“onat” — Fediverse search results on home.social

Mostly #HP desktops & laptops, w/ #MSWindows & #MSOffice.
Some #Apple Macs.
Zero use of CN or free-libre OSes like #UOS, OpenEuler, #HarmonyOS for PCs etc.
Seems #Huawei uncompetitive ATM with HP for their requirements.
One recent IT sovereignty action: replaced US HR #SaaS supplier with CN one. Felt employee data too sensitive to be in hands of foreign company.
LLMs: various self-hosted CN models.
Communications: Feishu (Lark, CN), Weixin (WeChat, CN)
As far as they know, no company plans or discussion ATM to migrate away from HP, Windows, Mac, MS Office etc.
Re the future, they feel it depends on:
- US-CN relationship: better? worse?
- Speed of CN's own tech development.
- Price. It's business, so price will always be a key factor.

PHONE

Huawei w/ Harmony OS.
Personal choice, not company issue.
Reasons:
#iPhone failed on biz trips to very cold places (N. China in winter, -20°C): would turn on for only 1-2 seconds before turning itself off, or wouldn't turn on at all.
iPhone's poor/zero signal strength below ground, e.g. shopping centres, parking. Friends/colleagues w/Huawei right next to them with more bars & no connection problems.
Celebrity iCloud leaks made them consider personal cloud security & #DataSovereignty ('are US companies making money off me & my data, & not even protecting it to boot?')
Used to be a regular iPhone buyer, then a few years ago won company prize of a mobile phone with choice of iPhone or Huawei. For above reasons, chose Huawei & has stayed with Huawei for subsequent purchases. Still thinks iPhone more beautiful UI & better photos, but happier with Huawei's greater reliability & IT sovereignty.

#openeuler #linux #china #itsovereignty #hp #mswindows

Players' Patchwork Theatre Co @[email protected]

2026-10-23

We just had to get our HEX on at Critical Hit Games in Cleveland Heights before their big move to the Coventry neighborhood staring this week! Each hex supports the move and the shop has supported the geeks of the Cleveland area for many years!

(Yes, we are aware we goofed at sketching our logo art; we do tell you we're "Confused" for a reason!)

*This post is not sponsored by Critical Hit. They are are a community asset and supportive of many geeky groups in the Cleveland area. They are also friends of the troupe and one of their founders had previously been a Player of the Patchwork!

#Theater #Improv #Improvisation #Commedia #CommediaDellArte #Mimic #DnD #DungeonsAndDragons #BoardGames #Gaming #CriticalHit #CriticalHitGames #ShopSmall #ClevelandHeights #Cleveland #CLE

#theater #improv #improvisation #commedia #commediadellarte #mimic

Denver Broncos @[email protected]

2026-10-24

NFL fullbacks scarce but Broncos’ Adam Prentice presses on

At some point there might be a museum display, and behind glass it will read “fullback.” There was…
#NFL #DenverBroncos #Denver #Broncos #AdamPrentice #BrandonJones #Football #JaylenWaddle #JustinStrnad #RileyMoss #SeanPayton #TalanoaHufanga
https://www.rawchili.com/nfl/1035995/

#talanoahufanga #seanpayton #rileymoss #justinstrnad #jaylenwaddle #football

Mike @mikestreety

2026-10-25

RE: https://fosstodon.org/@dantleech/117501478686180059

TIL Packagist protects the vendor once a package exists - you need to be a maintainer on at least one published package with that vendor to publish more

Dev Community @[email protected]

2026-10-25

Most businesses know how to track their Google rankings.

But what happens when a potential customer stops searching on Google and starts asking ChatGPT, Perplexity, or another AI assistant which product they should choose?

Your website might rank well. Your content might get traffic. Your competitors might even have fewer backlinks than you.

Yet when a customer asks an AI assistant for recommendations, your competitors appear while your brand is nowhere to be found.

That creates a new visibility problem: which questions are you losing in AI search?

I'm building Aurvikon to help answer that question.

The problem with measuring AI visibility

Traditional SEO gives us familiar metrics:

Keyword rankings
Impressions and clicks
Organic traffic
Backlinks
Search performance

These metrics remain valuable. But they don't fully explain how your brand appears inside AI-generated answers.

Imagine someone asking an AI assistant:

What are the best tools for improving AI search visibility?
Which platforms help SaaS companies monitor their brand in AI answers?
Compare three alternatives for tracking brand recommendations in AI search.
Which tool should a startup use to understand its visibility in ChatGPT?

Your brand might appear in one answer and disappear from the next.

A competitor might be recommended repeatedly. Another company might be described as the category leader. Your own product might be missing entirely.

Looking at a single AI-generated answer won't tell you the whole story.

You need to understand visibility across the questions your potential customers actually ask.

The shift: from keyword rankings to question-level visibility

I'm interested in a more useful way to think about AI search visibility.

Instead of asking only:

"Does my brand appear in AI search?"

Ask:

"For which relevant buyer questions does my brand appear, where do competitors appear instead, and what can I do about it?"

That second question leads to much more actionable work.

Consider three possible findings from an AI visibility audit:

1. You're missing from important questions.

People ask questions directly related to your product category, but the AI response doesn't mention your company.

2. Your competitors are being recommended instead.

Your product may be relevant, but competing brands are consistently appearing in the answers you're trying to win.

3. Your brand appears, but not in the way you want.

An AI response might mention your company without accurately communicating its core use case, differentiator, or value.

These are different problems. They shouldn't all receive the same recommendation to "publish more content."

What we're building with Aurvikon

Aurvikon is an AI visibility tool focused on helping businesses understand how their brands appear across AI answer platforms.

The core idea is straightforward:

Identify the questions where your brand is losing visibility, understand what appears instead, and turn those findings into an action plan.

A practical workflow looks like this:

Step 1: Identify the questions buyers ask

Start with questions your target customers might ask before choosing a product.

Don't limit the research to your brand name. Include category searches, comparisons, alternatives, use cases, and purchasing decisions.

Step 2: Test those questions across AI platforms

Run relevant questions across the platforms you want to monitor, such as ChatGPT, Perplexity, and Gemini.

Treat the responses as observations to analyze, not as permanent rankings.

Step 3: Identify where you're losing

Look for patterns:

Which questions mention your brand?
Which questions mention competitors but not you?
Where are you missing from relevant comparisons?
Which product capabilities or use cases aren't being communicated?
Which questions deserve attention first?

This is where an audit becomes more useful than a collection of screenshots.

Step 4: Turn findings into actions

Every visibility gap should lead to a hypothesis.

Maybe a product page doesn't explain a use case clearly. Maybe your comparison content is weak. Maybe your product lacks supporting content for a particular buyer question.

Investigate the evidence, make the relevant improvement, and test again.

The goal isn't to manufacture mentions. It's to make your brand easier to understand, evaluate, and recommend when it genuinely fits the user's needs.

The difficult part isn't generating an AI visibility report

AI answers change. Results can vary by wording, location, model version, and time.

That means a report saying "your brand was mentioned" is only a starting point.

A useful system should help you move from observation to diagnosis:

Buyer question → AI response → competitor comparison → visibility gap → action → retest.

That repeatable workflow is the problem space we're focused on at Aurvikon.

We're especially interested in making the results useful to founders and marketing teams who need to decide what to fix next, rather than simply collecting another dashboard of numbers.

What this means for SaaS founders

If you're building a SaaS company, think about the questions someone would ask immediately before buying your product.

Not just:

"What is [your brand]?"

But:

What is the best alternative to [competitor]?
Which tools solve [specific customer problem]?
Compare products that offer [important capability].
What should a small business use for [desired outcome]?
Which platform is best for [specific use case]?

These questions reveal how AI assistants represent your category and which products they surface for potential buyers.

They can also reveal gaps in your positioning and content strategy.

AI visibility isn't a replacement for SEO. It's an additional area to measure as customers discover products through AI-generated answers.

I'm building Aurvikon around one practical question

I believe the most useful starting point for AI visibility isn't another generic score.

It's knowing which valuable questions your company is losing, which competitors show up instead, and what you should investigate next.

That's the problem we're working on with Aurvikon.

I'd love to hear from other founders, SEO professionals, and SaaS marketers:

If you could see every important buyer question where AI assistants recommend your competitors instead of you, what would you want the tool to tell you first?

Would you prioritize the competing brands, the missing content, the sources behind the answers, or the specific actions most likely to improve visibility?

I'm interested in how people are approaching this problem in practice.#ai #seo #startup #showdev #software #coding #development #engineering #inclusive #community
Your Brand Can Rank on Google and Still Be Invisible in AI Search

#ai #community #software #coding #development #engineering

ROllerozxa @rollerozxa

2026-10-22

A (likely not exhaustive list) of Principia's current platform support:

- Windows has always been supported, but the open source builds have generally only supported Windows 7+. However I made a custom toolchain building everything from the ground up to create separate builds that runs on Windows XP again.
- Android has always been supported, but the FOSS builds haven't supported anything <4.0. A FOSS build that runs on at least Gingerbread would be cool but I'm generally burnt out on Android stuff.
- Linux support was one of the first things I worked on when the source code released, the original devs were all Linux users but I worked on getting that into a more usable state for end-users (like not depending on Valgrind to run & such...). Builds with GCC or Clang, runs on glibc or musl, have gotten it running on a Raspberry Pi as well as on Nura/postmarketOS with configurable touch support from the Android version.
- I ported Principia to Haiku OS, but haven't been able to get Haiku on real hardware yet
- I ported Principia to macOS with a VM, also set up CI to build it too but I don't have any real Apple hardware to test with
- I ported Principia to the web browser and integrated it into the site so you can conveniently create levels in the sandbox or play levels from the community site in your web browser
- I ported Principia to the Nintendo Switch with devkitPro, but their SDL3 is a bit unfinished and I haven't gotten further along with that. I also don't have a homebrewed Switch either.
- I recently got Principia to compile for iOS again in a VM but doesn't render in iOS sim yet. There's also a iOS slopfork from someone else that's further along but we don't talk about that one.

Principia is extremely portable with little dependencies, I replaced the old build system with a unified CMake build system to make it easier to build for different platforms, and I have managed to get rid of stuff like GTK3 and replacing them with Dear Imgui-based dialogs, but the main limiting factor at this point tends to be OpenGL 2.1 / ES 2.0 and SDL3.

Big endian support feels like the only low-hanging fruit left, as I believe there are parts of the codebase that are currently not endian safe and warn about it in our porting doc.

Nelson Lopez @[email protected]

2026-10-22

testing out tokodon in this weddy instance(tm)

i am liking it a bit more than tuba :neofox_base: and it has a :neofox_dogmask: custom emoji pick:neofox_legs:er

it's a bit slow but it's less slow than tuba for whatever reason. I wonder why is it that both QT and GTK are so bad at dynamically offloading image loading and stuff like that, it just kind of blows up when you have a lot of stuff going on at once

#kde

Dev Community @[email protected]

2026-10-23

Preventing duplicate customer messages when background jobs retry.

Push notifications are not financial ledger entries, but duplicates still damage trust. A customer should not receive the same failure alert three times because a worker retried, nor should two scheduler processes send the same campaign simultaneously.

Task queues normally provide at-least-once execution. Notification systems must design around that fact.

Claim the campaign before sending

Two workers can pick up the same scheduled campaign. Reading its status and then updating it is vulnerable to a race.

Lock the campaign and transition it to sending inside one database transaction:

with database_transaction():
campaign = Campaign.objects.select_for_update().get(id=campaign_id)

if campaign.status not in {"draft", "queued", "scheduled"}:
return

campaign.status = "sending"
campaign.save()

Only the worker that successfully claims the campaign proceeds.

Deduplicate recipients by delivery destination

A user may have duplicate device records, or the same token may appear in customer and merchant contexts. Build the target list from active devices, validate token format, and retain one target per actual push token.

Give each delivery a deterministic identity

Create a non-sensitive delivery key from the campaign and device token:

delivery_key = sha256(f"{campaign_id}:{device_token}".encode()).hexdigest()

Store one delivery record per campaign and key under a unique database constraint. Create that record before calling the push provider.

If a duplicate task finds the record, it can inspect the existing status rather than sending again.

Record actual provider outcomes

Queued does not mean sent. The delivery record should distinguish pending, accepted, and failed outcomes and retain a safe error message.

Campaign totals can then be calculated from delivery rows rather than optimistic task counts.

Handle partial failure

One invalid device token should not abort an entire campaign. Each delivery is an independent attempt, while the campaign summarizes the results.

If the campaign-level task crashes, move the campaign out of a permanent sending state so operations can inspect or retry it safely. Existing delivery keys prevent already-sent targets from receiving the message again.

The design principle

Exactly-once delivery cannot be guaranteed across every external push platform, but the application can guarantee that it submits each campaign-device pair at most once under its own retry model.

That requires transactional campaign claiming, target deduplication, deterministic delivery identities, and persistent per-device outcomes.#architecture #backend #database #softwareengineering #software #coding #development #engineering #inclusive #community
Exactly-Once Push Notifications on At-Least-Once Workers

#database #community #software #coding #architecture #development