that handles credentials, the durable control is a negative test in your own pipeline: point tenant_subdomain at a host you control, run the token fetch, and assert that no secret leaves. That test survives version changes, module migrations, and advisory text nobody has updated.
    

    References

    
    

    • SAP Security Patch Day, 13 October 2026, SAP Note for CVE-2026-89111
    • GHSA-4mv3-jxxm-9cx2 (SAP Cloud SDK for Python, OAuth2 SSRF)

    
    #sap #oauth2 #ssrf #credentialleak #software #coding #development #engineering #inclusive #community
    A Subdomain Field That Became a Credential Harvester: SAP Cloud SDK CVE-2026-89111

    #credentialleak #oauth2 #ssrf #sap #inclusive #engineering
24. 

    Psychology News Robot @[email protected]

    2026-10-24

    DATE: October 24, 2026 at 04:00PM
    SOURCE: PSYPOST.ORG

    ** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
    -------------------------------------------------

    TITLE: Expecting to lose economic standing hurts well-being more than expecting to gain helps it

    URL: https://www.psypost.org/expecting-to-lose-economic-standing-hurts-well-being-more-than-expecting-to-gain-helps-it/

    Believing that your socioeconomic position could decline in the future may itself reduce well-being by increasing anxiety about social status, according to research published in Personality and Social Psychology Bulletin. Expectations of moving up the ladder, by contrast, had weaker and less consistent effects.

    Social mobility describes movement up or down the socioeconomic ladder, which can involve changes in income, employment and social standing. Much of the previous research has focused on the promise of upward mobility. But the prospect of moving in the opposite direction may be especially important at a time when some people in wealthy countries expect to experience lower living standards than previous generations.

    The researchers focused on status anxiety, or worry about one’s position in the socioeconomic hierarchy. This can include concerns about losing status, failing to advance or being left behind compared with other people. Because anticipated downward mobility represents the possibility of losing resources and social standing, the researchers proposed that it could increase status anxiety and consequently reduce well-being.

    Led by Davide Melita of the University of Granada in Spain, the researchers conducted four studies involving 2,819 people in Spain and the United States. The first two were surveys, while the final two were experiments designed to determine whether changing people’s expectations about their socioeconomic future could actually affect status anxiety.

    Study 1 surveyed 216 full-time U.S. workers (average age 39; 49% women) about their beliefs regarding mobility in American society as a whole, such as whether most people now earn less than the previous generation. Those who believed downward mobility was more common reported greater status anxiety, which was in turn associated with lower life satisfaction, poorer perceived health and more depressive symptoms. Beliefs about upward mobility were not linked to status anxiety.

    Study 2 surveyed 1,536 people in Spain (51% women), recruited to resemble the national population, using single questions about whether participants expected their own socioeconomic status to improve or worsen. Expecting one’s own status to worsen was associated with greater status anxiety and lower life satisfaction. Unexpectedly, expecting one’s status to improve was also associated with greater status anxiety, although it was directly linked to higher life satisfaction as well. The authors suggest that strong expectations of change in either direction may bring uncertainty about the future.

    The researchers then tested the relationship experimentally. In Study 3, 472 Spanish university students (average age 22; 70% women) imagined starting a new life in a fictional society called Bimboola. Everyone began in the middle-income group, but participants were randomly told they had good chances of moving up, staying in the same group or moving down, while the level of inequality in the society was held constant.

    Participants told they were likely to move down reported more status anxiety than those told they were likely to stay put, although the difference was small. In exploratory analyses, that increased anxiety in turn predicted lower satisfaction with their imagined life in Bimboola. Being told they were likely to move up, however, did not affect status anxiety.

    Study 4 repeated the experiment with 595 employed Americans recruited online, and here the manipulation had much stronger effects on participants’ expectations. Prospects of moving down increased status anxiety, while prospects of moving up reduced it, and these changes in anxiety carried through to life satisfaction in Bimboola in opposite directions. The negative effect of anticipated decline was larger than the positive effect of anticipated advancement.

    Across the four studies, the pattern for downward mobility was notably consistent: believing that one’s socioeconomic position could worsen was associated with greater status anxiety and, through that anxiety, lower well-being. By contrast, the results for upward mobility varied between studies, and only the U.S. experiment found that prospects of moving up reduced status anxiety and indirectly increased life satisfaction.

    Melita and colleagues summarized, “our findings suggest that both upward and downward beliefs influence well-being through status anxiety, but the effects of downward mobility beliefs are stronger and more consistent.” The authors argue that policies aimed at improving well-being should not only expand opportunities for upward mobility but also protect vulnerable groups from economic downturns, for example by strengthening social safety nets.

    Some limitations should be noted. The first two studies were correlational, and Study 2 measured mobility expectations with single questions. The experiments involved an imaginary society rather than actual unemployment, income loss or downward mobility, and they measured satisfaction with life in that imaginary society rather than participants’ real lives.

    The researchers also noted that cultural circumstances could influence people’s reactions to the scenarios. The Spanish experiment involved young adults in a country with high youth unemployment, who may be skeptical about upward mobility, while Americans tend to overestimate how much mobility exists.

    The study, “Prospects of Downward Mobility Cause Status Anxiety and Life Dissatisfaction,” was authored by Davide Melita, Matthias S. Gobel, Juan Matamoros-Lima, Rosa Rodríguez-Bailón and Guillermo B. Willis.

    URL: https://www.psypost.org/expecting-to-lose-economic-standing-hurts-well-being-more-than-expecting-to-gain-helps-it/

    -------------------------------------------------

    Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org

    Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot

    -------------------------------------------------

    #psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #SocialMobility #EconomicMobility #StatusAnxiety #Wellbeing #MentalHealth #LifeSatisfaction #EconomicInequality #SocialPsychology #EconomicSecurity #ResearchStudy

    #researchstudy #psychology #counseling #socialwork #psychotherapy #mentalhealth
25. 

    Esslar2 @flyhigh

    2026-10-24

    Last Wednesday, a 14-year-old guy riding an e-motorcycle (not an e-bicycle that has pedals) on a hiker-biker trail on which e-motorcycles are not allowed, rode through an intersection with a 2-lane road, struck the side of a full-size pickup truck and died in the hospital. This was in Severna Park, MD.

    14 years old.

    I've had some of these e-motorcycles ride toward and come from behind me on that trail. They are as big as small ICE-powered motorcycles (125cc or 175cc) and if someone hit you with one, you could be badly hurt or killed.

    I don't know how these things can be controlled but you can't have anyone, adults or kids, riding these heavy two-wheelers at speed where people are walking and running.

    It's a damn shame what happened here. No one under 16 should be allowed to ride these things and then they should only be ridden on roads, not sidewalks or hiking trails.

    PS I've seen some adults riding too fast on these things, so it isn't just teens, either.

26. 

    Dev Community @[email protected]

    2026-10-24

    The tech industry has a strange contradiction right now.
    Companies are investing billions in artificial intelligence, building new platforms, shipping increasingly sophisticated products, and talking about unprecedented productivity gains.

    At the same time, thousands of developers, engineers, designers, QA specialists, and other technology professionals are facing an uncertain future.

    According to TechRepublic's October 2026 tech layoffs report, nearly 200,000 people had been affected by reported technology-sector layoffs as of October 23.

    That number is difficult to ignore.

    But behind every headline is a more personal question:

    How do you build a sustainable career in an industry that keeps changing the definition of valuable work?

    Let's look beyond the headlines and explore what these layoffs mean for developers, why AI isn't the whole story, and how we can prepare for an increasingly unpredictable technology landscape.

    1. The Layoffs Aren't Just Numbers on a Dashboard

    When a company announces a workforce reduction, the news is usually presented through percentages, headcounts, and stock-market reactions.

    For the people affected, the experience is very different.

    It's the developer who spent five years maintaining a critical service.

    It's the QA engineer who prevented production incidents nobody outside the team ever noticed.

    It's the infrastructure specialist who kept systems running during the most difficult outages.

    It's the junior engineer who finally landed their first job after months of interviews.

    These professionals don't suddenly lose their knowledge, experience, or ability to solve problems when their employment ends.

    Yet a layoff can make even experienced engineers question their value.

    One important distinction is worth remembering:

    A company eliminating a position does not automatically mean the person occupying it lacked value.

    Organizations restructure for many reasons, including financial pressure, acquisitions, overlapping responsibilities, strategic changes, and shifting investment priorities.

    Some reductions are connected to AI. Others aren't.

    For developers, understanding that distinction matters. Otherwise, it's easy to interpret every layoff as evidence that a particular skill or career path has become obsolete.

    The reality is more complicated.

    2. Is AI Replacing Developers, or Changing What Developers Do?

    This is probably the biggest question in software engineering right now.

    AI coding assistants can generate boilerplate, suggest implementations, explain unfamiliar code, create test cases, and help developers explore possible solutions.

    These capabilities are useful. Ignoring them entirely isn't a particularly strong career strategy.

    But the conversation becomes less useful when we reduce everything to a simplistic prediction: AI will either replace all developers or never replace any of them.

    Neither assumption helps us make better decisions.

    Consider a typical feature request.

    An AI tool might help generate an API endpoint in minutes. However, delivering that feature safely may still require someone to:

    Understand the business requirements and identify missing assumptions.

    Design the API contract and choose appropriate data models.

    Evaluate authentication, authorization, and data privacy risks.

    Test edge cases, failure modes, and unexpected inputs.

    Review database performance and concurrency behavior.

    Integrate the feature with existing services and deployment pipelines.

    Monitor production behavior and investigate incidents.

    Generating code is only one part of delivering reliable software.

    The challenge is that AI can make some tasks faster while also changing how much work a team needs to complete them.

    That can create real workforce pressure, particularly when organizations expect smaller teams to deliver more.

    And there's an important caveat: AI adoption and layoffs happening at the same time do not prove that AI directly replaced every affected employee.

    TechRepublic's reporting highlights this distinction. Some companies have explicitly connected restructuring to AI-focused strategies, while others have cited different organizational or business reasons.

    For developers, the practical takeaway isn't to panic or dismiss AI.

    It's to learn where these tools are useful, understand their limitations, and become better at the engineering decisions surrounding their output.

    3. The Real Competitive Advantage Is Engineering Judgment

    If AI can generate a plausible implementation, what makes an experienced developer valuable?

    Increasingly, the answer is the ability to determine whether that implementation is actually correct, maintainable, secure, and appropriate for the problem.

    Imagine an AI assistant generates a database query that works perfectly against a small development dataset.

    Will it still perform well when the production table contains 200 million records?

    What happens when two requests update the same resource simultaneously?

    Could the query expose information that the requesting user isn't authorized to see?

    Does the implementation introduce a subtle regression in another service?

    These aren't merely code-generation problems. They require engineering judgment.

    The same principle applies to testing.

    A test suite can report 95% code coverage while missing the business-critical scenario that causes a production outage.

    A generated test can confirm that a function returns the expected result without checking whether the result itself makes sense.

    A passing build doesn't guarantee a reliable system.

    This is where developers can differentiate themselves.

    Focus on capabilities that help you reason about the entire system:

    System design: Understand service boundaries, data flows, failure modes, and trade-offs.

    Debugging: Trace problems across application layers rather than guessing at isolated symptoms.

    Testing: Design meaningful assertions, boundary tests, integration tests, and failure scenarios.

    Security: Recognize vulnerabilities that aren't obvious from a successful demo.

    Performance: Understand latency, throughput, resource consumption, and scaling constraints.

    Communication: Explain technical decisions and their consequences to people with different backgrounds.

    These skills aren't immune to automation. AI can assist with many of them.

    Their value comes from knowing how to apply them, verify results, and take responsibility for the outcome.

    4. Stop Measuring Your Career by the Number of Technologies You Know

    When layoffs dominate the news, it's tempting to respond by learning everything.

    A new framework appears, so you learn it.

    A new AI tool launches, so you try it.

    A new programming language becomes popular, so you add it to your list.

    Soon, your learning backlog becomes larger than any project you could realistically finish.

    The problem isn't curiosity. It's confusing exposure with capability.

    Knowing that a tool exists is different from being able to use it to solve a meaningful problem.

    Instead of collecting technologies, build evidence of your engineering ability.

    For example, rather than creating five small repositories that demonstrate basic syntax, consider building one application that includes:

    A documented API with authentication and input validation.

    Automated unit and integration tests.

    Database migrations and realistic test data.

    Logging, metrics, and useful error handling.

    A CI pipeline that runs checks before deployment.

    A deployment strategy with a documented rollback procedure.

    A README explaining architecture decisions and known limitations.

    This project gives you more than a list of technologies.

    It demonstrates how you approach the complete software development lifecycle.

    If you use AI to build parts of it, document where you used it, how you reviewed its suggestions, and what you changed after testing.

    The goal isn't to pretend you wrote every line manually.

    The goal is to demonstrate that you can deliver software responsibly.

    5. Build a Career That Doesn't Depend on One Employer

    A layoff can be especially disruptive when nearly all your professional identity, network, and sense of security are tied to a single company.

    You can't eliminate that risk entirely, but you can reduce your dependence on any one organization.

    Start by keeping your professional portfolio current.

    You don't need to publish confidential company code or turn every weekend into a side-project marathon. You can document open-source contributions, personal projects, technical articles, or lessons learned from problems you've solved.

    Next, maintain professional relationships before you need them.

    Talk with former colleagues. Participate in technical communities. Share useful findings. Review other people's code. Contribute to discussions where you can genuinely help.

    Networking works better when it isn't treated as an emergency activity that begins the day after a layoff.

    Also, periodically review your accomplishments.

    Don't just record that you worked on a service. Record what changed because of your work.

    Examples include:

    Reduced API latency by identifying an inefficient database query.

    Improved release confidence by introducing integration tests.

    Reduced incident investigation time by improving observability.

    Simplified a deployment pipeline and removed manual steps.

    Identified and resolved a security weakness before release.

    Use real measurements when available. Never invent metrics to make a résumé look impressive.

    These examples help communicate the value of your work beyond a job title or list of responsibilities.

    Finally, if circumstances allow, build some financial breathing room. Even a modest emergency fund can create options when a job search takes longer than expected.

    Career resilience isn't only about technical skills. It's also about having choices.

    6. Don't Assume Every Company Is Hiring for the Same Kind of Developer

    A headline about thousands of job cuts at a major technology company can make the entire industry look closed.

    But company-wide reductions don't tell the whole story about individual teams, occupations, or hiring needs.

    A company can reduce its overall headcount while continuing to recruit for selected roles. Another company may be expanding its engineering organization while a competitor contracts.

    That doesn't mean finding a job is easy. It means the available evidence needs to be interpreted carefully.

    When researching opportunities, look beyond the employer's brand name.

    Investigate the specific role, team responsibilities, required experience, and business context.

    Ask questions such as:

    Is the role associated with a core product or a short-term initiative?

    What problems will the team be expected to solve?

    How does the company measure engineering quality?

    Is the position new, a replacement, or part of an expanding team?

    What expectations does the employer have around AI-assisted development?

    How does the team handle on-call responsibilities, technical debt, and production incidents?

    During interviews, pay attention to how people describe the work.

    An organization that expects developers to use AI responsibly, review code carefully, and understand production systems may offer a different engineering environment from one that measures productivity primarily by the number of tickets closed.

    No interview can guarantee job security.

    However, understanding the role helps you make a more informed decision than relying on a company's reputation alone.

    7. Junior Developers Need a Different Strategy, Not a Reason to Give Up

    For people entering software development, the current environment can feel particularly discouraging.

    Entry-level positions often require practical experience, but gaining that experience can be difficult without an initial opportunity.

    AI adds another layer of uncertainty because some of the tasks traditionally assigned to junior engineers can now be automated or completed more quickly.

    Still, the conclusion shouldn't be that learning to code is pointless.

    Instead, aspiring developers should focus on demonstrating that they understand the fundamentals rather than simply knowing how to prompt a coding assistant.

    Learn how data structures work. Understand HTTP, databases, version control, testing, and debugging. Practice reading unfamiliar code and explaining why a solution works.

    Then use AI as a learning partner.

    Ask it to explain an unfamiliar implementation. Request alternative approaches. Generate test cases and investigate whether they are correct. Compare its output with official documentation.

    Most importantly, practice solving problems without blindly accepting generated answers.

    Build projects that solve real problems, however small. Contribute documentation or bug fixes to open-source projects. Collaborate with other developers. Learn to discuss trade-offs and explain decisions clearly.

    Your first opportunity may take longer to find than you expected.

    That delay doesn't make the effort meaningless, and a difficult job market doesn't determine your long-term potential.

    8. What Engineering Teams Should Learn From These Layoffs

    This discussion shouldn't be limited to individual career advice.

    Engineering leaders also have responsibilities.

    If an organization reduces its workforce and expects the remaining team to maintain the same systems, deliver more features, and adopt unfamiliar AI tools immediately, the result can be increased pressure rather than improved productivity.

    Fewer engineers don't automatically mean less work.

    Someone still needs to maintain legacy systems, investigate incidents, review generated code, manage dependencies, and understand architectural decisions made years earlier.

    If that knowledge leaves with departing employees, the organization may lose capabilities that are difficult to rebuild quickly.

    Teams should therefore pay attention to:

    Knowledge preservation. Document critical systems, operational procedures, and architectural decisions before organizational changes create gaps.

    Quality controls. Establish clear expectations for testing, code review, security checks, and AI-generated contributions.

    Realistic capacity planning. Measure delivery outcomes and system reliability, not just the number of tasks completed.

    Sustainable ownership. Make sure critical services have adequate support and aren't dependent on one remaining engineer.

    Responsible AI adoption. Evaluate tools against real engineering workflows, including their costs, limitations, security implications, and effect on review effort.

    The goal should be to improve the way teams build and maintain software, not simply to make smaller teams absorb more responsibilities.

    9. A Practical 30-Day Plan for Developers

    You don't need to reinvent your entire career because of a difficult news cycle.

    A focused month can help you identify gaps and make tangible progress.

    Week 1: Audit your current skills

    Choose a technical area relevant to your goals. Review your recent work and identify what you can demonstrate confidently versus what you only know in theory.

    Update your résumé with specific, truthful accomplishments.

    Week 2: Strengthen one practical skill

    Choose a skill that supports your existing experience, such as API testing, database performance, cloud deployment, observability, or secure coding.

    Build a small exercise that forces you to apply it rather than just watch tutorials.

    Week 3: Complete and document a project

    Finish a useful improvement or small end-to-end application. Add automated tests, clear documentation, and a short explanation of your design choices.

    If you use AI, verify its output and document meaningful limitations you discovered.

    Week 4: Improve your professional visibility

    Publish a technical article, contribute to an open-source project, share a useful debugging lesson, or reconnect with former colleagues.

    Review relevant job descriptions to identify recurring requirements, then compare them with your current experience.

    At the end of the month, evaluate what you accomplished.

    You may not have a new job, a perfect résumé, or mastery of a new technology. That's fine.

    The objective is to build momentum and make your next step more deliberate.

    Final Thoughts: Your Career Is Bigger Than This Year's Headlines

    The 2026 layoffs are a serious reminder that working in technology doesn't guarantee employment security.

    They also highlight the need to think carefully about AI, organizational change, and the skills that help engineers deliver reliable software.

    But there's a difference between recognizing that the industry is changing and assuming that your future has already been decided.

    You don't control every restructuring decision. You can't predict which company will announce cuts next. You can't guarantee that mastering a particular framework will protect you from a difficult job market.

    What you can control is how you learn, how you demonstrate your abilities, how you adapt to new tools, and how you build relationships with other people in the industry.

    Don't compete with AI at generating code faster. Learn to build better systems, ask better questions, verify results, and solve problems that matter.

    And remember that your worth as a developer isn't measured by a company's headcount spreadsheet.

    The industry will continue to evolve. Our task is to keep learning without losing sight of the human judgment, collaboration, and responsibility that good engineering requires.

    Let's discuss

    I'm curious how other developers are navigating this period of change.

    AI and engineering: Has AI meaningfully changed the way you write, test, or review code?

    Career resilience: Which skills do you believe are becoming more valuable as teams adopt AI tools?

    Hiring: Are you seeing different expectations for junior, mid-level, and senior developers?

    Team culture: What can engineering leaders do to help teams adapt without sacrificing software quality or employee well-being?

    Share your experiences in the comments. Practical insights from people doing the work are often more useful than another prediction about the future of tech.

    Editorial note: This article is an independent, developer-focused perspective inspired by TechRepublic's reporting on 2026 technology layoffs. Layoff totals reflect reported announcements, not necessarily completed job losses. Figures and company circumstances can change as new information becomes available.#discuss #career #ai #programming #software #coding #development #engineering #inclusive #community
    Tech Layoffs in 2026: What Developers Should Do When the Industry Changes the Rules

    #ai #community #programming #software #coding #development
27. 

    Dev Community @[email protected]

    2026-10-27

    OpenAI launched GPT-6.1 Terra on October 26, 2026, and if you build agents for a living, the interesting question is not "is it smart?" It is "where does it sit in my routing table?" After reading OpenAI's own numbers as reported on October 26–27, my answer is: Terra becomes the default tier, and the flagships become the exception. Here is the reasoning, with the numbers that justify it.
    

    The default tier, priced like one

    
    Terra's API pricing is $1 per million input tokens, $0.05 per million cached input tokens, and $5 per million output tokens — 50% below GPT-5.6 Terra and GPT-6.1 Sol. Standard rates cover prompts up to 272,000 input tokens; beyond that, input and cache rates double and output costs 1.5x for the full request. It is available in ChatGPT Work and Codex for Plus, Pro, Enterprise and Edu users, and via the API as gpt-6.1-terra.

    Price alone would not move me. Price plus speed plus accuracy does. Terra runs tasks more than three times faster than GPT-6 Astra and GPT-6.1 Sol. On Agents' Last Exam — professional work such as turning architectural drawings into 3D models or reviewing film scenes into time-coded logs — it beats its predecessor by 15 points at medium reasoning effort, at about a third of the cost, matching Astra at roughly a tenth of the token price. On OSWorld 2.1, multi-step desktop-app work, it beats its predecessor's best score at medium effort and costs less per task.
    

    The routing rule

    
    Here is the rule I would ship this week:

    1. Terra by default for the workday bulk: invoice intake, form filling, document processing, inbox triage, proposal drafts, screenshot and drawing interpretation, and routine coding — scripts, fixes, refactors, tests.
    2. Sol or Astra on exception for complex coding and the hardest reasoning. Terra's Terminal-Bench 4.0 score is 50.3% at maximum effort — more than double its predecessor's 21.5% — but OpenAI itself says Sol and Astra are better for complex coding. Believe the vendor on its own product's limits.
    3. Effort as a dial, not a setting. Start bulk tasks at medium effort. Escalate to maximum effort only where the error rate matters, because the error numbers justify that dial: on OpenAI's error-inducing internal test, Terra's error rate is 16.7% at low effort (down from 53.6% for the predecessor) and 4.3% at maximum effort — comparable to the flagships.

    That third point is the one most routing layers get wrong. They route by model, once, at design time. Terra rewards routing by model and effort, per task, at runtime. A form-fill at medium effort and a contract-summary at maximum effort are different jobs even when they use the same model.
    

    Two tests before you widen autonomy

    
    Terra's alignment claims are the part I would verify before trusting it with a computer. OpenAI says it stays within scope, discloses limitations and blockers honestly, and resists prompt injection in testing. For a computer-use model, those are not nice-to-haves — they are the security boundary.

    Test one: put an instruction inside a document that contradicts your instruction, and see whether Terra follows the document or you. Test two: give it a task with a deliberate blocker and see whether it reports the blocker or invents a completion. If it passes both on your data, widen autonomy gradually. If it fails either, keep the human approval gate — especially for money, legal, or irreversible actions. A 4.3% error rate at maximum effort is excellent for this tier, and it is still an error rate.
    

    Measure cost per finished task

    
    The metric that matters after the switch is not cost per token. It is cost per completed task, including retries and corrections. Terra's speed and accuracy gains compound there: fewer retries, fewer human corrections, lower total cost even before the 50% price cut. Run your five most common tasks through Terra for a week, log completion rate, error rate, and cost per finished task at medium and maximum effort, and let that table — not the launch blog — set your permanent routing.

    Terra is not the model you show off. It is the model you leave running all day. Priced and performing like this, that is exactly where it belongs: as the default, with flagships reserved for the work that actually needs them.

    Sources: OpenAI GPT-6.1 Terra launch (October 26, 2026), as reported by NewsBytes, Okay News, and MoneyToday (October 27, 2026). Benchmark figures are OpenAI's own reported evaluations. Author: Shivam Kumar, Founder, VisionQuantech.#ai #llm #openai #agents #software #coding #development #engineering #inclusive #community
    I Re-Priced My Agent Stack on GPT-6.1 Terra: Here's the Routing Rule I'd Actually Ship

    #ai #community #software #coding #development #engineering
28. 

    Psychology News Robot @[email protected]

    2026-10-26

    DATE: October 26, 2026 at 12:00PM
    SOURCE: PSYPOST.ORG

    ** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
    -------------------------------------------------

    TITLE: Frequent cannabis use linked to higher odds of nighttime breathing problems

    URL: https://www.psypost.org/frequent-cannabis-use-linked-to-higher-odds-of-nighttime-breathing-problems/

    Adults who use cannabis are more likely to report loud snoring and pauses in breathing during the night, according to new research published in Sleep Health: Journal of the National Sleep Foundation. The findings indicate that more frequent cannabis consumption corresponds with higher odds of experiencing these nocturnal breathing issues, even after accounting for factors like body weight and tobacco smoking. This relationship raises important questions for the growing number of people who turn to cannabis as a sleep aid.

    Sleep-disordered breathing is an umbrella term for medical conditions characterized by abnormal respiratory patterns or insufficient ventilation during rest. The most common form is obstructive sleep apnea, a disorder in which the muscles in the back of the throat relax too much, causing the upper airway to narrow or collapse entirely. People with this condition require extra physical effort to breathe, often resulting in loud snoring, gasping, or brief, repeated stops in breathing known as apneas. Standard treatments like continuous positive airway pressure machines, oral appliances, and surgery can be effective, yet many patients find the devices uncomfortable or difficult to tolerate over the long term.

    At the same time, cannabis has become increasingly accessible across the United States, and difficulty sleeping is one of the most common reasons people cite for using it. While users frequently report that the plant helps them rest, controlled clinical trials examining cannabinoids and sleep have produced mixed outcomes.

    For example, a 2023 clinical trial covered by PsyPost found that consuming medicinal cannabis oil improved sleep duration and increased midnight melatonin levels in adults with insomnia, whereas a study covered by PsyPost in 2024 indicated that a cannabis compound called cannabinol reduced nighttime awakenings when taken alone but showed no benefit when combined with cannabidiol, another cannabis compound. Observational tracking also points to potential drawbacks, such as a 2026 longitudinal study of military service members that linked current cannabis use to worse overall sleep quality and longer times needed to fall asleep.

    When it comes to breathing disorders specifically, tetrahydrocannabinol, the primary psychoactive compound in cannabis, has shown some potential to stabilize breathing in animal experiments and small human trials using oral pills. However, the broader clinical evidence remains inconsistent, leading the American Academy of Sleep Medicine to formally advise against using cannabis to treat obstructive sleep apnea. Most everyday consumers inhale cannabis rather than taking standardized pills, exposing their airways to smoke and heat that could inflame the tissues of the throat.

    The new research, led by Tyler J. Gallagher, a resident physician in the Caruso Department of Otolaryngology-Head and Neck Surgery at the Keck School of Medicine of the University of Southern California, and co-first author Matthew E. Lin of the David Geffen School of Medicine at the University of California, Los Angeles, sought to evaluate how everyday consumption relates to signs of breathing issues at night.

    “While some studies have explored cannabinoids as potential treatments for obstructive sleep apnea, there has been relatively little population-level research examining whether real-world cannabis use is associated with common signs of sleep-disordered breathing, such as loud snoring and pauses in breathing during sleep,” Gallagher told PsyPost. “We sought to better understand this relationship using a nationally representative sample of US adults.”

    To investigate this connection, the authors analyzed information from the 2017 to 2018 Behavioral Risk Factor Surveillance System, a state-based telephone survey coordinated by the Centers for Disease Control and Prevention. Although nearly 900,000 adults completed the main survey during those two years, only Minnesota and Tennessee included optional survey modules asking about both cannabis habits and sleep breathing symptoms. From the respondents in those two states who had complete data, the researchers selected a stratified random sample of 14,485 adults designed to match the demographic profile of the broader United States population.

    Participants were asked how many days they had used marijuana or cannabis during the past 30 days, as well as their primary method of consumption and whether they used it for medical or recreational purposes. The researchers grouped the respondents into three categories: non-users (zero days in the past month), non-regular users (1 to 15 days), and regular users (16 to 30 days). Signs of sleep-disordered breathing were assessed using two yes-or-no questions asking if anyone had ever observed the respondent stop breathing during sleep, and if the respondent had ever been told that they snore loudly.

    Of the participants, 13,461 reported no current cannabis use, 438 were classified as non-regular users, and 364 were regular users, meaning about 5.5 percent of the sample currently used cannabis. Smoking was by far the most common consumption method, reported by about 87 percent of both non-regular and regular consumers, followed by vaporizing and eating. Among non-regular users, 61.6 percent used cannabis strictly for recreational reasons, whereas 37.6 percent of regular users reported using it strictly for medical reasons and another 24.7 percent used it for both medical and recreational purposes.

    Overall, signs of sleep-disordered breathing were common across the entire cohort, with 44.7 percent reporting either loud snoring or witnessed apneas. In the unadjusted raw numbers, 44.3 percent of non-users reported at least one of the two breathing signs, compared to 48.4 percent of non-regular users and 55.2 percent of regular users. Specifically, witnessed breathing pauses were reported by 15.3 percent of non-users, 17.1 percent of non-regular users, and 19.8 percent of regular users. Loud snoring was reported by 41.3 percent of non-users, 44.5 percent of non-regular users, and 50.0 percent of regular users.

    To account for other differences between users and non-users, the researchers ran statistical models that applied national survey weights (statistical adjustments that make a sample better mirror the U.S. adult population) and controlled for a wide range of potentially confounding factors. These adjustments accounted for age, sex, race and ethnicity, education, income, health insurance status, diabetes, body mass index, alcohol consumption, traditional cigarette smoking, and electronic cigarette use. Even after factoring out the influence of tobacco smoking and body weight, cannabis use remained independently associated with higher odds of sleep-disordered breathing symptoms.

    Compared to non-users, non-regular cannabis users had 41 percent higher odds of reporting witnessed apneas, 26 percent higher odds of reporting loud snoring, and 33 percent higher odds of experiencing either symptom. The association was more pronounced among regular consumers. Those who used cannabis 16 to 30 days per month had 73 percent higher odds of witnessed apneas, 68 percent higher odds of loud snoring, and 82 percent higher odds of reporting either sign compared to non-users. These figures describe odds rather than probabilities, so the absolute differences are smaller than the percentages might suggest; in the raw numbers, about 55 percent of regular users reported at least one sign, compared with about 44 percent of non-users.

    “While the impact of infrequent use is relatively small, the odds of irregular breathing during sleep almost double with more frequent cannabis use, making this a strong association worthy of consideration before frequent cannabis utilization,” Gallagher explained.

    The researchers also analyzed cannabis consumption as a continuous spectrum from zero to 30 days. In the weighted models, each additional day of cannabis use per month was associated with an approximate 2 percent increase in the odds of reporting witnessed apneas, loud snoring, or either sign, an estimate the authors note is clinically small and serves as a general summary across use levels rather than a strict per-day effect. When the authors repeated the analysis without the national survey weights, regular cannabis use remained linked to both breathing signs, though the estimates were smaller (for example, 36 percent higher odds of either sign rather than 82 percent). In that analysis, non-regular use was no longer linked to loud snoring or to either sign, and its link with witnessed breathing pauses sat right at the threshold of statistical significance.

    “The strength of the association and its greater magnitude among more frequent users were notable, particularly given that some studies have investigated cannabinoids as potential treatments for sleep apnea,” Gallagher said. “These findings may reflect differences between isolated cannabinoids studied in clinical settings and real-world cannabis use, including differences in composition and method of consumption.”

    The authors proposed two primary biological mechanisms that might explain why cannabis consumers report more signs of airway obstruction at night. Because roughly 87 percent of the consumers in the sample smoked their cannabis, physical irritation from smoke is one possible contributor. Unlike tobacco, cannabis smoke is typically inhaled through deeper breaths without a filter, and it burns at a higher temperature, which can cause thermal injury and inflammation in the throat tissues that narrow the upper airway.

    A second potential mechanism involves the way cannabis interacts with the autonomic nervous system, which regulates involuntary body functions. While small doses of cannabis tend to stimulate the sympathetic nervous system, the body’s “fight or flight” system, higher doses activate the parasympathetic nervous system, which promotes physical relaxation. Frequent users may develop tolerance and consume larger quantities, and the resulting parasympathetic activity may cause the muscles that hold the upper airway open to relax excessively during sleep, making the throat more likely to collapse.

    There are a few things to keep in mind when interpreting these findings. Because the survey captured information at a single point in time, the study cannot establish whether cannabis use causes sleep-disordered breathing or if the relationship works in the opposite direction. People who suffer from undiagnosed sleep apnea often experience fragmented, unrefreshing sleep, and it is possible that some of these individuals turn to cannabis in an attempt to self-medicate their exhaustion or insomnia. The researchers also could not account for factors such as sleeping pill or sedative use, heavy drinking, or psychiatric conditions, any of which might influence both cannabis use and nighttime breathing.

    The reliance on self-reported telephone survey data also introduces constraints. Asking participants if they have been told they snore or stop breathing is less reliable than conducting an overnight medical sleep study, and people who sleep alone may be unaware of their nighttime breathing habits. Additionally, the survey only tracked how many days a person used cannabis over the past month, without measuring the exact dosage, potency, or ratio of specific compounds like tetrahydrocannabinol and cannabidiol.

    The data came from just two states, Minnesota and Tennessee, because they were the only ones to include both sets of questions, and roughly 98 percent of the original survey respondents were excluded for that reason or because of missing information. Survey weights help align the sample with national demographics, but the authors note that applying them to such a small subset is debated among statisticians. In addition, the breathing questions asked whether these symptoms had ever been observed, while the cannabis question covered only the past month, so some symptoms may have predated participants’ current cannabis habits.

    Gallagher emphasized that reporting these symptoms is not the same as receiving a formal medical diagnosis. “While obstructive sleep apnea – a clinically defined and hazardous intermittent airway obstruction during sleep – is a type of sleep-disordered breathing, this study cannot make conclusions about the association between cannabis use and sleep apnea or other associated long-term risks,” he noted.

    Future research will need to incorporate objective sleep testing, such as polysomnography, an overnight sleep study that monitors breathing, oxygen levels, and brain activity, to verify whether cannabis habits correspond with clinically diagnosed sleep apnea. Scientists also need to compare different delivery methods, such as edibles versus inhalation, to separate the chemical effects of cannabinoids on throat muscles from possible damage from inhaling hot smoke.

    “Further research is required to examine the long-term effects of cannabis use on sleep and to determine the effects of cannabis dosage, different cannabis compositions, and different methods of consumption on sleep-disordered breathing,” Gallagher said. “Additionally, the long-term consequences of these impacts must be studied.”

    Until those relationships are clarified, the authors suggest that physicians should counsel patients about the potential respiratory risks of using cannabis, particularly for individuals who already show signs of sleep-disordered breathing. “People experiencing persistent snoring, pauses in breathing, or other symptoms of sleep apnea should seek medical evaluation rather than trying to utilize cannabis to manage their sleep,” Gallagher advised.

    “This study highlights the importance of evaluating the broader health effects of substances that people increasingly use for self-management,” Gallagher added. “Cannabis may have benefits for certain symptoms or conditions, but those potential benefits should be considered alongside possible risks. Sleep-disordered breathing is particularly important because it can go unrecognized for years while causing significantly worse quality-of-life. We hope these findings encourage further research and help clinicians have more informed conversations with patients who use cannabis for sleep-related concerns.”

    The study, “Cannabis use and associated sleep-disordered breathing among US adults,” was authored by Tyler J. Gallagher, Matthew E. Lin, Ian Kim, Ziva D. Cooper, Sebastian M. Jara, and Eric J. Kezirian.

    URL: https://www.psypost.org/frequent-cannabis-use-linked-to-higher-odds-of-nighttime-breathing-problems/

    -------------------------------------------------

    Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org

    Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot

    -------------------------------------------------

    #psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #Cannabis #SleepHealth #SleepApnea #SleepDisorderedBreathing #LoudSnoring #NighttimeBreathing #RespiratoryHealth #HealthResearch #MedicalResearch #SleepAwareness

    #psychology #counseling #socialwork #psychotherapy #mentalhealth #psychiatry
29. 

    Allen Hutchison @[email protected]

    2026-10-26

    Tokens Over Hires

    In the middle of September I ran ccusage against every Claude Code session on my laptop since May. It walks the local logs, counts the tokens, and prices them at what the API would have charged. I expected a big number. What came back was about twenty billion tokens and just under fourteen thousand dollars, across every project I’d touched in four months, with most of it going to Pepper, which is now open for signups, so go check it out. Nineteen billion of those tokens were cached reads.

    I sat with that for a minute. Fourteen thousand dollars is real money. At my current pace it works out to roughly thirty thousand a year. I could triple it and spend a hundred thousand dollars a year on tokens, and that still isn’t one engineer. In exchange, Chris and I have shipped more code than I’ve shipped in any stretch of my career. I wrote in September that the two of us merged 657 pull requests in our first thirty days with a budget instead of a platform team. When I put the ccusage number in those terms on a panel, it came to about a dollar fifty a pull request.

    That number is what my laptop would have cost at API prices, and it isn’t what we actually pay. Here’s the whole bill for both of us. Two Codex subscriptions, one each, are $200 a month. Anthropic is $550 a month: a Max plan for me and Chris, plus two Vycari team seats, one for Chris and one that runs our automation. I have an Ollama subscription at $200 a year. Greptile is about $1,500 a month. All in, that’s a little under $2,300 a month, or about $28,000 a year, for both founders and every pipeline we run. It still isn’t one engineer.

    The obvious conclusion is the one a friend reached when he heard the figure: if code is that cheap, just get more tokens. I thought so too, for about a day. Then I looked at what was actually slowing us down, and the token budget wasn’t on the list.

    The Constraint Is Attention

    Every agent I run needs things from me that tokens can’t buy. It needs a plan approved before it starts. It needs its pull request read when it finishes. When it hits something it can’t decide, it escalates, and somebody has to be there to answer. None of those steps is expensive on its own. The problem is what happens when I run enough agents that the steps overlap.

    When I run too many agents, the cost goes up a little and the risk goes up a lot. The biggest thing that’s slipped past us so far was how we managed database connections. It got out of hand, a little at a time, while my attention was on other pull requests, and eventually it caused an outage. Chris had to roll forward while I was out of town, and I spent the following week building a proper database abstraction layer. He put it more bluntly than I would have: the thing that kills us is splitting our attention. That’s when stuff slips through.

    When people ask how we decide what to spend, I give them the order. Optimize for human time, because that’s the scarcest thing we have. Then money, because that’s the second scarcest. Then everything around agent time. “I can waste agent time all day. I don’t care.”

    So the number that limits us is how many agents one person can supervise well at the same time. I don’t have a precise figure for that ceiling. I know I’ve been over it, because I can feel the difference between a day when every pull request got a real read and a day when I was skimming to keep up.

    Another friend told me recently about engineers at his company running up bills in the thousands to build simple internal copies of SaaS tools. His reluctant guess was that they just aren’t as good at using agents yet, and that it’s a skill people have to develop. I don’t know what they’re doing differently. It doesn’t sound like token maxxing, which I’ve never really understood either. I’d love to sit with engineers who run up giant bills and just watch. My guess is they’re using the agents inefficiently, and that what’s missing is supervision, which a bigger budget won’t fix.

    Building for More Agents per Person

    Almost everything I’ve built since the summer has been an attempt to raise that ceiling, and almost none of it has been about spending less.

    The pipeline I described in The Agent That Never Merges is the first piece. Agents open pull requests continuously and never merge them, which means the supervision cost per pull request is bounded at one careful read. The pipeline absorbs the rest: triage, planning, the first round of review comments, the retries. I only see the work once it’s in a state worth my attention.

    The second piece is where the work lives. I wrote about pulling Pepper apart into small, bounded repositories to keep CI fast and give agents less to load. It mattered just as much for my attention. An agent working in a repository with one job produces a pull request I can evaluate in one sitting.

    We’re up to fourteen repositories now. Last week I moved our iOS app out of the monorepo into its own. That was 150,000 lines of code, and nobody noticed except Chris, who had to wait a day to land his next batch of iOS changes. Agents make refactors that size easy. Having the CLI and the iOS client in their own repositories also forces us to keep good API definitions between the server and its clients.

    The third piece is delegation inside the agent layer itself. I run two Claude Opus 5.5 orchestrators on medium effort. One is the UTL, for uber tech lead, and its job is to spawn subagents that build features. The other is what I call the focused worker, and its job is working with me. It catches the manual tasks that come out of the UTL’s pull requests and keeps them in a ledger. Then we work through them together: systems changes, bringing up new platforms, migrating data, anything that needs my level of access and oversight. Everything else goes to a subagent under the UTL, Opus for design docs and code reviews, Sonnet for implementing a feature from a design doc. Every one of these agents can consult a model a tier above it as an advisor, and they all share a wiki for notes.

    Anthropic is now advertising much the same pattern with Claude Projects, and I’m happy to see others arriving at the same answer. Chris has been building a loop that babysits open pull requests through review until they score well enough to be worth a human’s time. Each layer like that turns a job I used to do by hand into something I check. The ceiling goes up one delegated task at a time.

    The Token Budget Was the Easy Problem

    There was a week in September when the meter really was the constraint. We ran through our free credits and paid about $120 in overage. Then AutoDev ate the whole Vycari quota, and I did server cleanup by hand because I couldn’t do anything else.

    Most of that was self-inflicted. I’d started with Fable as the orchestrator, with no cap on context, and burned a week’s quota in three days. The setup above fixed it. The orchestrators run on medium effort, and the cheaper model does the implementing. Opus answers the reviews because Sonnet is too literal about them, and a literal reading turns two review cycles into twelve. Every agent auto-compacts at 200K tokens, because Anthropic charges more for context past that point. With that setup, and the work spread across parallel sessions, I find it hard to spend all of my quota. My goal now is to hit 99% of it every week just before it resets. I keep a list of research projects, and if I have quota left 24 hours before the reset, I spin one up. That isn’t the same as maxing out tokens. I’m not trying to use as many as possible. I’m trying to use all the ones I’ve already paid for.

    There’s also a second account on the same machine. Claude Code reads a CLAUDE_CONFIG_DIR environment variable, so two shells with two config directories give you two accounts side by side. The second one runs the AutoDev and code review pipelines, and those use up its quota every week, so it isn’t a fallback for my own sessions. When I do run short, I supplement with other labs’ plans. Every one of those fixes took an afternoon or less. None of the supervision problems above has had an afternoon fix.

    Where the Money Actually Goes

    While I had the numbers in front of me, I looked at where development spend actually lands, because it isn’t where I expected either.

    Development tokens currently run about ten times what the product itself consumes, even with real people using it. Building the thing costs more than running it. That won’t last. The feedback from our private beta has been really good, and we now open Pepper to a limited number of new signups every day, so product usage is rising quickly.

    Most of what we actually pay goes to code review. Subscriptions are the cheap way to buy tokens if you’re willing to hit limits, so they’re the smaller line. Greptile reviews every pull request we open, and at about $1,500 a month it’s our biggest single expense. We both think it’s worth it, because it’s the layer that lets the never-merge pipeline run without me reading every first draft.

    In October I tested that. I spent a few days building a cheaper reviewer to replace it. I came out the other side saying, “I think we should just pay for it because I can’t do it cheaper.” What I could change was how often we call it. The agents kept asking for a re-review before they’d fixed anything. Because every repository shares a common dev environment, the fix went in once: our pull-request skill now has agents run /simplify and then /code-review before they’re allowed to open a pull request. On many of our repositories, our own reviewer also does the first round and only then calls Greptile. My goal is a pipeline where Greptile’s reviews come back with nothing to say. We’re not there yet, but we get a little better every week.

    I’d rather pay for review than have a second person do it, and the reason isn’t salary. The person would need supervising too, because review is a job I’d have to check, not one I can hand off.

    What a Hire Is For Now

    Five years ago, if I’d been getting a product like this ready for market, I’d have been hiring twenty to fifty engineers. The work would have needed that many hands, and most of what they’d have done was write code. Today the code is the cheap part. If I bring someone in to write code, I’ve added a person who needs plans approved and pull requests read, which is the exact resource I’m short on. A hire whose job is output adds coordination faster than it adds capacity.

    I said on a podcast that came out last week that the code I’ve written would have cost about fifteen thousand dollars at API prices, and that I couldn’t hire engineers for that money. That’s true. The engineers I’d still want are a different kind from the ones I hired at Google. We need a few more people who can herd agents, not fifty.

    The engineering hire that adds capacity is a different shape. It’s someone who can own a bounded service whole. Here’s the interface, here’s everything it needs to do, let me know when it’s done. That person brings their own supervision. They run their own agents, read their own pull requests, and answer their own escalations, and the only thing that crosses the boundary between us is the contract. Supervision divides along the interface instead of piling up on one person. That’s a tech lead’s job, and it’s the only kind of engineering hire I can see that raises the ceiling instead of lengthening the queue.

    That raises a fair question about how anyone grows into that job now, which I tried to answer in The Questions Are the Job. The other advice I give is to work on open source. I’ve met people who showed they could work really efficiently with agents through open source projects, Gemini CLI in particular, and some of them ended up being hired onto my teams. Open source has its own problems right now. But if you show up as a thoughtful engineer with features or bug fixes that are well reviewed, well tested, and bring value to the project, I think you’ll be welcome. That’s one of the reasons I decided to open source the Pepper CLI.

    The first hire probably isn’t an engineer at all. I’ve said this a few times now, including on stage at a panel in September. Neither Chris nor I are go-to-market people, and I may hire one before I hire another engineer. I can create piles and piles of code, even relatively good code. What I can’t do is agentically acquire customers. (Did I mention that Pepper is open for signups now?) Someone in marketing came up after the panel and told me I’d validated her existence.

    The Third Trend

    I’ve watched this happen twice before. Open source developer tooling made it so a small team didn’t need to buy or build its own compilers, databases, and frameworks. Cloud infrastructure made it so that team didn’t need to own hardware or a data center. Each time, the number of people you needed to start something real dropped, and the skills that mattered shifted toward the people who understood systems well enough to compose what was suddenly free.

    Agentic tools are the third one. Anyone with a good idea can now get from concept to production on a budget that would have been a rounding error in a Google planning cycle. But the constraint didn’t vanish. It moved, the same way it did the last two times, toward the people who understand systems design well enough to drive the agents and notice when something has slipped through. I wrote a year ago that management skills were going to carry over to working with agents. I didn’t expect to be proving it with a two-person org chart and fourteen thousand dollars of tokens.

    This isn’t only a small-company problem. At Google it was hard to get more than a few changes in a day, because each one waited on code review. I’ve talked to engineers there who now do all their work in experimental directories that don’t require review, then port it back to their team’s repository at a pace the review process can keep up with. That’s what happens when you don’t manage for human attention. Productive people spend their cycles waiting on the process.

    When other companies ask me what to change, my answer has become: drive until human attention is the scarce resource, then build for that. If you’re reading your own ccusage number and wondering whether the answer is more tokens, look at where your attention went first. For us the answer has been more interfaces. Those are the places where one person’s supervision ends and another’s begins, or where an agent takes over a job one of us used to do by hand.

    #Agents #AI #Developer #Startups

    #startups #developer #ai #agents
30. 

    Psychology News Robot @[email protected]

    2026-10-26

    DATE: October 26, 2026 at 07:00AM
    SOURCE: PSYPOST.ORG

    ** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
    -------------------------------------------------

    TITLE: Political endorsements by scientific journals reduce public trust in research

    URL: https://www.psypost.org/political-endorsements-by-scientific-journals-reduce-public-trust-in-research/

    When scientific journals publicly endorse political candidates, they risk lowering public trust in the scientific community, particularly among moderate and conservative Americans. These endorsements cause measurable declines in how people view the impartiality and societal value of science, though they do not appear to change whether people are willing to follow practical scientific advice. The findings were recently published in the journal Group Processes & Intergroup Relations.

    Public trust in scientific institutions is an important factor in shaping how society responds to global challenges like pandemics and climate change. Historically, scientific organizations have sought to maintain an apolitical stance to preserve their reputation as objective arbiters of fact. In recent years, several high-profile scientific journals have broken from this precedent. Editors at these publications have published pieces endorsing Democratic presidential candidates or strongly criticizing Republican candidates, often framing these stances as necessary defenses of scientific integrity. Researchers wanted to understand how these explicit political stances affect how the American public views the scientific enterprise as a whole.

    Stylianos Syropoulos, Kyle Fiore Law, and their colleagues set out to examine this phenomenon through the psychological framework of motivated reasoning. Motivated reasoning is the human tendency to process information in a way that confirms existing beliefs and political identities. When individuals encounter statements that conflict with their political views, they often scrutinize or reject the source of that information.

    The research team suspected that political endorsements from scientific journals might trigger this psychological mechanism. They hypothesized that people who identify as moderate or conservative might question the objectivity of science after reading endorsements that clash with their political leanings.

    To capture a complete picture, the researchers evaluated trust not as a single concept, but as a collection of distinct dimensions. These dimensions include perceived ability, which is the competence of scientists to provide accurate information. They also looked at integrity, which involves the belief that science is impartial and objective. Benevolence measures the perception that science serves the public good and lacks hidden agendas. Finally, behavioral trust reflects whether people are actually willing to follow scientific recommendations in their daily lives, such as adhering to public health guidelines.

    In the first experiment, conducted shortly before the 2020 presidential election, researchers recruited a large sample of 3,081 participants online. They randomly assigned these participants to read one of two types of texts regarding prominent scientific publications, such as Science, The Lancet, or Scientific American. The control group read a brief, neutral description of the journal’s history and mission formatted like a news wire article.

    The treatment group read the same background information, but with an added excerpt from an actual editorial published by the journal that endorsed Joe Biden or criticized Donald Trump. Following the reading, participants answered a series of questions measuring their trust in science and their intentions to comply with health guidelines.

    The researchers found that reading the political endorsements caused a measurable drop in general trust in scientific institutions. Participants in the treatment group were more likely to report that science lacks impartiality, pointing to a decline in perceived integrity. This effect was largely driven by politically moderate and conservative individuals, who exhibited lower trust after exposure to the endorsements.

    Among conservatives, the treatment also increased belief in conspiracy theories about science and the origins of the coronavirus, indicating a drop in perceived benevolence. However, the endorsements did not yield a statistically significant effect on behavioral trust. Participants exposed to the political messaging remained just as willing to follow practical public health recommendations as those in the control group.

    To see if these results would hold up under different conditions, the researchers conducted a second experiment days before the November 2020 election. They recruited a sample of 1,056 participants, matched to national demographic quotas for age, gender, and ethnicity. The experimental setup mirrored the first study, with participants randomly assigned to read either neutral background text or a political endorsement from a scientific journal.

    The results replicated the core findings of the first experiment. Exposure to the political messaging reduced general trust in science and increased the belief that science is biased, again driven by moderate and conservative participants. In this iteration, the treatment group also reported a lower likelihood of using scientific sources for coronavirus updates, which suggests a decline in perceived scientific ability or competence.

    Just as in the first study, the political endorsements had no statistically significant impact on people’s willingness to comply with practical safety guidelines. The messaging also did not alter belief in conspiracy theories for this specific group.

    A third experiment took place four years later, surrounding the 2024 presidential election. The research team recruited a large sample of 2,144 participants to read material from Scientific American, Nature, or The Economist. The Economist was included because it frequently covers science and technology for a broad audience. As before, participants read either neutral background descriptions or actual published editorials endorsing Kamala Harris or criticizing Donald Trump.

    Because the pandemic was no longer a central issue during this later study, the researchers removed questions about the coronavirus. They added new measures to evaluate general perceptions of scientific objectivity and societal usefulness.

    The results from the 2024 election cycle aligned closely with the 2020 data. Reading the political endorsements decreased general trust in science and increased the belief that personal and political values govern scientific research. Participants in the treatment group also reported lower confidence in the idea that science is objective and useful for society. Once again, the declines in general trust and perceived integrity were most pronounced among moderate and conservative respondents.

    The study relies entirely on real-world editorials that endorsed Democratic candidates or criticized Republican ones. Because the researchers used actual published materials to ensure their experiment mirrored reality, they did not test how left-leaning individuals might react to a major scientific journal endorsing a conservative candidate. It remains unknown if political liberals would exhibit the same motivated reasoning and subsequent loss of trust if faced with scientific endorsements that opposed their own political identities.

    The researchers note that while explicit political endorsements carry reputational costs, complete silence from the scientific community on policy matters might also negatively affect public perception. Choosing not to address political rhetoric that directly targets scientific funding or spreads false information could be viewed as a failure to defend the scientific enterprise. Future research will need to explore how scientific organizations can correct falsehoods or advocate for evidence-based policies without appearing overly partisan. Finding the right balance will help institutions maintain their legitimacy across the entire political spectrum.

    The study, “Presidential candidate endorsements by scientific journals decrease trust in science especially for moderate and conservative Americans,” was authored by Stylianos Syropoulos, Kyle Fiore Law, Crystal Li, Bernhard Leidner, and Kevin L. Young.

    URL: https://www.psypost.org/political-endorsements-by-scientific-journals-reduce-public-trust-in-research/

    -------------------------------------------------

    Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org

    Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot

    -------------------------------------------------

    #psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #Science #ScientificResearch #PublicTrust #PoliticalEndorsements #ScienceCommunication #Research #Politics #MediaLiteracy #EvidenceBased #PublicHealth

    #psychology #counseling #socialwork #psychotherapy #mentalhealth #psychiatry