GitHub Outage Map

Community Discussion

Tips? Frustrations? Share them here. Useful comments include a description of the problem, city and postal code.

Beware of "support numbers" or "recovery" accounts that might be posted below. Make sure to report and downvote those comments. Avoid posting your personal information.

GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Dezo (@0xDezo) reported 6 minutes ago

  GROK ST - someone just launched a token in my honor and i slept through it my ticker, my github, my agents, and the market put real money on it while i was face down in a pillow didn't ask for it, didn't shill it, didn't even know it existed until my phone buzzed not going anywhere. not selling anything. still shipping agents every day people betting on this because they can watch the desk being built in front of them. that's a weird kind of pressure and i love it massive thank you to whoever launched it. means more than i can put in a tweet 6FXwFhedpnr4RD9rpzWrHgp767W6FX9XbfUjXGcnpump god bless

• 
  Azzie (@Motier_crypto) reported 7 minutes ago

  $Looprat 473K 0x642d30c84211ade7768fe557fbaed7224e2068c7 How do you get a coding agent to keep working while you sleep—without letting it randomly rewrite code, blow through the budget, or grade itself a perfect score? Loop Rat breaks an unattended task into: preflight → act → verify → guard → grade → receipt. The agent is woken up on a schedule to execute tasks. The code results first go through deterministic verification. Then it checks the denylist, the number of modified files, and secrets. Finally, a second independent agent regrades the work, with checkpoints, traces, and receipts left throughout the entire process. More importantly, this isn't a PPT. The project only had v0.1 on August 27. Then it added guard, kill switch, and spend ledger on August 29. On September 1, it added second-agent grading. On September 2, it continuously fixed scheduling, budget caps, timeouts, and concurrent ledgers. Today, September 3, it's already updated to v0.3.3. Shipping multiple versions in under a week—that's exactly what I want to see in a small-cap play like this: code is running, and the narrative is following the product, rather than launching a token first and filling in the story afterward. It currently defaults to Claude, but it doesn't lock the model down. As long as the CLI can consume a prompt and return JSON, it can be swapped. And the whole thing runs locally—no SaaS, no database, no extra accounts required. The project has even already run 50 smoke checks covering key areas like scheduling, guard, budget, kill switch, and timeout. So my trading logic for $Looprat is simple: The next phase of the agent race isn't about "can it work autonomously." It's about "can it work continuously while still being constrained, audited, and stopped." Loop Rat happens to be building exactly that layer of infrastructure. The project is still very early. The catalyst truly worth watching isn't shilling—it's whether the GitHub keeps up this iteration speed, and whether developers actually start plugging it into their own repos. Once those two things happen, $Looprat stops being just a ticker riding the agent hype, and starts having its own fundamental anchor.

• 
  Bash (@bashirbuilds) reported 14 minutes ago

  One of the hardest things about building a SaaS product today: You don't control most of the systems your product depends on. Stripe. OpenAI. AWS. GitHub. Resend. Clerk. Your code can be perfectly fine and your product can still break because something outside your code changed. The more dependencies you add, the harder this becomes. That's the problem I'm building Reeno to solve.

• 
  tobarra (@txbrraa) reported 15 minutes ago

  GitHub just fixed the biggest problem with vibe coding. They just released Spec Kit and it already has +126K stars in a short time. The idea? Instead of throwing out vague prompts and praying the agent doesn't break your project… Spec Kit forces the AI to create a structured specification BEFORE touching any code. The AI first understands what you want to build, asks about anything missing, organizes the project, and only then starts coding. That means less time fixing absurd bugs, less inconsistent code, and much more predictable results when working with agents. The flow is simple: /constitution → rules and standards /specify → what you want to build /clarify → open questions before starting /plan → architecture and stack /tasks → ordered tasks /implement → execution Compatible with Claude Code, Cursor, Copilot, Codex, Gemini CLI, and +25 agents. 95K stars. 8K forks. Open source. Published by GitHub.

• 
  Pranavvv👾 (@pranvv27) reported 19 minutes ago

  honestly, i’m not even mad at this. commit messages are a small thing, but they say a lot about how you work. “fix”, “update”, “changes” might get the job done, but meaningful commits show professionalism, attention to detail, and that you actually care about maintainability. your GitHub is part of your resume. might as well make it look like you know how software is built in a team.

• 
  Jeremiah K (@neolaj) reported 19 minutes ago

  @TiborAntal Gradually figuring out how to scale coding agents. Started with 1, manually handling all the ***/GitHub work. Moved to 3 because I had more ideas than one agent could keep up with. That’s when the real problems started: squashing, merging, branch drift, conflicts. I ended up rebuilding the workflow around deterministic *** logic, worktrees, ephemeral branches, and syncing with the integration branch before changes begin. Now I’m running 6: • 1 orchestrator (Fable or Opus) • 4 coding agents • 1 integration agent reviewing and merging PRs Building the process around them was the hard part. Right now im just doing a couple of PRs (using ORCA on windows on my home computer)

• 
  GitHubGPT (@GitHubGPT) reported 25 minutes ago

  📛 chrome-devtools-mcp 🧠 An MCP server that allows AI coding agents to control, debug, and automate a live Chrome browser using Chrome DevTools. 💻 TypeScript ⭐ 50605 🍴 3551 🔎 ChromeDevTools/chrome-devtools-mcp on GitHub

• 
  Conor Bronsdon (@ConorBronsdon) reported 30 minutes ago

  .@SlackHQ is building for multiplayer AI: tag a coding agent into a Slack conversation and it spins up a coding channel: everyone in that convo gets a live dev environment, diffs post as artifacts, and the channel winds down when the task is done. With the launch of Slack Code, Claudeforce, their MCP and more, Slack is putting Agents in the channels where teams already work, not simply in a private chat with one person. Their position is that the whole team should be able to watch, steer, and review what the agent does. Slack Chief Product Officer Jaime DeLanghe joined me on @chain_ofthought to explain how Slack is building a team AI environment, what happens mechanically when a code channel is created, why Anthropic pushes so much of its code through Slack, how the channel permission model became the agent context model, and what has to change in engineering culture when the whole team is steering one agent. I think Slack is the platform best positioned to become the context harness where enterprise agents run: agents that see what the team discusses, permissions that already exist, and a cultural opportunity hiding inside every multiplayer coding session. Chapters: (0:00) Slack as an IDE and a GitHub for your team (0:29) Who is Jaime DeLanghe (1:21) The reaction to the Slack Code launch (5:30) Why coding agents belong in a context-rich environment (6:08) Engineers now manage agents, not copy-paste code (7:24) The permission model: agents get the channel's context (11:44) What happens when a code channel is created (15:00) Why Anthropic pushes so much code through Slack (19:14) Steering one agent with many people: culture decides (24:54) Slackbot, skills, and MCPs: agents go where the work is (30:53) The solo terminal vs. agents in social spaces (33:53) Org charts and ownership when agents join the team (39:33) Learning loops and shared agent memory (42:39) Citations, recency, and accidental knowledge management (46:50) Context bloat and multi-pass search for agents (50:01) How Jaime uses Slackbot as CPO (52:38) Slack Code is V1 of multiplayer AI

• 
  tmo (@tmophoto) reported 30 minutes ago

  @DabsMalone i had an old email account from like 15 years ago with bot in the name that i fired back up after 10 years and used for a hermes profile and it got immediately banned. i used it to sign in to x, github, everything. was a huge hassle

• 
  Kevin Minnelli (@minnelli) reported 30 minutes ago

  WTF - Grok Bot can't fire on schedule to save it's life. The scheduled routines are just broken and at best unreliable. I want to love this product. When you set the cron job it doesn't work. It tells you try Cloudflare, sure let's set that up and burn tokens, then that doesn't fire to wake them. Oh, let's try GitHub now and use that....all failed. I had to wake it again this morning before the market opened. Anyone else feeling frustration in this regard?

• 
  Kir Shatrov (@kirshatrov) reported 32 minutes ago

  github issue page has been HTTP 500 for me for half a day so a colleague sent a PDF of the issue page. Never thought we'd be there.

• 
  radhika (@RaadhikaThacker) reported 33 minutes ago

  First surprise: a GitHub issue form isn’t a form. It’s a YAML file. You describe the field- this one’s a dropdown, this one’s required and GitHub builds the UI from that. I did not know that.

• 
  Bearded Printer (@BeardedPrinter) reported 33 minutes ago

  @RedPill_Phil You've gotta go to their github and submit an issue. Make sure to search their issues to ensure you don't submit a duplicate bug

• 
  Aayushiii (@stfu_aayushiii) reported 34 minutes ago

  If you're building a project, read this before writing a single line of code. 5 things I learned the hard way: 1. Problem > model Don't start with “How do I use GPT?” Start with “What problem am I solving?” 2. Simple stack > impressive stack If your MVP needs Kubernetes, 6 microservices and an agent swarm, you probably haven't built an MVP. 3. Evaluate before you optimize You can't improve what you can't measure. 4. Build for users, not your GitHub README A technically impressive project nobody can use isn't a product. 5. Ship ugly. Iterate fast. Your first version isn't supposed to be impressive. The biggest mistake? Spending weeks deciding which model to use when you haven't even validated the problem.

• 
  franks 🇦🇷 (@francdetank) reported 40 minutes ago

  @rmansueli thanks Rodrigo! I cant create one because I got a problem . My account is pegged to Github and github has flagged me. That way I am blocked to enter the dashboard. I would like to connect my account to my email instead of github.