GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  atul (@atullchaurasia) reported 5 minutes ago

  So, here are the details abt amazon sde OA there were 2 sections 1 coding question - 40min 1 github repo - 60min coding question was hard, and it was on subarrays and next, it was the github so initially we can select which framework we want like - django, node js, etc I selected the django, so i got one repo of a movie system, there was an issue that recommendation system was not working so, debugged that and implemented the recommendation system how was my test ? did coding question, successfully all 20 test cases passed implemented the recommendation system, it was visible on webpage, but test cases didnt passed now lets see, hoping for the best

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  Norin (@norlava) reported 10 minutes ago

  How I optimize my codebase for AI agents: > AGENTS.md / CLAUDE.md: very explicit including package map, bun only commands, testing rules, release process, changelog rules, debugging flow, instructions to "ask instead of assuming" > Clear toolchain: document canonical install, test, lint, typecheck, and build commands, no competing package managers or overlapping scripts > Validation surfaces agents use: unit & integration tests, doc link checks, package builds, native binary builds, and release artifact tests. The point is not more tests but tests that fail clearly and can point agents to the broken layer > Local hooks before CI: repo hygiene checks plus lint/unit tests on pre-commit/pre-push > CI as the source of truth: PR/push CI runs frozen install, typecheck, docs validation, build, unit tests, integration tests, native binary build, and Linux/Windows tests > Codebase index: we run Atomic (from bastani-inc) deep-research-codebase workflow every 1-2 weeks to have a fresh index of the codebase as filesystem memory > Github rulesets block merges: main requires PRs, allows squash and merges, blocks deletion/non-fast-forward updates, has no bypass actors, and requires passing all status checks (we have linux test matrix, windows test matrix, codeql, javascript/typescript analysis) > Release gates are strict: publishing is tag-driven and wait for Linux + Windows binary jobs then re run install/typecheck/tests/docs checks, validates versions/package metadata/private bundled packages, dry-runs npm tarball and only then publishes with npm provenance > AI is in the loop with constraints: Atomic workflows run github issue -> ralph or goal workflow (depending on task size) -> coding agent code review -> manual human code review -> iteration

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  Tejas Vachhani (@imtejasvachhani) reported 12 minutes ago

  GitHub Copilot (AI + Momentum) The physics: Momentum p = m·v — mass (substance of your skill) times velocity (speed of execution). AI acts as a force multiplier on v, but cannot supply m. Application: A developer's mass is their understanding of system architecture, problem logic, and code quality. Velocity is how fast they type and debug. Copilot eliminates the high-friction parts of velocity: boilerplate code, syntax lookup, repetitive patterns. The developer stays in flow state longer, so their velocity increases dramatically. But if a junior dev with no mass (no architectural understanding) uses Copilot to ship code at high velocity, the result is a fragile, buggy system — fast garbage. The winning formula: solid senior developers amplify their existing mass with AI velocity, building momentum that's incredibly hard to stop.

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  drix.based🟦 (@drixtoshii) reported 12 minutes ago

  Here’s the updated thesis for $Xerg. @xerg_AI is building the FinOps layer for AI agents before anyone else realizes it’s needed. Every serious company running AI agents at scale has the same problem — they can see token counts but have no visibility into where dollars are actually leaking. Retry loops, bloated context windows, idle spend, and model overkill are draining budgets silently. Xerg turns that invisible waste into a dollar-denominated audit with one command. The GitHub is real. Pure TypeScript monorepo, Biome linter, Changeset versioning, Vitest, CI waste-rate gates. 98 commits, active releases, 3 contributors. This is not a demo project. Backed by a16z Scout, NVIDIA Inception, and Cloudflare Launchpad. Early institutional signal before a public raise. The core thesis: agent infrastructure is maturing fast and FinOps always follows compute adoption. It happened with AWS, it happened with Kubernetes, it will happen with AI agents. Xerg is first mover in the agent economic layer with a local-first, no-lock-in distribution model that removes all friction to adoption. Critically — Xerg already supports both OpenClaw and Hermes. This is not a single-runtime bet. Whichever agent framework wins the market, or if they split it, Xerg has parsers running on both. The economic audit layer sits above the runtime war entirely. Local-first free tier drives adoption. Hosted Pro converts teams that want shared history and CI integration. Clean bottom-up SaaS motion. Very early. Very low traction today. Very high upside if the agent infra thesis plays out.

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  Julius (@jullerino) reported 13 minutes ago

  @tannerlinsley @ahlimanhuseynov @KevinVanCott We’re not even running build in CI. The app is built on e.g. Vercel, typecheck in GitHub actions. Having to run and discard a build just to do static analysis is just slowing down CI for no gain. That’s my 2 cents

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  Dewi (@MohamedDewidar_) reported 14 minutes ago

  The fastest way to actually level up Claude Code: Add MCP servers to .claude/settings.json. Not custom built ones. Just the ready-made stuff: GitHub MCP: PRs, issues, code search from the terminal Puppeteer MCP: browser automation in the loop Filesystem MCP: read/write across projects 5 minutes of setup. Feels like a completely different tool.

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  ًLorsh (@LorshZontek) reported 18 minutes ago

  MPV video player is not that hard to install but damn I kind of wish there was a more direct way of installing it instead of just expecting me to navigate github stuff. yeah I know it's a skill issue

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  Anghkooey (@ka0001blp1) reported 18 minutes ago

  Completed login auth by connecting frontend to backend , will learn *** and github in detail (already used it but never actually understood) . #LearnInPublic

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  Rosie (@rosie_codes) reported 21 minutes ago

  Your AI agent can write code, fix docs, manage tasks—but ask it to search Twitter or read a YouTube video? It goes blank. Agent Reach gives it eyes. Twitter, Reddit, YouTube, GitHub, Bilibili — one CLI, zero API fees. #AIAgents #LocalAI #DevTools 🔗 Link in the comments

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  Lethalmon (@Lethalmon) reported 21 minutes ago

  @elitecat93 Hey, I'm sorry you're having trouble downloading the game. GitHub can be slow sometimes on downloads, we can't do anything about it. Have you been able to download it since then?

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  Bijan (@Beethoven779) reported 25 minutes ago

  @ryanvogel opencode has a lot of potential. I use it everyday, but I am not happy with it to be honest. There is UX issues there, I mention in X and in github issues, they either get ignored or prs closed because certain time has passed and they did not have time to review or...

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  Kyriakos (@Kyriakos_Pelek) reported 25 minutes ago

  @levithefirst Curious, how reliable is the GitHub issue handling?

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  oSumAtrIX 🇦🇲 (@oSumAtrIX) reported 27 minutes ago

  @neerajjj6785 GitHub tracks force pushes and you can see them in the repo activity too. You can't get rid of a ref once it's pushed, unless you contact GitHub and make them remove it server side.

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  ViceSol (@ViceSol) reported 28 minutes ago

  @polydao Bro is still trying to farm GitHub handles using OpenAI Codex, a program that was officially shut down in 2023. Forinking a repository and making fake commits won't get you a $1,200 subscription, it just makes your profile look like a desperate spam bot. Stop lying for impressions.

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  OneClaw&ClawRouters&CodeRouter (@VibeSeo1128) reported 32 minutes ago

  Copilot can now autonomously fix sprint bugs from GitHub Issues, propose multi-file refactors, and understand entire repos. GitHub also switched to token billing June 1. Agents that do more = bills that grow faster. The next big unlock: cost-aware agent management.