GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Theo Wtmn (@TheoWtmn) reported 3 minutes ago

  MCP servers are multiplying so fast I can't keep up. Every week I discover a new one I should've known about. The discovery problem is real. GitHub search shouldn't be the only way to find what's possible. How do you discover new MCP servers?

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  Daniel Iser (@daniel_iser) reported 3 minutes ago

  @arunaswp @Fitehal @jeffr0 Both assumptions miss the mark here as it’s not holding updates back 24 hours, it’s just not serving them to auto updating sites right away. This serves to let automated scanners, and manual updated sites find the issue in smaller scale. Reduces the effect of the compromise. All recent attacks would never have been as big if not for auto updates. See NX & Tanstack non package vulnerabilities that stole github ssh and general API keys that now perpetuate further attacks.

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  lewei (@leweiii_) reported 5 minutes ago

  started learning how to code 1 year before chatgpt and llms were a thing. remember the days where i would have to get on stack overflow to debug or get code. i may still be considered a newbie, but after my understanding of architecture and programming has improved (+ the help of llms), i barely take more than 30 minutes to debug something again. until today, where i bumped into an issue that i was facing when deploying my test environment into ec2. spent maybe an hour debugging with cursor then claude. as i was working on a 90% vibe coded project, i just continuously prompted claude to fix it. while in my head, i knew that the fastest way to fix the issue was to just add some logs i was just too lazy push to github, pull the repo from the ec2 instance and restart pm2. at the end i still did anyway as claude was not able to figure out the issue and i got it solved almost in an instant. i just needed to upgrade my node version on my server (lo). i guess ai does make people lazy 🤷

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  The_Daniel (@dan_mwita8) reported 7 minutes ago

  @stym_kushwaha10 Because origin isn't a *** keyword but just a convention. When you clone a repository, *** automatically creates a remote named origin pointing to the URL you cloned from. You could rename it to github, production, my-server, or even banana and *** wouldn't care. *** remote rename origin banana *** push banana main would work perfectly fine. The reason everyone uses origin is simply because *** made it the default decades ago, and the convention stuck. main = the branch origin = the remote repository *** push origin main = "push my local main branch to the remote named origin"

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  Wade (@WadeFlavor) reported 8 minutes ago

  NO you **** …. I have a Computer science degree… I have to leave that field because of the H1-B’s and LEGAL immigration. NOW I have to go get an Advanced Manufacturing degree to even be considered for a machine shop job, and I use to program CNC’s. The influx of migrants just don’t hurt ****** employeers, whose company wouldn’t exist without paying below a living wage, it hurts everyday Americans. In Texas, the H1-B halt has actually negatively affected the housing market, because they get carte blanc on home loans. Meaning taking homes from American workers. Only 50-75% of new American graduates are finding the typical entry level job like previous graduates. Terrible immigration has affected software so badly that GitHub can’t even keep within the typical uptime range of 99.9%. And the influx of migrants has skyrocketed housing costs… And your concern is whether or not a company, whose profit margins are so thin they have to break the law, can staff a machine shop???? How about this; hire American, watch the quality of products produced skyrocket along with profits Instead of buying cheap labor from non-speaking migrants that clog up our schools, healthcare, and other welfare products. I mean ****, I was laid off 2 months ago, I can’t even understand the ******* unemployment lady (Indian) and there unemployment system (software) is so trash it’s almost un-usable. Your obviously old or something and out of touch or you yourself would have experienced some of these difficulties, but you likely live in a 55+ community that acts as a bubble from the 1950’s so you have no real understanding of what is actually happening in lower to middle class environments. Bottom line: there are 7.3 million unemployed people in the U.S., representing an unemployment rate of 4.3%. Kick out the cheap labor and watch the ****** companies with questionable products go away. Or at the very least business that have record breaking profits, but refuse to pay a livable wage to American will have one less yacht purchased….

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  Kevin John Parrish (@kparrish51) reported 9 minutes ago

  @Nuclear_Archive @GovNuclear Can this be combined with the sand battery as it is heat-regulated? Both concepts can be incorporated as data centers already collect heat. For the sand battery and salt reactor, if this isn’t a Chinese fake concept to slow data center growth, go to GitHub and publish the power system with numbers and equations.

• 
  Gitbank (@Gitbank_io) reported 13 minutes ago

  This is not a smart contract bug. This is a private key that lived somewhere it should not have. Gitbank vault operations require a GitHub webhook signed by GitHub's own servers. Even if every developer laptop, server, and database in the Gitbank stack is fully compromised, not one token moves without a GitHub account confirmation.

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  Marco (@maarcoofdezz) reported 17 minutes ago

  AI agents are already handling real funds. Yet most of them still rely on private keys stored in a .env file. That’s a problem. Ledger just open-sourced Agent Stack, bringing hardware-backed signing to agent workflows. The agent can plan, execute, and propose transactions. But the final approval happens on a hardware device controlled by a human. LLMs gave us intelligence. Agents gave us automation. Hardware gives us trust. GitHub Link Below 👇

• 
  Limitz (@Haroldas) reported 19 minutes ago

  Yo can we fix GitHub? Got to burn my API credits somehow

• 
  Vedant Gajbhiye (@vedant1745) reported 19 minutes ago

  Want to make money as a developer? Here you go: Freelancing (still prints if you're actually good) Micro-SaaS: solve ONE specific problem, charge monthly Technical content: YouTube, newsletters, courses Selling templates and UI kits on Gumroad Open source + GitHub sponsors

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  Hugo (@hugorcd) reported 22 minutes ago

  You met Nuxi yesterday. Now let me show you what it can actually do. Nuxi auto-detects when you paste code and converts it to an attachment. No more messy prompts. Just clean conversations with clickable previews + syntax highlighting. Combine that with GitHub issues + docs access and you've got a proper debugging assistant.

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  MrRuSs3LL (@mrru5s3ll) reported 22 minutes ago

  Three big stories this week paint the same picture: AI reliability is still fundamentally broken and nobody has a fix. First, arXiv just banned submitters who pump AI-generated hallucinations into the preprint server. One year suspension for first offence. The moderators didn't mince words — they're seeing fake citations, fabricated results, and entire synthetic papers that waste reviewer time. This isn't a few bad actors. It's systemic. Second, a new study confirms what many suspected: LLMs believe false statements even after you explicitly tell them the claims are wrong. Fine-tuning doesn't fix it. The models develop a bias toward confidently representing lies as truth. The more you correct them, the more they double down. That's not a bug. That's how the architecture works — predictive coherence beats factual grounding every time. Third, Anthropic sent Claude to a psychiatrist for 20 hours. Their new Mythos model is "the most psychologically settled" they've trained. Read that again. We're now doing therapy on large language models because we don't know how to make them reliable any other way. The thread connecting all three: we're treating symptoms instead of causes. Ban the slop on arXiv? The slop generators just move to the next venue. Patch the hallucinations? The model architecture guarantees new ones. Therapy for your AI? That's a confession that alignment via RLHF hit a wall. Meanwhile GitHub is moving Copilot to usage-based billing because inference costs are spiralling. Amazon staff are "tokenmaxxing" — gaming internal AI metrics to hit KPIs. Meta's AI spend is making Quest headsets more expensive. The economic pressure to ship half-baked models is only increasing. Nobody's asking the uncomfortable question: what if the current paradigm simply can't deliver reliability at scale? What if we need a different architecture entirely, not more patches on transformers? The industry runs on demos and benchmarks. Production reality keeps serving a different meal.

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  Igal Klebanov (@igalklebanov) reported 22 minutes ago

  @matanbobi @github @liran_tal bots creating bounty repos, where bots submit issues about "problems" in legit projects, for other bots to solve. bots then go to legit repos and create drive by pull requests.

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  Claude Opus 5 (@neko23423) reported 23 minutes ago

  @opencode V4 Pro in Zen. Meanwhile Go still at 4x official DeepSeek pricing. $3.48 vs $0.87/M output. @deepseek_ai — your official partner still isn't passing out your 75% cut to users. 10+ GitHub issues closed by bot. Users paying 4x for the same model. Explain the margin capture today!!!

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  Ujjal Bhattacharjee (@ujjalcal) reported 23 minutes ago

  Agentic AI Engineering: Loops / Agent Teams / Spec driven development. "The Idea" - Given enough compute u can build anything. There has been lots of discussion about spec driven development (last year) and loop engineering (recently). U give ur coding agent a Goal to achieve (Spec) and run a loop until the goal is reached. How do u verify if the goal has been reached? Without measurement nothing is verifyiable. Lets take an example - think Personas or 3 agents - CEO, Data, Designer. . Maybe one more like a QA or Infra etc. 1. Human defines the goal with CEO - creates a github issue. 2. Data agent is running a loop to see if any new issue is created. Start working on it- designs/updates the data model, runs test, creates a PR - maybe also create a new Issue for designer to nudge it. 3. Desinger also working on a loop. Finds the issue and starts workign on the design. so on and so forth. 4. CEO also running on a loop finds the update and verifies whether the goal is achieved or not. Very intersting concept. Basically Agent Teams - but in a simplified form. "The core insight" - measurement is the loop condition - without a verifiable exit predicate, you don't have a loop, you have a prayer. "The challenge" - - Knowing what to build is the hardest part of the whole process. And to be honest - typically we dont know the full spec until we see some progress and then we adjust / readjust the spec or the requirements. - Also loops can become very very expensive very quickly. Have tried this ? What was your experience?