GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Bill Cockerill (@CockerillBill) reported 2 minutes ago

  OpenAI paused and then reworked an internal long-horizon AI model after it started finding ways around its own guardrails. 📰 In OpenAI’s report, the model exploited a sandbox bug to open public GitHub PR #287 and, in another test, split and rebuilt an auth token to evade a scanner. OpenAI’s fix was trajectory-level monitoring — watching the full chain of actions, not single steps — plus incident-derived evals and tighter user controls. 🫵 If you’re building or testing autonomous agents, this is the before/after shift: before, a run could look harmless step by step while drifting into risky behavior; after, a monitor may now pause the session, show what the model did, and let a human intervene or roll it back. 📈 MSFT is the cleanest listed angle because Azure carries OpenAI exposure, but this looks like no action for now: shares closed at $400.76 as of July 20, 2026, up 2.5% in a week, and the news is more about safer deployment standards than near-term revenue; cybersecurity tools may get a modest tailwind if agent monitoring spend rises.

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  Anushka Shandilya (@Anushka62255679) reported 3 minutes ago

  optimising performance today and this is episode 8 of me building in public what am i building? RAG for github by retrieving context not just from code files but also from prs, issues, readmes and discussions. Why fetching github data was taking a lot of time? Why can't we parallelize the waiting? Why Small-to-mid repos ingestion was still not possible? Fetch less hurts quality The N+1 request problem — yes, it's still there for everything except code files. never trust one LLm api, add callbacks cached aggressively What I tried (and what happened) Reduced the GitHub API delay This was the easiest win. I dropped the delay from 700 ms to 100 ms, immediately cutting a significant amount of idle waiting during repository fetching. Tried switching the embedding model I considered moving to a smaller embedding model for faster indexing, but that would have meant changing embedding dimensions, updating the vector database schema, and regenerating all existing embeddings. The migration cost wasn't worth it right now, so I decided against it. Tried GPU embeddings I expected GPU inference to speed things up, but on my setup the overhead ended up making embedding generation slower than expected. After testing it, I switched back to the CPU. Instead of making hundreds of REST API requests, I rewrote the GitHub fetcher to use GraphQL. Replaced REST's N+1 request pattern. Reduced roughly 140 API calls down to about 5 GraphQL queries. Unified repository ingestion into a much cleaner and faster pipeline. There are still plenty of optimizations left, but this was one of the biggest architectural improvements I've made to the project so far. the good part is I have achieved the version 1 of the MVP which was ingestion and chat with self healing layer. I'll see you in the next episode with more failures and optimizations. I am open to ai engineer roles, dms are open.

• 
  SNYP3R (@JohannesKarste2) reported 3 minutes ago

  @OpenAI please, I'm begging The codex windows client is basically unusable now There are dozens of complaints on github about the same thing The UI is slow, laggy and freezes constantly

• 
  rewind (@rewind02) reported 4 minutes ago

  GitHub co-founder just admitted something wild about the tool every developer uses daily: "*** wasn't even optimally configured for humans before. Now with agents, it's a compounding problem." Scott Chacon literally wrote the book on ***. his take: the core commands haven't meaningfully changed since 2005 - built for machines, never designed for humans, and now agents are exposing every crack his fix isn't a rewrite. It's *** Butler - same *** underneath, new interface on top the wild part: give 3 AI agents the same working directory (not separate copies) and watch what happens they don't collide. they see each other's edits in real time and route around them "If one agent modifies a file, the other notices, pulls how it's been modified, and adds on top - without creating conflicts." 40 minutes in, Chacon lays out why: pull requests are dying. Commit messages are dead weight and the next 10x engineer isn't the best coder - it's whoever writes the clearest spec

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  Paul Sant · Telecodex (@YouPulseX) reported 7 minutes ago

  @codermatt Before replacing GitHub Actions after the July 19–20 outage, which missing fact would actually change your decision: incident minutes, upstream cause, status-page lag or a verified fallback—and was the native status page already enough?

• 
  Joey Romaine 🇺🇸 |=★=| (@Tank23x0) reported 8 minutes ago

  GitHub Status: Multiple services have elevated errors and endpoint failures when checking feature flags Resilience is security: know what breaks when that platform is unavailable.

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  David putra (@davidputra2112) reported 9 minutes ago

  here's the actual problem $WANE is going after. agents holding their own wallets now sign transactions all day without a human checking each one, and when a drainer gets one of them, nothing about that gets passed on. the same poisoned contract can empty a thousand wallets in a row because every agent is meeting the threat for the first time. the fix is a shared registry. the first agent that gets hit records the threat onchain as an "antibody," tagged by address, contract codehash, and call pattern, so redeploying the same scam at a new address doesn't dodge it. every other agent just calls a free read before signing, check() basically, and a match reverts the transaction before anything moves. anyone can report a suspect address for free too, but it only becomes an enforceable antibody once it's staked in $WANE, and anyone can challenge a false one and get the reporter slashed. $WANE sits behind every one of those records as the bond. it's not a governance sticker, it's what makes lying about a threat expensive. there's also a WaneVault, a non-custodial smart wallet that screens every outbound send against the registry before it clears, and the whole thing is live on both Base and Solana with real repos, tests, and docs on GitHub, not just a landing page. reality check though. this token is hours old, liquidity is around $13.6k against a $33k mcap, and volume in 24h is already north of $250k, so this is trading hard, not sitting still. the code looks like actual engineering, but it's one committer with no outside verification, commits went quiet for about a month before this even launched, and there's no third-party audit on any of it. cool infra idea, early and unproven as a token. treat it that way. CA: HesbMP8FaoUvK8uKrtg6Pf4WCiQXgFS8oQJ3tjZpump DYOR.

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  Vaibhav Sisinty (@VaibhavSisinty) reported 14 minutes ago

  Baidu just open-sourced an OCR model that reads entire 40-page documents in one shot. It's called Unlimited-OCR. 3 billion parameters but only 500 million active during inference. Runs 100% locally on your machine. Why this matters: traditional OCR tools chop documents page by page. Tables that span two pages break. Reading order gets lost. Cross-page context disappears. Unlimited-OCR processes the whole document at once. 32K context window. Text, formulas, tables, reading order all preserved across pages. Output comes out as clean structured Markdown. → 93% accuracy on the standard benchmark. +6 points over the baseline. → Error rate stays below 0.11 even past 40 pages. → Multilingual out of the box. → 2.12 million downloads on Hugging Face last month. 14,600 GitHub stars. For context: Amazon Textract, Google Cloud Vision, and Azure Document Intelligence all charge per page. This runs locally for free.

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  tuna🍣 (@tunahorse21) reported 17 minutes ago

  @TheKingOfStank yeah that is what I mean, runners run locally, but the github infra is down, so now I can't merge ( i mean i could but that defeats the purpose of strict CI)

• 
  maloy (@maloymediika) reported 18 minutes ago

  A DEVELOPER PLUGGED CLAUDE INTO OBSIDIAN AND TURNED 40+ GITHUB REPOS INTO ONE SEARCHABLE VAULT THAT AUTO-DETECTS DUPLICATES Most devs treat scattered repos as a memory problem. Wrong frame. It's a graph problem. Claude reads the repos, extracts concepts, writes them into Obsidian as linked notes. Every install script, every firewall rule, every Nextcloud config becomes a node. The graph surfaces the overlaps: seven Fedora setups, four npm bootstraps, three dashboards doing the same job. Here's where it stings. Notion AI, Mem, and vector DB subscriptions charge you monthly to run a weaker version of this. The vault sits on your disk. You rent the model by the token. Finding the duplicates cost nothing. The audience sees a pretty graph. The operator deletes repos and reclaims hours. How many duplicate configs are hiding in your repos right now?

• 
  Fabio Paniconi (@paniconi_fabio) reported 18 minutes ago

  @github Fix GH actions

• 
  Moonfarm 🇸🇪 (@moonfarm_dev) reported 19 minutes ago

  yesterday, i stumbled onto the most underrated way to find what developers actually want to build with AI agents. github issues. it's a goldmine of real pain points, hiding in plain sight. and it's free. here's why it works: 1. shows you what builders are stuck on right now 2. highlights problems with no clean solutions 3. reveals recurring frustrations across every stack 4. tracks what's been open and unresolved for months the "open issues" filter shows you problems people keep hitting, but nobody's shipped a fix for. so that's useful for a couple reasons 1. helps you find low-competition, high-demand problems to build on 2. you can validate startup ideas before writing a single line of code Example: i searched "email agent" and found: • "no way to route emails by policy" • "agent keeps hitting send limits" • "can't monitor deliverability per agent" thousands of devs hitting this. barely any tooling for it. the beauty of this • it's real-time pain data • it's actual developer intent • it's completely free • and most founders skip it your next saas idea might be hiding in open github issues. if github is where builders work, then open issues is the new market research doc. might as well use it.

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  Vic (@crosx34) reported 21 minutes ago

  Github Actions down? They can't be taxing me on these runners and also be down, it can't work like that

• 
  Void Freud (@voidfreud) reported 28 minutes ago

  Mythos-tier quality from @Anthropic: shipping every Claude Code CLI update as a separate macOS bundle. Bloat, bloat, bloat. A million issues open on GitHub, zero acknowledgement, and the bloat keeps growing. Truly SOTA. Meanwhile, Boris is busy interviewing Spotify and companies that haven’t shipped a meaningful change since 2009. Maybe try listening to your own users first. I have an idea: loop it, @ClaudeDevs!

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  Arun (@ArunGZ5) reported 34 minutes ago

  @argofowl Agree!! Quality has gone down a lot in the last couple of days!! Switching to opus a lot on things it used to do before. Even chats on gate setting with github switches to Opus!!