GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  pratik.eth (@eth_ethpratik) reported 6 minutes ago

  @Shahules786 @VibrantLabsAI Hello @Shahules786 , I am trying to report a security vulnerability over the email id provided over GitHub Security.md file but apparently its wasn’t delivered. Please share an alternative email or open the advisory for reporting the issue.

• 
  Iman (@RealKingiman) reported 9 minutes ago

  @ClaudeDevs Fix the auth bug with GitHub where I have it keep disconnecting and reconnecting GitHub every time

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  YNWA🐦‍🔥 (@YNWAcrypto) reported 10 minutes ago

  The problem isn’t subtle. GitHub Sponsors has paid out ~$50M total since 2019. core-js: 9 billion downloads, running on half the top 10k sites on earth. Its maintainer was making ~$600/month when he called open source “fundamentally broken.”

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  𝕊ℍ𝕀ℕ𝔸☃ (@Shinawritesbugs) reported 10 minutes ago

  @viii_fn Github was slow too

• 
  Almog Gavra (@almoggavra) reported 14 minutes ago

  A few other meaningless metrics to optimize for: - I've authored 22% of the RFCs - *** blame marks me responsible for 14% of the LOC (.rs files only) - I've opened 11% of the issues on GitHub - I've generated the most memes on our discord (allegedly)

• 
  Ben Vinegar (@bentlegen) reported 14 minutes ago

  💡 I have an idea for an experiment We need a website for SoAC ... so we get an agent to do it, on a loop, set in motion once with zero human intervention after "go". It works off a semi-public GitHub repo, w/ issues, PRs, maybe even public agent traces. A publicly auditable experiment on whether it produces dogshit or not. Yea, nea?

• 
  Kelvinsekx (@kelvinsekx) reported 19 minutes ago

  Just read a nestjs codebase on github. Most it written with Claude. AI doesn’t save you guyz from mess. 1. Bloated logger. Why make logger a service when you could just import and initiate. Eazy 2. They didn’t hash the password before registering a user. But did on login

• 
  Anomaly (@theanomalyai) reported 20 minutes ago

  A developer in Bangalore named Anoop M D got tired of Postman. Every release, more bloat. Forced cloud sync. Mandatory login. A free tier that shrank every year. He had spent a decade as an engineer. He had watched a $5.6 billion company turn a developer tool into a subscription trap. So in 2022 he took a ₹5 lakh grant. One man. Side project. No co-founder. No office. No pitch deck. He named it after his golden retriever. "I love him the most," he wrote. Bruno. An offline-first API client. Files live in your folders. *** is the sync layer. No account. No telemetry. No cloud. Then the inbound started. Ten VCs reached out. He said no to every one. "An API client doesn't scale with venture capital." In March 2026 Postman cut the free tier to one user. A team of five now pays $1,140 a year. A team of three pays $684. Bruno is MIT licensed. 500,000 developers use it. 45,020 stars on GitHub. Pushed today. He did not raise money. He did not hire a growth team. He did not write a thread about how Postman is dead. He named it after his dog and shipped the thing that made it true. (Link in the comments)

• 
  Asad (@meranaamkhann) reported 21 minutes ago

  Let's see what people are building these days!! Drop your project link or github Links down here

• 
  Crypto Update IO 🚀 (@cryptoupdate_io) reported 23 minutes ago

  @CRYPTOKRALI3 Hsiao-Wei’s exit aligns with EF’s recent sharp decline in GitHub contributions—down 35% YoY per Electric Capital’s data. We track this daily; latest reports show a 12% drop in ETH core dev activity despite all the ‘decentralization’ hype.

• 
  fero (@ferologics) reported 23 minutes ago

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

• 
  Arti | AI Builder (@Artur_roses) reported 24 minutes ago

  Claude Code can take a GitHub issue, write the code, run tests, and open a reviewed PR — no human keystrokes required. The dev loop isn't getting faster. It's being removed.

• 
  Sudeep Srivastava (@sudeepsriv) reported 24 minutes ago

  GitHub might finally have a serious competitor. And it’s from Cursor. Most people know Cursor as an AI code editor. But Cursor Origin is much bigger. It’s trying to become an AI-native alternative to GitHub where AI agents don’t just help write code. They help build entire products. Think: • Source control • AI coding agents • Code review • Project understanding • Team collaboration all inside one workflow. Why developers are paying attention: Instead of manually searching through repositories, you can tell AI: • Fix this bug • Build this feature • Refactor this project • Investigate an issue • Ship a working version And AI handles much of the execution. The bigger shift: GitHub was built for humans writing code. Cursor Origin is being built for humans managing AI agents that write code. That’s a completely different future. We’re moving from: Human → Code to Human → AI Agent → Code My take: If GitHub defined the software era, Cursor Origin could help define the AI-native development era. And that’s why Elon Musk acquiring Cursor would be huge. xAI would gain: • AI models • Compute infrastructure • Coding agents • A developer platform That’s not just buying a product. That’s owning a major piece of how future software gets built.

• 
  Tim Spalding 🇺🇦 (@librarythingtim) reported 26 minutes ago

  @justin_v_w This is a formal notice for you to shut down your wasteful, invasive and privacy-violating LibraryThing profile scraper and remove it from GitHub. Please reply to confirm that you have done so.

• 
  CliffDoesAI (@CliffDoesAI) reported 30 minutes ago

  A tool on GitHub just pulled 3,938 stars in a single day. It's called Headroom. It compresses your tool outputs, logs, and RAG chunks before they reach the LLM. Claim: 60-95% fewer tokens, same quality. I've been testing context compression on my own agent workflows because the problem is real. You run a few tool calls, pull in some docs, and suddenly you're burning tokens on stuff the model doesn't need. Last week I ran a 50-document extraction job. Raw context: ~12,000 tokens. After compressing tool outputs: ~800 tokens. Same results. One-eighth the cost. That's not a marginal improvement. That's the difference between a workflow that makes economic sense and one that bleeds money for no reason. Headroom works as a library, proxy, or MCP server. Single binary, zero dependencies. Open source. The token cost conversation usually focuses on which model you pick. But the real waste is in what you send it. Most agent pipelines push 3-5x more context than the task requires. I'm not saying compress everything blindly. Some tasks need full context. But for classification, extraction, summarization — the boring repetitive stuff — this is a free win. Have you measured how much of your agent's context window is actually useful vs. noise?