#productmanagement — Public Fediverse posts

Anthropic's latest Risk Report is a sobering look at the friction between rapid AI scaling and safety. It’s rare to see such transparency regarding internal failures, from CoT leakage to training on poisoned data. We must move beyond "safe zones" in monitoring.

Read the full analysis: https://thezvi.substack.com/p/anthropic-risk-report-august-2026

#AI #ProductManagement

Anthropic's latest Risk Report is a sobering look at the friction between rapid AI scaling and safety. It’s rare to see such transparency regarding internal failures, from CoT leakage to training on poisoned data. We must move beyond "safe zones" in monitoring.

Read the full analysis: https://thezvi.substack.com/p/anthropic-risk-report-august-2026

#AI #ProductManagement

Anthropic's latest Risk Report is a sobering look at the friction between rapid AI scaling and safety. It’s rare to see such transparency regarding internal failures, from CoT leakage to training on poisoned data. We must move beyond "safe zones" in monitoring.

Read the full analysis: https://thezvi.substack.com/p/anthropic-risk-report-august-2026

#AI #ProductManagement

Anthropic's latest Risk Report is a sobering look at the friction between rapid AI scaling and safety. It’s rare to see such transparency regarding internal failures, from CoT leakage to training on poisoned data. We must move beyond "safe zones" in monitoring.

Read the full analysis: https://thezvi.substack.com/p/anthropic-risk-report-august-2026

#AI #ProductManagement

Anthropic's latest Risk Report is a sobering look at the friction between rapid AI scaling and safety. It’s rare to see such transparency regarding internal failures, from CoT leakage to training on poisoned data. We must move beyond "safe zones" in monitoring.

Read the full analysis: https://thezvi.substack.com/p/anthropic-risk-report-august-2026

#AI #ProductManagement

Pondering invisible bottlenecks and delays

Looking for a job is different to working in an organisations with many teams.

For one thing looking for a job is more boring than having a job. For another thing, my side of the job matching is visible, while the “hiring person” side is basically invisible.

I can see if I look at a role and then postpone applying and even though a day might slide by, I can see that the bottle next was me. I cannot see whether someone read my resume or discussed it internally or much of anything else.

This impacted my “quick cycle times lead to quick learning” because I can fire off a resume and hear nothing back, or I can hear back a couple of weeks later. So I improve my online profile and the information I submit for jobs with no feedback from real customers.

That is the opposite of continuous discovery and good product management but is also a factor of the constraints of my current market. Of course calling it a market when I have one product (me or the services I can offer) and a few potential hirers is probably a stretch, but the principles of product management apply.

I could innovate with the product by offering to work as an interim executive, a volunteer, a part-timer, a contract or permanent. I could add features to my offering by doing a course in governance or learning to be a hit man. I could do a lot to tweak what is on offer and I should prioritise that.

Interim executive is a good idea, governance training will not likely improve my time to the next role but it would add value in the long run. Hit-man qualifications are probably not going to enhance the value of a delivery manager, unless I change my target market to “illegal mafia like organisations and international espionage”.

What I was thinking though – is that nearly everything on my side is visible to me and that is a real luxury compared to working as part of a system.

Even the invisible bits can be tackled. If I want to improve my resume I can fire it off to many organisations and hear nothing, or I could share it with friends who work in the industry and get real feedback from these “proxies for the customer”, because they, like I, have hired for similar roles that I would apply for.

But in a real job, you often wait for feedback, wait for permission, wait for work to get done and generally depend on others. In this situation you can get really busy, but the activity will not move things along if you are waiting for some input or decision.

So you get good at managing dependencies, stakeholders and change. It is a real skill that comes with experience but can almost be invisible.

Of course you can “get good” at managing dependencies by harassing people mercilessly, but that strategy is both less fun and less effective than it sounds.

On TV, leaders are often very demanding and they get all the resources they need because they demand them. They also tackle drama head on and keep moving at a pace that keeps the audience engaged.

In the real world, asking for people to swarm onto your dependency is less likely to succeed when there are many more dependencies for them to manage, with their own dependencies to manage and many more annoying stakeholders asking for urgent attention.

So a real skill is to know when focusing on something will increase the speed and quality and when it is better to let things take their course.

I guess that seems like a vague statement, but they say you don’t appreciate something until you miss it or lose it. In this case I think I don’t see the challenge until I am in a simpler environment with few dependencies and a product I build myself without needing much negotiation with others.

So sitting hear next to the trees in my backyard, I can operate at my own sustainable pace. But the real thing I realise is that in a complex working environment, not everything is visible and the lack of that visibility has a real impact.

It is quite easy to “see” a bottleneck and focus on it. But generally you are seeing the symptom of a bottleneck and not the real cause, or sometimes not even the real bottleneck.

For example, at my last company, code reviews took a long time. So doing faster code reviews with AI would seem like a good idea. But in fact it was not the time spent on the code review that was an issue, it was the scarcity of experienced people who understood the code.

So getting more people experienced with the code seems like a good idea and it probably is.

But there are a couple of problems with that. Firstly the desire to use a tool or process to fix things – “Use AI to make it faster” – can actually be a distraction. Getting people to pull experienced technical people into meetings to decide whether to make AI code reviews better makes them more scarce on the ground. Doing that might cause them to take longer to go to a code review and make it harder to find time to mentor others to increase the people who can review code.

Of course, using AI to improve code reviews is the way to go and things like telemetry and automated checking will improve both quality and time spent on manual reviews. But it won’t in itself make senior staff more available.

So what might make the crew more available is better delegation, better decisions rights or more focused discussions when the crew do get together.

But then, what if the problem is not just scarcity of gurus? And what if the improvement or decay in our cycle time is the result of a change we made a month or two ago.

Guru scarcity will increase if we have a lot of turn-over but should reduce over time if we have stable teams and good senior staff who spend time coaching others. Even having people fix bugs will add to their understanding and reduce the overhead of code reviews. So we could see improvements now that are the result of one good tech lead creating stability in the team because people enjoy learning from her.

That change occurred a while ago, then people realised and then their skill increased and then we saw the improvement. Similarly the use of AI in code reviews might initially not have a visible impact and then a few weeks later it might be having a massive impact, but people are not mentioning it because it is obvious.

Or the code reviews are taking a long time because in fact the engineer was making “dumb assumptions” because they did not understand the way the customer used the product and the guru sent them back to ask questions of the PO and then make changes. If this happens then the delay in code reviews happens twice every story (or code package). And it might be the result of poor information coming into the team, which is fixed by neither the use of AI or the increased availability of coding gurus.

So I guess the conclusion is that, while AI is revolutionising the way we build products, there are skills and attitudes that still matter a lot. And the more complex the environment the more they matter.

The problem is though, the same as it was a hundred years ago. People fix and improve what they see and when they see a change they often assume that they understand the cause, when they are only looking at a symptom.

I don’t think I can put “take time to notice things and has a knack for finding invisible stuff” on my resume.

But I can say that it is a requirement of many senior product and engineering roles. It is part of the joy of the work and also part of the invisible value that motivated and experienced people can add.

So if it is not a resume thing, what is it?

Some of it is boring process and habit management. Making things visible, being transparent and looking at the system are all ways that uncover previously invisible delays and bottlenecks.

Part of it is also curiousity. There is an Irish saying, or at least a saying I was told is Irish – “If you fall over, don’t look where you landed, look back at what caused you to trip”.

We could say that it is moving upstream or shifting left, but it is really as simple as remaining curious. Instead of acting on the symptom you see, you pause and ask how it came about.

More often than not, the slow moving tech lead who is not getting to code reviews is not actually a slow moving tech lead not bothering to look at code. It is a person in a system with many forces creating the existing situation.

And the better you get at finding where the hidden things are the better. It is often the time to make a decision that delays the implementation. It is often the distraction and not the work itself that is a delay. And it is often a lack of access to the right information or resources that causes the delay and the rework.

That kind of sounds obvious when you sit back next to a tree and ponder. But the art comes in paying attention and creating space to notice and ponder things when being pulled in 20 different decisions while multiple important things compete for attention.

`

Why Most AI POCs Stall and How to Build an AI Operating Model That Works

https://bhavingandhi.com/2026/08/26/why-most-ai-pocs-stall-and-how-to-build-an-ai-operating-model-that-works/

The Minimum Viable Unit of Saleable Software

https://brandur.org/minimum-viable-unit

#HackerNews #minimumviableproduct #softwaredevelopment #startupideas #productmanagement #agilemethods

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#MentalModels #BusinessStrategy #LeadershipDevelopment #CriticalThinking #HardwareStartups #StrategicPlanning #ExecutiveCoaching #DecisionMaking #SystemsThinking #ProductManagement (1/1)

Microsoft’s “Microslop” Discord Ban Backfires: What AI Builders Can Learn from This Epic Moderation Fail

2,644 words, 14 minutes read time.

The “Microslop” Catalyst: When Automated Moderation Becomes a PR Liability

The recent escalation on Microsoft’s official Copilot Discord server serves as a stark reminder that in the high-stakes world of generative AI, the community’s perception of quality is as vital as the underlying architecture itself. In early March 2026, what began as a routine effort to maintain decorum within a product-support hub rapidly spiraled into a live case study of the Streisand Effect. Reports from multiple industry outlets confirmed that Microsoft had implemented a blunt, automated keyword filter designed to silently delete any message containing the term “Microslop.” This derogatory portmanteau has been increasingly used by developers and power users to describe what they perceive as low-quality, intrusive, or “sloppy” AI integrations within the Windows ecosystem. While the corporate intent was likely to prune what a spokesperson later categorized as “coordinated spam,” the execution triggered a tidal wave of digital civil disobedience. Instead of silencing the critics, the automated system provided a focal point for them, validating the sentiment that the tech giant was more interested in brand preservation than addressing the technical grievances that birthed the nickname.

Analyzing the root of this frustration reveals that the term “slop” is often an emotional reaction to a very real technical burden placed on the developer community. For instance, attempting to upgrade a SharePoint Framework (SPFx) project from version 1.14.x to the recently released 1.22.x is frequently described by those in the trenches as a “blood bath” of error messages and cryptic warnings. The transition is not merely a version bump; it is an overhaul of the build toolchain that often leaves developers debugging deep-seated errors that appear to stem from AI-generated or “slop-induced” bugs within M365 and community plug-ins. When a developer spends three days chasing an error only to find it buried in a low-quality, automated code suggestion or a poorly integrated community tool, the “Microslop” label stops being a joke and starts being an accurate description of a broken workflow. This disconnect between Microsoft’s “AI-first” marketing and the gritty, error-prone reality of its development frameworks is precisely why a simple keyword filter was never going to be enough to contain the community’s mounting resentment.

The Streisand Effect: How Censorship Becomes a Signal

The failure of the “Microslop” ban is a textbook example of how heavy-handed moderation can amplify the very information it seeks to suppress. In the context of AI builders, this incident highlights the danger of using automated tools to sanitize discourse, as it inadvertently creates a “badge of resistance” for the user base. Every bypassed filter and every subsequent ban on the Copilot Discord became a signal to the broader industry that there was a significant rift between Microsoft’s narrative of AI “sophistication” and the community’s lived experience with the product. Furthermore, by escalating from keyword filtering to a full server lockdown, Microsoft effectively confirmed the power of the “Microslop” label. This elevated the term from a minor annoyance to a headline-grabbing symbol of corporate insecurity, demonstrating that the more a corporation tries to hide a piece of information, the more the public will seek it out and amplify it.

This phenomenon is particularly dangerous for AI-centric companies because the technology itself is already under intense scrutiny for its reliability and ethical implications. If a builder cannot manage a community hub without resorting to blunt-force censorship, it raises uncomfortable questions about how they manage the more complex, nuanced guardrails required for the Large Language Models (LLMs) themselves. The internet rarely leaves such attempts at suppression unpunished; in this case, the ban led to the creation of browser extensions and scripts specifically designed to spread the nickname across the web. This demonstrates that in 2026, community management is no longer just an administrative task; it is a critical component of brand integrity that requires a much more sophisticated approach than a simple “find and replace” blocklist. Builders must recognize that transparency is the only effective dampener for the Streisand Effect, as any attempt to use automation to hide dissatisfaction only serves to validate the critics.

Why the “Slop” Narrative Resonates: The Technical Quality Gap

At the heart of the “Microslop” controversy lies a deeper, more substantive issue regarding the growing perception that AI integration has entered a period of diminishing returns, often referred to as the “slop” era. The term “slop” gained significant cultural weight after major linguistic authorities and industry analysts began using it to specifically define the flood of low-quality, mass-produced AI content clogging the modern internet. When users apply this term to a tech giant, they are not merely engaging in schoolyard insults; they are expressing a technical frustration with the way generative AI features have been integrated into a legacy operating system. Analyzing the user feedback leading up to the Discord lockdown reveals a clear pattern of “quantity over quality” in the deployment of Copilot. Developers and power users have documented numerous instances where AI components were perceived as being forced into core OS functions like Notepad, File Explorer, and Task Manager, often at the expense of system latency and overall stability.

This quality gap is precisely what gave the “Microslop” nickname its viral potency, as it hit upon a verifiable truth regarding the current state of the software. If the AI integration were universally recognized as seamless, high-value, and technically flawless, the derogatory label would have failed to gain traction among the engineering community. However, because the term captured a widespread sentiment that the software was becoming bloated with unrefined, “sloppy” code that prioritizes corporate AI metrics over actual user utility, the attempt to ban the word felt like an attempt to ban the truth itself. For AI builders, this serves as a critical warning that one cannot moderate their way out of a fundamental quality problem. If a community begins to categorize a product’s output as “slop,” the correct response is not to update the server’s AutoMod settings to include the word on a prohibited list; the solution is to re-evaluate the product roadmap and address the technical regressions causing the friction.

Root Cause Analysis: The Failure of Brittle Automation in Community Governance

The technical root cause of the Discord meltdown can be traced back to the implementation of “naive” or “brittle” automation—a common pitfall for organizations that treat community management as a purely administrative task. Microsoft’s moderation team relied on a basic fixed-string match filter, which is the mos

Furthermore, the automation failed to account for context, which is the most vital component of any successful moderation strategy. The bot reportedly flagged every instance of the word “Microslop,” regardless of whether the user was using it as an insult, asking a question about the controversy, or providing constructive criticism. By labeling a corporate nickname with the same “inappropriate” tag usually reserved for hate speech or harassment, the automated system actively insulted the intelligence of the user base. This lack of nuance in the AI-driven moderation stack created a pressure cooker environment where every automated deletion was viewed as an act of corporate censorship. For AI builders, the lesson is that any automation deployed for community governance must be as sophisticated as the product it supports. Relying on 1990s-era keyword filtering to manage a 2026-era AI community is a recipe for disaster, as it signals a lack of technical effort that only further reinforces the “slop” narrative the organization is trying to escape.

The Strategic Shift: Moving Beyond Blunt Force Suppression

The failure of the “Microslop” ban highlights a critical strategic inflection point for AI builders who must navigate the increasingly volatile waters of developer communities. Relying on blunt-force suppression as a first-line defense against product criticism is a strategy rooted in legacy corporate communication models that are incompatible with the transparent, decentralized nature of modern technical hubs. When a tech giant attempts to scrub a derogatory term from its digital ecosystem, it effectively abdicates its role as a collaborator and assumes the role of an adversary. This shift in posture is particularly damaging in the context of generative AI, where the success of a platform like Copilot is heavily dependent on the feedback loops and integrations created by the very developers who feel alienated by such heavy-handed moderation. Instead of viewing these “slop” accusations as a nuisance to be silenced, sophisticated AI organizations should view them as high-fidelity data points indicating where the gap between marketing hype and functional utility has become too wide to ignore.

Consequently, the move toward resilient community management requires a transition from “policing” to “pivoting.” Analyzing the fallout from the March 2026 lockdown reveals that the most effective way to neutralize a pejorative nickname is to address the technical deficiencies that gave the name its power. For instance, if users are labeling an AI integration as “slop” due to high latency, resource bloat, or inconsistent output, the strategic response should involve a public-facing commitment to performance benchmarks and a transparent roadmap for optimization. By engaging with the substance of the criticism rather than the semantics of the label, a builder can naturally erode the legitimacy of the mockery. Microsoft’s decision to hide behind a locked Discord server suggests a lack of preparedness for the “friction” that inevitably accompanies the rollout of transformative technologies. To avoid this pitfall, builders must ensure that their community teams are empowered with technical context and the authority to translate community outrage into actionable product requirements, rather than being relegated to the role of digital janitors tasked with sweeping dissent under the rug.

Building Resilience: Lessons in Context-Aware Governance

For AI startups and established enterprises alike, the “Microslop” debacle provides a definitive masterclass in the necessity of context-aware governance. The primary technical takeaway is that community moderation in 2026 must be as intellectually rigorous as the models being developed. A sophisticated governance stack would utilize sentiment analysis and intent recognition to differentiate between a user engaging in harassment and a user expressing a legitimate, albeit sarcastically phrased, grievance. By failing to integrate these more nuanced AI capabilities into their own moderation tools, Microsoft inadvertently signaled a lack of confidence in the very technology they are asking the world to adopt. If an AI leader cannot trust its own systems to handle a Discord meme without resorting to a total server blackout, it becomes significantly harder to convince enterprise clients that the same technology is ready to handle mission-critical business logic or sensitive customer interactions.

Furthermore, building a resilient community requires a fundamental acceptance of the “ugly” side of product development. In the age of social media and rapid-fire developer feedback, mistakes will be memed, and failures will be christened with catchy, derogatory nicknames. Attempting to legislate these memes out of existence is a losing battle that only serves to accelerate the Streisand Effect. Instead, AI builders should focus on creating “high-trust environments” where users feel that their feedback—no matter how unpolished or “sloppy” it may be—is being ingested as a valuable resource. This involves maintaining open channels even during a PR crisis and resisting the urge to implement “emergency” filters that treat your most vocal users like hostile actors. By prioritizing stability, transparency, and technical excellence over brand hygiene, organizations can transform a potential “Microslop” moment into a demonstration of corporate maturity and a commitment to long-term product quality.

From Damage Control to Product Discipline: Reclaiming the Narrative

The ultimate fallout of the Microsoft Discord lockdown serves as a definitive case study in why AI builders must prioritize technical discipline over narrative control. When a corporation attempts to “engineer” a community’s vocabulary through restrictive automation, it inadvertently signals a lack of confidence in the underlying product’s ability to speak for itself. Analyzing the broader industry trends of 2026, it becomes clear that the “slop” label is not merely a social media trend but a technical critique of the current state of LLM integration. For a developer audience, the transition from “Microsoft” to “Microslop” in common parlance was a direct reaction to perceived regressions in software performance and the intrusion of non-essential AI telemetry into stable workflows. By focusing on the removal of the word rather than the remediation of the code, Microsoft missed a critical opportunity to demonstrate the “sophistication” that CEO Satya Nadella has publicly championed. Builders must realize that in a highly literate technical ecosystem, the only way to effectively kill a derogatory meme is to make it irrelevant through superior engineering and undeniable user value.

Furthermore, the “Microslop” incident underscores the necessity of a unified strategy between product engineering and community management. In many large-scale tech organizations, these departments operate in silos, leading to situations where a community manager implements a blunt-force keyword filter without realizing it contradicts the broader corporate message of AI-driven nuance and intelligence. This strategic misalignment is what allowed a minor moderation decision to balloon into a global PR crisis that dominated tech headlines for a week. To build a resilient AI brand, organizations must ensure that their automated governance tools are reflective of their core technological promises. If your product is marketed as an “intelligent companion,” your moderation bot cannot behave like a primitive 1990s-era blacklist. Moving forward, the industry must adopt a “feedback-first” architecture where automated tools are used to categorize and elevate user frustration to engineering teams, rather than acting as a digital firewall designed to protect executive sensibilities from the harsh reality of user sentiment.

Conclusion: The Lasting Legacy of the “Slop” Era

The March 2026 Discord lockdown will likely be remembered as the moment “Microslop” transitioned from a niche joke to a permanent fixture of the AI era’s vocabulary. Microsoft’s attempt to use automated moderation as a shield against criticism backfired because it ignored the fundamental law of the digital age: the more you try to hide a grievance, the more you validate its existence. For those of us building in the AI space, the lessons are clear and uncompromising. We must build with transparency, moderate with context, and never mistake a blunt-force keyword filter for a comprehensive community strategy. If we want our products to be associated with innovation rather than “slop,” we must earn that reputation through technical excellence and genuine engagement, not through the silent deletion of our critics’ messages. In the end, Microsoft didn’t just ban a word; they inadvertently launched a movement, proving that even the world’s most powerful tech companies remain vulnerable to the power of a well-timed, nine-letter meme and the undeniable force of the Streisand Effect.

Call to Action

If this breakdown helped you think a little clearer about the threats out there, don’t just click away. Subscribe for more no-nonsense security insights, drop a comment with your thoughts or questions, or reach out if there’s a topic you want me to tackle next. Stay sharp out there.

D. Bryan King

Sources

• PCMag: Microsoft Effort to Ban ‘Microslop’ on Copilot Discord Didn’t Go As Planned
• Windows Latest: Microsoft Locks Copilot Discord After Moderation Backlash
• Futurism: Microsoft Bans “Microslop” on Discord, Gets So Humiliated It Locks Server
• Gizmodo: Microsoft Bans Term ‘Microslop’ From Official Discord Server
• PC Gamer: Microsoft banned the word ‘Microslop’ in its Copilot Discord server
• It’s FOSS: Microsoft Locks Down Discord Server Over “Microslop” Posts
• Slashdot: Microsoft Bans ‘Microslop’ On Its Discord, Then Locks the Server
• Ground News: Microsoft Locks Down Discord Server After Microslop Ban Backfires
• Mysterium VPN: Microsoft Banned “Microslop” on Discord, Then Panicked
• Kotaku: Flood Of ‘Microslop’ Messages Forces Microsoft’s Official Copilot AI Discord Into Lockdown
• WinBuzzer: Microsoft Bans ‘Microslop’ on Discord, Locks Server After Backlash
• NIST: AI Risk Management Framework
• CISA: Secure by Design Principles for AI

Disclaimer:

The views and opinions expressed in this post are solely those of the author. The information provided is based on personal research, experience, and understanding of the subject matter at the time of writing. Readers should consult relevant experts or authorities for specific guidance related to their unique situations.

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And it can't be disabled. Do better #Microsoft.

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#tomverrilli #twitch #twitter #chiefproductofficer #productmanager #productmanagement

A great product manager is a great storyteller by Tom Verrilli

Main Site: https://www.analyse.asia/the-art-of-product-management-with-tom-verrilli/
Full YouTube Video: https://youtu.be/hYsJ0qzyM4g
Newsletter Signup: https://www.analyse.asia/#/portal/signup
LinkedIn Page: https://www.linkedin.com/company/analyse-asia

#tomverrilli #twitch #twitter #chiefproductofficer #productmanager #productmanagement

I kinda went on a rant: https://open.substack.com/pub/paninid/p/organizational-information-gain?r=4hxgy&utm_medium=ios&utm_campaign=post

#informationgain #decisiontrees #values #priorities #systemsthinking #productmanagement #strategy #CX #UX #masspersonalization #GenerativeAI #collaboration #platform #networkeffects #SaaS #communication #socialmedia #customersuccess #processoptimization #employeeengagement #servicedesign #LLMs #cashflow #psychologicalsafety #emotionalintelligence #ambiguity #productmarketfit #backpropagation #machineaugmented #digitaltransformation

Your literary exercise today is John Houbolt’s letter to Robert Seamans, “Manned Lunar Landing Through Use of Lunar Orbit Rendezvous”.

The good shit starts at page 55 in this NASA archive document. So good.

https://ntrs.nasa.gov/api/citations/19960014824/downloads/19960014824.pdf

Also, Houbolt went to Joliet. Mfers you need to hire more Southsiders.

#HotRobotContent #Engineering #ProductManagement #ApolloProgram #FuckYeah #SouthSideChicago

Your literary exercise today is John Houbolt’s letter to Robert Seamans, “Manned Lunar Landing Through Use of Lunar Orbit Rendezvous”.

The good shit starts at page 55 in this NASA archive document. So good.

https://ntrs.nasa.gov/api/citations/19960014824/downloads/19960014824.pdf

Also, Houbolt went to Joliet. Mfers you need to hire more Southsiders.

#HotRobotContent #Engineering #ProductManagement #ApolloProgram #FuckYeah #SouthSideChicago

Your literary exercise today is John Houbolt’s letter to Robert Seamans, “Manned Lunar Landing Through Use of Lunar Orbit Rendezvous”.

The good shit starts at page 55 in this NASA archive document. So good.

https://ntrs.nasa.gov/api/citations/19960014824/downloads/19960014824.pdf

Also, Houbolt went to Joliet. Mfers you need to hire more Southsiders.

#HotRobotContent #Engineering #ProductManagement #ApolloProgram #FuckYeah #SouthSideChicago

One sees many references to the conscious decision by @Gargron to not include in Mastodon any algorithm that selects which posts you'll see on your feed.

But Mastodon does have an algorithm that drives how your feed gets populated, however basic.

And I think it can be iterated.

Read my long post at
https://paper.wf/pierric/mastodons-algorithm and react in this thread!

potentially interesting to @productmanagement folks

#ProductManagement #Algorithm #Mastodon #BigSocial #SocialMedia #YourData

Tässä profiilitekstistä hiukan laajennettu #esittely:

#Humanisti-#nörtti #IT-alalla (#softwaredevelopment #productmanagement #qa #testing), entinen #opettaja.

Harrastuksia #sarjakuvat, #pelit (#videopelit, #lautapelit, #roolipelit) ja #musiikki (#kuoro, #piano, #huilu).

Kiinnostuksia myös #tiede, #taide, #kulttuuri, #kielet, #psykologia, #koulutus ja #yhteiskunta.

#Vanhemmat-vertaistuki on hyväksi.