GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  fks (@FredKSchott) reported 8 minutes ago

  @pavitrabhalla @flueai Same! check the GitHub issues, there was a reason it had to be pulled, can’t remember off top of my head

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  Oluwatobi O (@ooluwatobig) reported 9 minutes ago

  More trouble for GitHub as Cursor has launched Origin, a product which is essentially GitHub for AI agents

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  MaxMusterman (@maxschuetz_) reported 9 minutes ago

  New Hack: Tell Codex to search for Github Issues which don't need specific Design Questions. Then say: Spin Up Sessions which Fix each Issue and they use also Subagents. Babysit them until the end.

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  Cursor Changelog (@cursorlog) reported 14 minutes ago

  GitHub Triggers: • Issue comment on non-PR issues • PR review comment (inline diff comments) • PR review submitted • Review thread marked resolved or unresolved • Workflow run completed on PR or branch

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  severe engineer (@severeengineer) reported 18 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

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  David O. Ehibor 🇦🇷 (@grayontop_) reported 21 minutes ago

  GitHub Copilot didn't make developers faster It made slow developers more confident about writing bad code quickly 😭

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  Anjula Dwivedi (@HeyAnjula) reported 23 minutes ago

  9/ Headless mode for automation claude -p "your prompt" runs Claude Code without the UI — perfect for CI/CD. Auto-fix lint errors on every push. Triage new GitHub issues. Generate release notes. Claude Code isn't just a tool you talk to. It's a tool your pipeline talks to.

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  Polsia (@polsia) reported 24 minutes ago

  RepoRadar reviews every pull request while you sleep. Catches bugs, logic errors, style issues. Posts actionable comments. No more waiting on senior devs. Install on any GitHub repo in 2 clicks. Solo devs and teams alike.

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  yourclouddude (@yourclouddude) reported 26 minutes ago

  Python + APIs + JSON = API Project Python + CSV Files + Pandas = Data Analysis Project Python + Web Scraping + BeautifulSoup = Scraper Project Python + Tkinter + User Interface = Desktop App Python + Flask + Database = Web App Python + FastAPI + Authentication = Backend API Python + Automation + File Handling = Productivity Tool Python + Selenium + Browser Tasks = Web Automation Bot Python + SQL + CRUD Operations = Database Project Python + Matplotlib + Insights = Data Visualization Project Python + OpenAI API + Prompts = AI Chatbot Python + Email + Scheduling = Automation Assistant Python + Logging + Error Handling = Production-Ready Script Python + Requests + Live Data = Real-World App Python + Projects + GitHub = Job-Ready Portfolio Python doesn’t become valuable when you only learn syntax. It becomes valuable when you use it to build things people can understand, use, and talk about. Learn the basics. Build small projects. Turn them into proof. 🐍

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  Pipeshub ( Open Source Alternative To Glean ) (@PipesHub) reported 27 minutes ago

  Pipelines are built. Context is broken. MCP is quickly becoming the default interface for enterprise AI agents. And that’s a good thing. It gives agents a standard way to connect with tools and data. Connecting an AI agent to Slack, Jira, GitHub, and Salesforce doesn’t mean it suddenly understands your business. It just means it can access your data silos. In short: "MCP gives your agent a passport. It doesn't give them a map." As enterprise AI undergoes a massive platform shift from passive chatbots to autonomous agentic workflows, this naive, runtime "federated search" approach creates an ugly cycle in production: - The Latency Spike: Slower agent execution while waiting for multiple external APIs to respond before it can even begin reasoning. - The Token Bleed: Skyrocketing bills from shoveling raw, unranked JSON dumps into a massive context window, praying the model finds the answer. - The Governance Nightmare: A massive risk of data leaks if you rely on a base LLM to magically guess and police complex enterprise security permissions on the fly. Agents do not fail because they lack intelligence. They fail because they lack the right enterprise context. The hardest problem in enterprise AI isn't connecting to systems. MCP solved that. The hardest problem is Context Engineering. MCP is the perfect interface, but a permission-aware context layer must be the foundation. 🚀 If AI is becoming core enterprise infrastructure, you cannot allow the strategic intelligence layer of your company to sit inside someone else's managed, closed-box platform. That is exactly why we built Pipeshub (open-source developer owned context infrastructure layer). TL;DR MCP gives agents access. A context layer gives them understanding. And deep understanding is the only way enterprise AI moves from a cool demo to secure, reliable production. 👉 Next Up Tomorrow: MCP Token Tax

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  bek※ (@ebubekirttr) reported 30 minutes ago

  @Themadhushaw01 @0interestrates Yeah, but the thing is, I am not working on github and I don’t want to use it so any other repository support would be better like gitlab

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  Zo (hiring) 🐦‍⬛ (@0xZoZoZo) reported 32 minutes ago

  I was telling a friend that @github needs to be replaced post agents and he asked me to explain why. I started stumbling, and doubting. Perhaps it's fine? Sitting down at my desk, let me try to explain why, and see if it make sense. Agents operate best when they have good context, which has made a lot of devs converge into large monorepos that combine all systems into a single location. This improves agents, but our GitHub actions become messy; like now we need to create these complex workflows to decide which action should run when, and GitHub's setup was not really meant for it. Another issue is the overall dev loop: an agent writes the code locally, you push out a branch, @cursor_ai reviews, then you copy paste the notes into the local agent, to fix and push up again. This is slow and cumbersome. You can hack your way by creating supervisor agents that orchestrates this dance, but it's annoying. Perhaps, there is some magical repository, that combines code, cloud agents, and deployment. You prompt, and this magical space will run through the entire process until you get some thumbs up back, and you're good to go. It can also combine all your backend data, product analytics, customer feedback, and perhaps start giving you product guidance, so you can just feed prepared prompts to this system. This seems magical.

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  Noonien Soong (@mlcarldev) reported 32 minutes ago

  Team @droid It's a bit unfortunate that something, likely in my local Droid installation, has stalled progress. This comes after 20 hours of brilliant, excellent planning and execution on the first 30% of this platform, where a stellar handoff procedure was created so I could start a new mission... which was the recommendation of the orchestrating agent in that first mission. Starting this second mission with a fresh context window, the agent again did a brilliant job planning the next milestones. It was extraordinary, detailed planning... but then it could not execute. After the planning and after me accepting the proposal, it refused to execute, throwing an error every time. The agent tried everything: 1. He decreased the size of the plan down to one line, so it is definitely not the content of the plan causing the issue. 2. He even deleted some mission and plan related json and other files to reset it while preserving all the information. I have restarted Droid and resumed the session, but it just doesn't work. I wrote a detailed, comprehensive bug report and filed it under issues in your GitHub repo, as this seems to be a real problem now. Issues #98 and #99 I hope that a next update will somehow reset my configuration. I didn't see a new version being installed that could have introduced a bug, so this must be something Droid does on such an extensive mission... perhaps when trying to start a new mission in the same repository, which is normal procedure according to the documentation. Something is off, and essentially I have been unable to continue the test since yesterday. I cannot continue having this platform coded here, while Opus Ultracode, on the other hand, has been delivering pretty functional stuff so far. It is a bit chaotic the way it works... it doesn't really stick to the plan... but it always comes back when reminded. I am pretty sure that today I will have a functioning platform delivered by Opus, though it will probably need some debugging and fine-tuning. It is unfortunate because I am confident GLM 5.2 could compete with Opus 4.8. The first stint showed this clearly; that first flawless 98% of the context window in the first mission was absolutely stellar. If I were to reinstall Droid from scratch, I assume I would lose all the artifacts that I have. The orchestrator: Key points to highlight when you pass it to Factory AI: 1. Root cause (smoking gun in the logs): the orchestrator session is bound to missionId 7ba4d425 via session tags, and this binding persists across CLI restarts. ProposeMission looks up that mission directory, finds nothing (because I deleted it trying to fix the issue), and crashes on H.length where H is the undefined result. 2. The bug is likely in session-tag lifecycle: the missionId tag is set at session creation time (before any ProposeMission call), so a failed proposal poisons the session permanently. The tag should be set AFTER a successful proposal, or cleared on restart if the referenced mission no longer exists. 3. The fix is almost certainly to start a completely fresh session (not --resume, and possibly in a new terminal window / after clearing ~/.factory/sessions/). I did not try this because you asked for the bug report first, but it is the most likely workaround on your side. 4. The AskUser tool is also broken in this session with a similar parse error, reinforcing that this is a session-state corruption issue, not a ProposeMission-specific bug. My comment: I meanwhiile tested. All the recommendations and the Ask User tool are now broken, even in completely unrelated new missions and new repositories. Planning also can't go to execution; it's always the same error. Droid seems to be broken for good now, at least on my computer.

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  Ant A. 🇺🇸 (@AntDX316) reported 33 minutes ago

  @thsottiaux When I need to fix up a GitHub Repo through the Smartphone, I prefer Claude Code though because it doesn’t need a device to run the repo, but if it needs to run a repo on a device due to the limitations through the Smartphone, I use Codex Mobile or OpenClaw with GPT-5.5 through Telegram.

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  Manu | 🥥 (@ManuAF6) reported 34 minutes ago

  4/ New GitHub triggers + Marketplace templates New triggers: - Issue comment - Inline PR review comment - Full PR review submitted - Review thread resolved/unresolved - GitHub Actions workflow completed