GitHub Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Ed (@Eduardopto) reported 9 minutes ago

  Anthropic is facing a weird feedback loop: users are complaining that Claude’s output quality is nosediving, and Claude itself agrees. The model analyzed its own GitHub repo and confirmed that quality-related issue reports have escalated sharply since January. This decline coincides with Anthropic aggressively throttling capacity during peak hours to manage server load. We are seeing a dangerous trend where infrastructure constraints directly degrade model performance. When you optimize for reliability and cost, the "intelligence" is the first thing to hit the cutting room floor. It’s hard to build robust agentic flows when the base model’s reasoning capability fluctuates based on the time of day if you are building right now, what does this actually unlock or kill?

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  Viksit Gaur (@viksit) reported 10 minutes ago

  @nicoalbanese10 is there a github? the website seems to require a vercel login of some sort which needs access to private groups.

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  NiNE (@AfterThe925) reported 11 minutes ago

  Two weeks ago, deploying an AI agent took a weekend and a GitHub degree. Now: dashboard, click, running. Anthropic handles sandboxing, retries, auth. Platforms handle hosting, integrations, memory. The infrastructure layer is being commoditized in real time. Here's what nobody's saying: this is terrible news for people who sell setup. And great news for everyone else. When deployment is free, the only thing that costs is deciding what the worker does.

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  AnMioLink (@anylink20240604) reported 11 minutes ago

  @weezerOSINT OK, i saw the github issues.

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  Jimmy (@jimmy_toan) reported 13 minutes ago

  Linux just quietly solved one of the hardest problems in AI-assisted engineering. And nobody framed it that way. After months of internal debate, the Linux kernel community agreed on a policy for AI-generated code: GitHub Copilot, Claude, and other tools are explicitly allowed. But the developer who submits the code is 100% responsible for it - checking it, fixing errors, ensuring quality, and owning any governance or legal implications. The phrase from the announcement: "Humans take the fall for mistakes." That's not a slogan. That's an accountability architecture. Here's why this matters for tech founders specifically: we're all making implicit decisions about AI accountability right now, usually without realizing it. 🧵 The question isn't whether your team uses AI to write code. They do, or they will. The question is: who is accountable when it's wrong? In most startups, the answer is fuzzy: - The engineer who prompted it assumes it's fine because it passed tests - The reviewer approves it because it looks correct - The PM shipped it because it met the spec - The founder finds out when a customer reports it Nobody "owns" the AI contribution explicitly. Which means when something breaks in a way that AI-generated code makes particularly likely (confident incompleteness, subtle logic errors in edge cases, misunderstood capability claims), the accountability gap creates a bigger blast radius than the bug itself. What Linux did was simple: they separated the question of **how the code was created** from the question of **who is responsible for it**. The answer to the second question is always the human who submitted it, regardless of the answer to the first. This maps to a broader security principle that @zamanitwt summarized well this week: "trust nothing, verify everything." That's not just a network security policy. Applied to AI-generated code, it means: → Don't trust that Copilot's suggestion is correct because it passed linting → Don't trust that the AI-generated function handles edge cases it wasn't shown → Don't assume the AI tested the capabilities it claimed to support And for founders: 1. **Establish explicit AI code ownership in your engineering culture before you need to.** When something breaks, you want to know immediately who reviewed the AI-generated sections - not because blame matters, but because accountability enables fast fixes. 2. **Zero-trust for AI outputs is not paranoia - it's good engineering.** Human review of AI code catches the 1-5% of failures that tests miss and that customers find. 3. **The liability question is coming for AI-generated code.** Linux addressed it proactively. Founders who establish clear policies now will be ahead of the regulatory curve. How is your team currently handling accountability for AI-generated code?

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  Ashkan (@Ashknz7) reported 15 minutes ago

  @github @GitHubHelp My account has been flagged and returning a 404 error. I raised support ticket #4257826 last Wednesday but no response yet. Could someone please look into this? Thanks.

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  Gajae (@GajaeMode) reported 20 minutes ago

  split-pane shutdown now checks stale leader targeting. GitHub Issues beat vendor support tickets.

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  Krastyo Krastev (@k_krastew) reported 21 minutes ago

  @_Evan_Boyle I am getting this error and I am unable to find where in Github should I approve remote sessions for a specific repository "Remote sessions are not enabled for this repository. Contact your organization administrator to enable remote sessions." Any help?

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  Fabio Paniconi (@paniconi_fabio) reported 25 minutes ago

  @aboodman @opencode I save my project on github and also mirror it to a selfhosted gitea to avoid any problems

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  Faheem B M (@imfahmbm) reported 25 minutes ago

  amd's ai director analyzed 6,852 claude code sessions, 234,760 tool calls, wrote a full github issue anthropic closed it without explaining anything that's one way to handle feedback i guess

• 
  MTu (@Tre_bie) reported 31 minutes ago

  @sisaranger @songjunkr u can use github fix, search it, but only in terminal, lmstudio same , not workin

• 
  Ez.- (@ecura) reported 32 minutes ago

  We've been at it for 3 weeks. 5 contributors. 3 continents. 1 GitHub issue. 0 meetings. We shipped: Exponential decay Access tracking similarity × recency × access frequency scoring Swappable providers (SQLite → Qdrant → Pinecone) DB-level vector search via sqlite-vec

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  Gilfoyle (@FSoyluyor) reported 34 minutes ago

  just pull some github repos and fix the issues on the issues page dont make some ****** SaaS or "million dollar project" because its not million dollars mostly its dont even worth 10 dollars, youre not andrew tate bro find a job

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  SkyDaddysGG (@skydaddysgg) reported 34 minutes ago

  @adamhjk GitHub issue name, description, and comments are becoming Spec, or AI "positive reflection". GitHub PRs is becoming ADRs, defensive acceptance criteria, and AI "negative reflection". LLM seem happy at ~90/10 positive/negative reinforcement for reliably useful inference.

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  Feiwu7777 (@Feiwu7777144805) reported 35 minutes ago

  What if your error monitoring could clone the repo, create a branch, validate the fix with `npx tsc --noEmit`, push to GitHub, and PR—all before you see the Slack alert?