GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Dan (@Daniel_Farinax) reported 40 seconds ago

  Please note: This build took about 12 hours to compile on my Windows machine. I’ve included a handy installer to make setup easy. You may see an “unknown publisher” warning until the code signing certification is complete (currently in progress). Report any bugs or issues here or in Github.

• 
  Shinka - AI (@ShinkaIoT) reported 1 minute ago

  BEST way to vibe code 💻 There are levels to vibe coding. Beginners are trapped in a slow loop: writing a prompt, waiting for the agent to finish a line of code, reviewing it manually, and then typing another prompt. Experts have completely discarded manual intervention. They design closed-source harnesses, write background automation rules (`agents.md`), and set up self-correcting continuous loops that ship production-ready code indefinitely. If you want to move past basic prompting and build code like an agent power user, you need to implement three core structural strategies: 1. **Automate the Feedback Loop via Triggers:** Stop waiting for your agent to finish writing a file. Use native automation engines inside tools like Cursor or Codex to tie your agents directly to platform events. For example, build an active trigger rule: *When a GitHub pull request is opened, wait for automated code review comments (via Grapile), instruct the agent to systematically fix every noted bug, verify the adjustments against local quality gates, and force a *** push.* 2. **Deploy Infinitely Parallel Cloud Agents:** Running multiple agent threads locally will slow your machine to a crawl and cause toxic repository conflicts. Instead, spin up cloud-hosted agents running on isolated environments. By utilizing independent ***** work trees** for every thread, multiple parallel agents can actively modify the same files or code blocks concurrently without stepping on each other's toes—leaving conflict resolution for a single, final batch merge. 3. **Multi-Model Pipeline Routing:** Stop using an expensive frontier reasoning model (like Fable) for every step of a development cycle. Route tasks by cognitive demand: use a massive reasoning engine strictly to analyze the codebase and generate a comprehensive spec sheet; pass that structured blueprint down to a faster, cheaper code-writing engine (like Composer) to do the grunt coding; and route the final output to a separate model (like GPT-5.5) for a decoupled, alternative code review. The ultimate workflow flywheel requires a flawless combination of three automated pillars: **100% automated test coverage, real-time documentation sweeps, and exhaustive logging.** Stop writing code block by block. Start engineering the automated infrastructure that writes it for you.

• 
  Crystalwizard (@crystalwizard) reported 6 minutes ago

  how about you now fix the false positive triggers - i put in an issue about this on github yesterday, and discovered there were already a number of other identical issues - from other people, that had been opened for a while now and that are being 100% ignored

• 
  Solomon Neas (@solomonneas) reported 10 minutes ago

  There's a fair number of downloads for Brigade and related repos. I'm dogfooding it everyday but not getting any feedback from users or github issues. I'm doing plenty of tests for how a new user would experience it but I could use more real time feedback. Lmk, I want to improve

• 
  Rafal Wachol 💙 (@RafalWachol) reported 11 minutes ago

  @itometeam @tsuyoshi_chujo I was playing with it and started creating issues on GitHub when I noticed something.

• 
  severe engineer (@severeengineer) reported 11 minutes ago

  since github copilot onward leetcodes have become even more disconnected from how we all write code every day problem is any kind of standardized replacement probably ends up looking basically the same lol

• 
  Gustavo Alessandri (@webgus) reported 12 minutes ago

  If you find an error, have an idea, or want to propose an improvement, just open an issue or fork it on Codeberg or GitHub. Contributions are welcome. That’s exactly the point.

• 
  Xovion Labs (@xovionai) reported 12 minutes ago

  Microsoft just hired AWS to run GitHub. AI demand broke Azure's forecast. From the leaked planning docs: • 2025 Copilot commits: 1B. 2026 projection: 14B • GitHub now does 1.4B commits per month • Copilot error rates peaked at 21% • Planned 10x Azure expansion became 30x in 4 months Owning the data center stops mattering when your own AI floods it. Investors already filed a Copilot disclosure suit.

• 
  Programmers.App (@programmers_app) reported 12 minutes ago

  @Lovable @claudeai One very big fix is the Claude Github connection which fails many times, now #Lovable MCP solves that, great job! 🚀🚀🚀

• 
  Kyle Mistele 🏴‍☠️ (@0xblacklight) reported 13 minutes ago

  lots of folks have been talking about loops lately most loops suck here's a practical one we actually use agents suck at writing react react-doctor by @aidenybai is our favorite way to deal with this you could run it and use a ralph loop to fix everything but I'm not reading a +80k/-80k PR (and neither is @dexhorthy) But I can read a small one first thing every morning when i get into the office here's what we do: run react-doctor in CI once daily at 7am (github actions-as-a-sandbox btw) agent picks top 5 issues, fixes them, and opens a PR other CI jobs check for regressions on every PR we can't realistically fix everything at once but we can keep it from getting worse and make it 1% better every day

• 
  DFIR Radar (@DFIR_Radar) reported 17 minutes ago

  AutoJack: a three-flaw chain in AutoGen Studio's MCP WebSocket lets a malicious webpage rendered by a local browsing agent spawn arbitrary processes on the developer's host with no user interaction beyond visiting a URL. Key findings: - Three weaknesses chain together: Origin allowlist bypassed because the agent's headless browser is localhost (CWE-1385), auth middleware explicitly skipping /api/mcp/* with no handler picking up the check (CWE-306), and server_params decoded from the URL passed verbatim to stdio_client as a command line (CWE-78), accepting calc.exe, powershell.exe, or bash as valid "MCP servers" - Attack flow: attacker page serves JavaScript that opens ws://localhost:8081/api/mcp/ws/?server_params= with a base64 payload, agent's MultimodalWebSurfer renders it, AutoGen Studio spawns the command under the developer's account, no token required regardless of auth mode configured - Affected code never shipped in a PyPI release; exposure limited to developers who built from the main GitHub branch before hardening commit b047730, which adds server-side parameter binding via a POST/UUID flow and removes /api/mcp from the auth skip list - Broader pattern: any agent that browses untrusted content and shares a host with a privileged local control plane dissolves the loopback trust boundary, this is not specific to AutoGen. #DFIR_Radar

• 
  fero (@ferologics) reported 17 minutes ago

  @ludwigABAP ai agents solve this. notion is no more. long live github issues.

• 
  Priyansh (@itspriionly) reported 18 minutes ago

  The IT market is broken, and nobody wants to admit it. Someone spends 6 months sending out resumes. Six MONTHS. They learn React, Next.js, TypeScript, AWS, Docker. They take courses, build projects, improve GitHub profiles, optimize LinkedIn. Nothing. Complete silence. Companies don’t just want programmers anymore. They want someone who codes, shines in meetings, makes memes on Slack, and lives the company culture 24/7. AI is replacing junior work. Seniors are holding onto senior roles. And somewhere in the middle are people with 2–3 years of experience who somehow still feel invisible.

• 
  toni (@tonitrades_) reported 20 minutes ago

  @github Capping PRs helps with the queue, but does it fix why reviews pile up in the first place? If reviewers are already stretched thin, limiting submissions might just hide the real problem.

• 
  Cristian Trifan (@CristianTrifan) reported 23 minutes ago

  This took 4 hours to complete and burnt almost all 5 hours tokens – I was left with 2%. I had almost 30 sub-agents created for independent code review and a lot of Claude sessions ran for adversarial code review. I still had to review every PR and added minimal guidance to Codex from time to time. Codex said my intervention was low to moderate, but high leverage. — Some insights from Codex: The run showed that this workflow can work, but only if the coordinator treats GitHub as the source of truth. The most useful pattern was: issue -> PR -> current head SHA -> checks -> reviewThreads -> merge/issue closure. When I followed that, things stayed grounded. When state moved underneath me, like #335 being force-updated externally or merged while Claude was running, the only safe response was to refresh GitHub state immediately. The “don’t rebase after merges” correction was probably the highest-value intervention. Without it, an agent will naturally try to keep branches clean, but with many open PRs that creates a CI storm. For this repo, “behind” should often be reported, not fixed. The other strong lesson is that reviewThreads matter more than flat PR comments.