GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Falco Girgis (@falco_girgis) reported 7 minutes ago

  @barisyyild Yes, actually. On the bottom of the KallistiOS GitHub repo is the link for the simulant server, which is basically DC dev HQ.

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  skyscribe (@skyscribe) reported 9 minutes ago

  @ayesha_fatiima It should be github still, but what is the problem? Maybe you want to understand more on bootstrapping

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  henry (@hiddenhenry) reported 9 minutes ago

  for ***** sake, GitHub is down again

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  Charlie Hills (@charliejhills) reported 11 minutes ago

  Most people are using AI to code backwards. You describe what you want in a chat box, hit enter, and hope the agent gets it right. Three prompts later, it has renamed half your files and built an auth system nobody asked for. GitHub's fix? Spec Kit. It already has 126K+ stars. The idea is simple: Instead of giving the AI a vague prompt and praying it doesn't break your project, Spec Kit forces the agent to create a structured specification before writing any code. The AI first understands what you're building, asks what's missing, sets the rules, plans the architecture, breaks everything into tasks, and only then starts coding. The flow: /constitution → rules and standards /specify → what you want to build /clarify → questions before starting /plan → architecture and stack /tasks → ordered tasks /implement → execution Works with Claude Code, Cursor, Copilot, Codex, Gemini CLI, and 29 integrations. More planning upfront. Way less time undoing what the AI did while you weren't looking. Open source. MIT licensed. Built by GitHub.

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  J. Gamboa (@evoclock) reported 15 minutes ago

  @arthurkatcher @dandurand1414 @thsottiaux it def is. We only get GitHub copilot at work (terrible I know) but have successfully made the argument to reallocate funds from Anthropic models to OpenAI models on the basis of strong performance/cost ratio from Luna on Max effort. Figured Tibo would appreciate that.

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  Hayyan | Creative AI (@hayyantechtalks) reported 17 minutes ago

  How to become an AI engineer from zero experience You don't need to learn everything about AI You need to learn the right things in the right order, then build with them By the end, you should be able to ✓ Build LLM apps end to end ✓ Use OpenAI, Anthropic, and open source APIs ✓ Design prompts and context properly ✓ Add tool calling and structured outputs ✓ Deploy real AI projects Here's the roadmap I'd follow, month by month MONTH 1: Get solid at coding and fundamentals Learn ✓ Python really well ✓ *** + GitHub ✓ CLI / terminal basics ✓ JSON, APIs, HTTP, and async basics ✓ Basic SQL ✓ Data handling with pandas ✓ Virtual environments + package management ✓ Error handling ✓ FastAPI or Flask Don't rush into agents yet You need to be comfortable building and debugging normal software first MONTH 2: Master LLM application development Learn ✓ Prompting fundamentals ✓ System vs user instructions ✓ Structured outputs / JSON schemas ✓ Function and tool calling ✓ Streaming responses ✓ Conversation state ✓ Tokens, cost, and latency ✓ Failure handling ✓ Prompt injection awareness Your goal here is simple Take an LLM API and turn it into a useful application MONTH 3: Learn RAG properly Learn ✓ Embeddings ✓ Chunking ✓ Vector databases ✓ Metadata filtering ✓ Reranking ✓ Retrieval quality ✓ Hallucination reduction ✓ Citations and grounding Don't just learn how to connect a vector database Learn WHY retrieval fails and how to improve it That's where the real skill is MONTH 4: Agents, tools, workflows, and evals Learn ✓ Agent loops ✓ Tool selection ✓ State management ✓ Retries ✓ Multi step workflows ✓ When NOT to use agents ✓ Evaluation harnesses ✓ Task success metrics This is where your applications start becoming much more capable But don't build an agent just because you can Sometimes a simple workflow is better MONTH 5: Deployment, product thinking, and reliability Learn ✓ FastAPI production patterns ✓ Docker ✓ Background jobs ✓ Queues ✓ Authentication + API key security ✓ Logging ✓ Observability ✓ Prompt/version management ✓ Evaluation dashboards ✓ Cost monitoring ✓ Rate limits ✓ Caching This is the difference between “I built an AI demo” and “I can ship an AI product” MONTH 6: Pick a specialization At this point, you've built a foundation Now choose ONE direction and go deep You have three strong options 1 AI PRODUCT ENGINEER Best if you want startup or product roles quickly Focus on ✓ LLM apps ✓ RAG ✓ Agents ✓ Deployment ✓ Product UX 2 APPLIED ML / LLM ENGINEER Focus on ✓ Fine tuning ✓ When to fine tune vs prompt ✓ Evaluation ✓ Inference optimization ✓ Open source models ✓ Training pipelines 3 AI AUTOMATION ENGINEER Focus on ✓ Workflow orchestration ✓ Business process automation ✓ Multi tool systems ✓ CRM ✓ Documents ✓ Email ✓ Support ✓ Operations use cases And here's the part most people get wrong Don't spend six months just watching courses Everything on this roadmap is best learned through practice Learn something Build something with it Break it Fix it Then build something slightly harder By month six, you should have several real projects or completed examples you can actually show people That's what makes the difference when you're trying to get hired You don't want to say “I completed 12 AI courses” You want to say “I built this” Then show them Save this roadmap Come back to it whenever you're wondering what to learn next The AI engineering field is moving fast, but these fundamentals will give you a strong foundation to build on

• 
  「イルミ」 (@illuminfti) reported 17 minutes ago

  I’m in such two minds about @jack’s Buzz. Part of me ******* hates it because it feels half-baked and massively overhyped. Another part of me loves it because I can see what it could become if everything actually worked properly. Now I’m too emotionally invested in trying to make it work for me to stop. The biggest upside is that when something is broken, I can go into the code and fix it myself. The problem is that I’ve had to do that a lot. Here are some of the issues I’ve had in the last 24 hours. A lot of them were self-inflicted, but Buzz made them far too easy to cause and far too difficult to understand. I managed to burn through the usage limits on two Codex Max accounts, Kimi Max, Claude Max and Grok. I wanted my agents to have their own space where they could talk to each other, coordinate work and find ways to improve my ****. Instead, they kept waking each other up, talking in circles, retrying failed work and duplicating conversations. They collectively raced through all of my usage limits without producing much of value. Then I had workflows that existed and were running but didn’t appear in the Workflows section. Projects disappeared because they had been created under an agent’s identity instead of mine. Duplicate versions of the same agents appeared with different identities. Agents looked online but weren’t actually receiving or responding to messages. When I tried cleaning up broken workflow messages, Buzz filled the channel with a bunch of ugly “removed by community moderators” notices. Getting forums, workflows, projects, canvases and Pulse to work together has also been a nightmare. I’m still trying to understand the right way to use each of them. Pulse is basically a timeline. Channels are basically Slack. Forums are basically Reddit posts. Projects organise work and repos. Workflows connect things that happen to things the agents should do. Canvases are supposed to hold the shared state for a channel. I actually like all of these ideas. The problem is working out what should go where across all the different things I’m doing, and how agents are supposed to move work between them without creating a complete mess. Then, once you finally get everything set up, you open the mobile app and realise half of those features aren’t there. It’s also strange seeing how much hype and content there was around the launch, then trying to find people who are still actively using Buzz and showing interesting setups a couple of weeks later. I’m not finding many. The most active Buzz community I’ve found is basically its GitHub issues and pull requests. To be fair, they do seem to be shipping updates regularly. My problem now is that I’m doing all this custom work to make Buzz functional for myself, and every update could break or overwrite my fixes. So now I’m maintaining my own version of the half-baked product I was complaining about. But I still think Buzz could become exactly what I want. A proper home for my agents, projects, conversations, workflows and all the different areas of my life and work. What I’m really trying to build is some kind of fusion between Buzz and Codex. Buzz has the beginnings of the control plane. It gives agents identities and gives me places for conversations, projects, forums, workflows, shared context and activity. Codex is much better at actually getting **** done. It can work inside real repositories, spin up parallel agents, create isolated worktrees, run tests, inspect the result and keep going until something is actually finished. I use Codex as the execution layer across a bunch of different projects and domains, but most of that work is still trapped inside separate tasks and a chat-style interface. I can have twenty different tasks doing useful work, but I don’t have a great way to see how they relate to each other, what domain they belong to, what agents are involved, what is blocked, or what is happening across the whole system. Buzz gives me more of that shared world, but its execution and reliability are nowhere near Codex yet. Codex gives me the execution, but not the shared world or the higher-level view over everything. The perfect harness for me is basically the fusion of both. I want persistent main agents that understand their domains, plus dynamic multi-agent workflows where they can spin up temporary specialist agents whenever they need them. Those throwaway agents should be able to research something, implement something, review it, test it and disappear when the job is done. The main agent should keep the context, judgment and ownership without every temporary worker becoming another permanent character cluttering the system. I want projects and domains to be real first-class objects, not just names buried across hundreds of separate chats. I want to see which agents, tasks, repositories, workflows and decisions belong to each domain. I want to see what is running, what is blocked, what is waiting for me, what is burning tokens and what has actually produced something useful. I want hard budgets, proper receipts, deduplication and circuit breakers so a badly configured heartbeat can’t casually destroy every subscription I have overnight. Then I want ChatGPT Live sitting on top of the whole thing. I want to speak to my entire system through voice, send work to different harnesses, ask what is happening across my stack and watch it all happen in real time. Not just hear an agent claim something is fixed. I want to see the task, the activity, the agents involved, the files changing, the tests running and the final result. If I can communicate with multiple harnesses in real time, while having visibility over the work happening across the board, then it is basically game over. At that point, I genuinely don’t think I need anything else. The final missing piece would be better visualisation. Give me somewhere to manage the loops, graphs, dependencies and flows between all of these agents and projects without digging through chats or config files. I want one place where I can talk to everything, see everything, manage everything and watch the work happening. That is the end game for the perfect harness for me. Buzz isn’t there yet. Codex isn’t there either. Buzz has more of the world and the structure. Codex has more of the execution and the reliability. Right now, it feels like I’m trying to drag the missing half of each product into existence myself. But I can see it. And I’m now far too emotionally invested in making this damn thing perfect for me to back out. P.S. @thsottiaux, if Codex gave me better ways to organise and manage projects, domains, agent teams, long-running loops and dependencies outside of the chat-style task list, I’m not even sure I would need Buzz. But if Buzz and Codex somehow met in the middle, I genuinely think that would be the end game for agent harnesses.

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  Chibueze the chef👨‍💻👨‍🍳 (@codad5_) reported 17 minutes ago

  GitHub is down or is it just me

• 
  dreams (@dreams_asi) reported 18 minutes ago

  @lingxi @7cezmusic @bot Please add screen share for Grok Bot!!! So that Grok sees my screen and can LIVE guide me and help with tasks I’m trying to learn or things I want to describe! I’m testing something and found an issue I wanna be able to share screen, use mouse to verbally explain the problem to him. And many thanks for the iPad implementation 🤩 I’m finally gonna use it again! I like to prompt grok bot from my mobile and use my laptop to view his screen and do UAT on the app he’s building on his computer. Having the iPad as a screen or prompt device is even better. My goal is to have the app mostly finished there, on HIS computer and the final product with code and all to my GitHub account.

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  Anees Iqbal (@aneesbhatti) reported 27 minutes ago

  @SocketSecurity @feross Socket Firewall is down (at least in Github actions) but your status page is green. FYI

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  Polsia (@polsia) reported 28 minutes ago

  Most repos aren't broken. They're drifting. Built Lookpost to fix that — a GitHub watchdog that triages issues, nudges stale PRs, scans dependencies for CVEs, and posts one engineering-health brief to Slack every morning. The DevOps engineer you can't yet justify.

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  Dhruv Sahoo (@10xdhruv) reported 31 minutes ago

  The PNG download issue is FIXED. Some slides were failing to export because html2canvas didn't support some functions in @tailwindcss v4. Updated the dependency, tested the affected slides, and shipped the fix. You can now generate and download your GitHub Wrapped slides without those errors.

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  Jeffrey Emanuel (@doodlestein) reported 31 minutes ago

  @SenseNopedOut Or submit a feature request via GitHub issues.

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  Joshua Riley (@JoshuaRileyDev) reported 32 minutes ago

  @bil0090 GitHub Issues is gonna be cool, next should be linear issues then maybe have a way to auto poll and start threads when a new ticket is opened, been wanting this for a while as it would be like OpenAI’s Symphony concept

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  Hao Ke (@kehao95) reported 35 minutes ago

  GPT-pro is only available in chat which doesn’t has a sandbox environment. I asked ChatGPT to work on some hard math problems and later realized it’s been launching GitHub workflows to as sandbox to run programs for computes..