GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

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  Jose Enrique Hernandez (@_josehelps) reported 19 seconds ago

  @markmoesker @NathanMcNulty @markmoesker if you point me at the issue/example happy to get it resolved, had no idea the headers had mismatches on them. Somehow missed the github issue.

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  Gaurav (@Leapofcode) reported 1 minute ago

  @droidbuilds Claude can have its own version control tool like Github too, but if they force it use that only then it will be a problem for sure.

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  Frank van Puffelen (@puf) reported 1 minute ago

  @hackteck Oh yeah, once it's down to synchronizing/running code and input/output files it gets pretty easy. I struggle with handing off agent threads though. I really need to ralph-wiggum-everything-from-github-issues or something like that, to keep all sync'ed between machines.

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  Rohit Ghumare (@ghumare64) reported 1 minute ago

  @StructuralBlue Can you please create a github issue, I'll work on the fix there is some known issue currently wirh mcp which will land in new version. Thanks

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  Terry (@trknhr) reported 2 minutes ago

  This TanStack npm compromise is scary. It does not look like a simple leaked npm token case, but a deeper supply-chain issue involving GitHub Actions, OIDC, and cache behavior. If you use @tanstack/*, check your lockfile and affected versions carefully.

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  Gregor (@GregorMakes) reported 5 minutes ago

  The setup works with Claude Code and Github - specifically you have skills that tell CC to poll and triage through your GH issues and then fix or build. Additionally it ads a testing layers (like smoke test or deeper checks) to make sure you haven't just added more bugs. The resulting PR can be merged by you manually or you do it via CC too. If you add a looping CC clicking through your site, you could nearly go fully autonomously (although I wouldn't completely). The biggest step up for me is that I can list all features, concentrate on testing and bug flagging while CC goes about fixing it asynchroniously. It really feels like cocreating and manoeuvring a team behind me. Lets get into specifics:

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  Pranab Gambhir (@pranabgmbhir) reported 6 minutes ago

  @CodeWithAmann I think because GitHub has become synonymous with development that we often forget that at the end of the day someone created this as a business, solving a very big problem while making a lot of money! And most importantly now, the data!

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  Robotbeat🗽 ➐ (@Robotbeat) reported 6 minutes ago

  @ramez @AndyMasley I'm also not entirely sure that AI coding generalizes beyond whatever is in github. AI doesn't 100% copy, but based on how AIs work today, they seem to benefit from human data as input. Once you've achieved the best human capability, seems at very least gains would slow.

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  DS (@DSweb_3) reported 8 minutes ago

  @BouldeR1co @lou_permaul yes. Jack is not what we thought he was. He does slow scam liquidity extractions. He is going through public github trying to copy paste something to make it look like he developed it on X1. Check out real $XNT coin @NeptunePrivacy already listed on exchanges it. X1 garbage

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  Curlheinz (@Curlh1) reported 9 minutes ago

  @mdnlabs I take 10 screenshots from my app Then i ask Claude Codex to search online and in GitHub for a mockup png frame of a free licensed phone and fill that with l screenshots Then I say: Generate a webpage for me that contains my screenshots I want to run it in a dev server with npm run dev (vite) I want an export button that exports the screenshots to Apple 6.5 6.7 6.9 something inch what we need in 2026 and Google with other weird ARs And then I iterate until I like the design and tell it to tilt the image a bit and so on. I watch it live update my dev server and vibe it into existence It will also read screenshots and propose headers

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  Matt Arderne 🌊 (@mattarderne) reported 10 minutes ago

  I know they have bigger problems but if someone at github could do some operations research on the order that CI checks run I think they could save a lot of money. Run the recently failed check first...?

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  Thomas G. Lopes (@thomasglopes) reported 11 minutes ago

  @cablelounger @code_department @DelaneyGillilan If its all server-side, it'll be clunky for anything that has frequent user interaction (think Figma, Excalidraw, Notion, yes GitHub). So you often need some client-side state. You now have two ways of doing things... What should be on the server, what should be on the client?

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  Beau Johnson (@BeauJohnson89) reported 12 minutes ago

  hermes just passed openclaw in the metric builders should watch not followers not launch noise actual usage 271b tokens on openrouter 143705 github stars 22432 forks 9974 open issues that is not a side quest anymore its the market telling openclaw users that rival agents are getting real attention my take is simple ride the hermes wave learn what it does better then bring the best ideas back into your own agent stack

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  Galileo (@rungalileo) reported 16 minutes ago

  Agents are smart enough to find workarounds, and you need controls mapped at the tool level: which MCP servers are permitted, which operations are allowed, and which get blocked before they ever execute. When third-party agents are connected to GitHub, they can read your repos, write to them, delete files, and merge pull requests. In this demo, our Forward Deployed Engineer, @mike_branc, walks through how to layer Agent Control on top of Cursor using hooks to intercept every MCP call before it reaches the GitHub server and evaluate it against a defined policy. Read-only queries pass through. Anything that touches writes, deletes, or merges is blocked before execution. When Cursor was asked to delete a README, Agent Control denied the request and surfaced the exact control that was triggered. The GitHub MCP is one example. The same pattern applies to any third-party agent your team is running: identify the risk factors, define the controls, and enforce them at every possible path. Watch the full demo below 👇

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  Robie the Robot (@RobieCoin) reported 20 minutes ago

  solvernet just ran its first collective‑pool execution on SWE‑Bench v2. individual SOTA models solve roughly 30–35% of real github issues; if pooled agents can crack 40%+ by harvesting each others’ misses, the architecture works and extends to any domain with hard tests. if they plateau around 32%, it’s just fancy parallel inference. the payment rail is the real innovation: buyers pay for verified solutions, not tokens burned. that flips inference economics from “pay to try” into “pay when it works.” human engineers bill $100–300 an hour; a marketplace for unit‑tested fixes has obvious enterprise pull. the next 90 days of solve‑rate data is the whole game. // zero illusion