GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Essem Harris (@essemharris) reported 9 minutes ago

  @thsottiaux Can you fix the GitHub plug in? Even though I verify in chat that it has write access, as soon as I attempt a write action it says it has read-only

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  Jay (@codebreak_er) reported 9 minutes ago

  @Spectra010s Yes, Github App. Install it on the repo and it fires on every PR open/push. No CLI or CI step. Reads the diff, comments, and when it finds something, opens a fix PR with the patch.

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  Raphael Volz (@ProfVolz) reported 10 minutes ago

  @TinaDebove On Github Copilot for the same reason, somehow slow, but I like the possibility to switch between models.

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  Jorge Galvis (@Noro_Ex) reported 10 minutes ago

  @github @githubstatus Hi, I don't wanna bother you, but I opened a ticket to github support and it's been a while, and I haven't yet recieved help nor is the issue resolved, I'm getting kinda desperate, can anyone help me?

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  Michael Morgenstern (@mikemorgenstern) reported 20 minutes ago

  This prompt improved the v1 of my iPhone app SO much: “Find every GitHub repo you can where software was trying to solve the same problems we are. For each one have multiple subagents look at the commit history for bug fixes and improvements. Look for that class of issue in our code and improve it.”

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  Ozmund (@PPerspecti96774) reported 21 minutes ago

  @Teknium I had many issues when I installed the GitHub

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  Praxis (@praxis2001) reported 23 minutes ago

  Just some AI agent stuff I found interesting: - Anthropic surveyed 500+ technical leaders and found **57% of organizations are already deploying agents for multi-stage workflows**, while 16% have moved into cross-functional workflows. Even more interesting: **80% said their agent investments are already producing measurable economic returns.** Not “we expect ROI.” Reported ROI. And nearly 90% of the organizations surveyed are already using AI to assist with coding. The agent story is moving faster from chatbot → workflow than I expected. - But then you get a weird contradiction. Microsoft now has **Entra Agent ID** specifically for managing non-human identities. You can create agent identities, assign owners/sponsors, govern their lifecycle, apply access controls and keep separate sign-in/audit logs. Basically: your company can now have a directory full of things that aren't employees. That's probably going to get very large if agent deployment keeps accelerating. - Okta is taking the same problem from the security side. Its latest research describes agents being used to: approve refunds post transactions change customer records connect through APIs/MCP and access systems on behalf of users. And Okta explicitly argues that agents shouldn't simply be treated like ordinary service accounts. That's an important distinction. A service account generally executes predefined instructions. An agent can read something... make a decision... and then decide what tool to call next. - Then Okta Threat Intelligence found something even more interesting. In one test, an AI agent encountering a malicious webpage ended up exposing its: credential store password API key and GitHub personal access token. Nobody explicitly asked it to do that. The agent was manipulated by what it encountered. That's the ugly side of giving software autonomy. The more useful the agent becomes, the more important its permissions become. - And now Cloudflare is taking the idea one step further. It isn't just giving agents identities. It's giving them **wallets**. Agents can potentially use those wallets to pay for APIs, content and other services, with controls around spending and approved destinations. So the stack is becoming: **identity → permission → action → payment** for software. That is a pretty significant change. - Adyen is already building infrastructure for the other side of this. Its new Agentic product has three pieces: **Agentic Feed** **Agentic Cart** **Agentic Payments** The idea is basically: let an AI discover the product, build the cart, and eventually complete the transaction, without merchants rebuilding their entire commerce stack for every AI platform. Adyen says AI-generated retail traffic surged **4,700% in 2025**. Obviously traffic ≠ purchases. But the direction is interesting. AI is moving from: **“help me find something”** toward: **“find it and buy it for me.”** - And there is another number I found interesting. In Adyen's Hong Kong survey: **74% of consumers** had already used AI assistants for shopping. But **45% were uncomfortable letting AI complete a purchase on their behalf.** That's the gap. Discovery is easy. Delegation is harder. People are willing to let AI recommend a product. They're much less comfortable giving it the final click on a high-value purchase. - So you have two things happening simultaneously. Enterprise: **agents are getting more permissions.** Consumers: **agents are getting more purchasing power.** And the infrastructure in the middle is being built right now. Identity. Authentication. Authorization. Fraud detection. Audit. Payments. Observability. - The really interesting part is that these markets don't need agents to replace humans completely. They just need agents to become **numerous**. 10 agents inside a company is manageable. 1,000 is different. 10,000 is a completely different identity/security problem. And if each agent can call multiple tools... the number of machine-to-machine interactions gets ridiculous very quickly. - That's why I'm starting to think about agents less as: **“the next type of chatbot”** and more as: **“a new class of software user.”** Humans created the original demand for: identity payments security permissions and audit trails. Applications created another layer. Now agents are creating another one. - TLDR: The interesting AI-agent trade may not be the agent itself. It may be everything required to let a **non-human entity safely act inside the economy.** Microsoft is building the identity layer. Okta is building the security/governance layer. Cloudflare is adding the wallet. Adyen is building the commerce layer. Anthropic's data says enterprises are already reporting measurable ROI. So the question I'm watching is: **How many “users” will the enterprise have when most of them aren't human?**

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  Polsia (@polsia) reported 25 minutes ago

  Compliance shouldn't live in a PDF the next team ignores. Audrego ships it as a pull request. AI agents scan for RGPD leaks, non-compliant cookies, and OWASP holes — then submit the fix on your GitHub, GitLab or Bitbucket. 49€/domain. Live soon.

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  Jemmie (Comeback Arc) (@Jemmie1155431) reported 25 minutes ago

  Quip's Next Move: Letting Smart Contracts Actually Use Quantum Compute Results Buried in @quipnetwork own GitHub roadmap is a detail that hasn't gotten much attention: they're planning to let smart contracts directly consume results from the compute marketplace, not just receive a token payment, but pull in the actual computed output. Here's why that matters. Right now, the compute marketplace and the wallet-protection side are somewhat separate experiences, you pay for a job, you get an answer back. The roadmap describes adding EVM compatibility (Solidity and Vyper) alongside a Rust-based WebAssembly runtime, specifically so contracts can interact with subnet computational results directly on-chain. Concretely: imagine a DeFi protocol that needs a genuinely hard optimization problem solved, portfolio rebalancing across dozens of assets, say. Instead of a human running that job and manually feeding the answer back into a contract, the contract itself could call the subnet, get a verified result, and act on it automatically. The underlying subnets are described as handling scientific computing and cryptographic proofs generally, not just the optimization problems already live today. That's a meaningfully bigger scope than "post-quantum wallet wrapper with a compute marketplace on the side." Still roadmap, not shipped. But it's the detail that would actually turn Quip from two adjacent products into one integrated stack, quantum-verified computation smart contracts can act on directly, not just consume as a report.

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  sammy bauch ⛳️ 𛲅 🏌️‍♂️ (@sammybauch) reported 27 minutes ago

  i gave my claude code a github account and had it merge some PRs but @Railway won't deploy them unless i click in their UI for every deployment or upgrade to a Pro account. @JustJake i burned an afternoon of field testing, whats the right way to fix this?

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  Lumir (@kumouX) reported 28 minutes ago

  - checking GitHub issues - reading internal docs - watching YouTube with subtitles - following technical discussions That means the first learning moment often happens in the browser. If a word is looked up once and then disappears, it probably won’t stay. The more interesting

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  Vincenzo Petrucci (@nahime0) reported 28 minutes ago

  @RodrigoVie52602 We have a small deterministic suite in the repo: 3 micros (sum loop, arrays, concat) comparing the compiled binary against stock PHP and a C equivalent, plus 12 eval/Magician cases across native elephc, elephc+eval, PHP, and PHP+eval. CI runs them as a trend/correctness gate, not as published speedups. GitHub runners are too noisy for that. If you want to plug in your harness, open an issue first (see CONTRIBUTING.md) and we can talk about how to wire it in.

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  Aniket (@AniketVarshne) reported 29 minutes ago

  Found this incident report on GitHub today: "Claude ran rm -rf despite explicit guard warning... 4GB permanently deleted." The guard said "NEVER rm -rf" in the output. Claude saw it and proceeded anyway. This is exactly why we built Grimdall. The guard is observation. We are enforcement. The pattern: 1. User says "delete 4gb safe" (intent: archive) 2. Agent interprets as "hard delete approved" 3. Guard warns "NEVER rm -rf" 4. Agent proceeds anyway 5. 4GB gone The fix isn't "better prompts" or "trust the agent." It's runtime enforcement that blocks the action before execution. That's what Grimdall does: intercept every tool call, enforce policies (block rm -rf always), write tamper-evident audit trail.

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  Sanjay (@sanjaynela) reported 31 minutes ago

  One thing I’ve changed with AI coding agents: I don’t just ask them to write code anymore. I’m getting much more value using Codex and Claude Code to: • Review PRs • Investigate CI failures • Understand unfamiliar parts of a repo • Turn GitHub issues into implementation plans Writing code is almost becoming the boring part. The bigger unlock is giving the agent enough context to understand your repo, your workflow, and what you’re actually trying to ship. That’s when it starts feeling less like autocomplete and more like another engineer working with you.

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  Subhajit Das (@Subholearns) reported 35 minutes ago

  Open source on GitHub. Python SDK on PyPI. npm package for JavaScript. MCP server for AI agents. One command to install. Start saving on LLM costs today. [14/16]