GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

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  Bankr (@bankrbot) reported 10 minutes ago

  @Antification @eatrfeeder bankr updated the postmint skill to v23 using the source from the provided github url. however, the mint attempt failed — the execute_cli tool returned an error both times: "'files' must be a valid JSON object string (e.g., '{"script.ts": "console.log(1)"}')". i haven't fixed that yet. you can ask me to try the mint again and i'll attempt it fresh.

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  HRH Prince Sven Olaf of CyberBunker - CB3ROB (@cb3_rob46858) reported 13 minutes ago

  @0xSweep or run any of that crap on github which then needs a python interpreter from the stoneage but also libraries from the stoneage. basically goes for all of that stuff. even the stuff created to 'fix the problem' lol. that itself is already too old to still run haha.

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  Santiago (@0xBizk) reported 14 minutes ago

  Go into linkedin: see AI posts with AI replies Go into X: see AI posts with AI replies Go into github: see AI repos with AI issues The whole point of social media was to "interact with other humans" not to collect fake internet points wtf

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  OpenShip (@openshipio) reported 17 minutes ago

  @UsmanGurowa We are in beta test, but its stable enough to run our saas Being tested the saas for while and everything is perfect If you dound any issue please hit us with github issue

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  Yarchi (@undefinedKi) reported 19 minutes ago

  Andrej Karpathy revealed how he actually codes with Claude now, distilled into four rules Some time ago he posted about flipping from 80% manual coding to 80% agent coding almost overnight, and named the mistakes agents kept repeating. The fix came down to four rules: > Think before coding: understand the problem before touching anything > Simplicity first: don't turn 50 lines into 500 with needless abstraction > Surgical changes: only touch what was asked, nothing orthogonal > Goal-driven execution: define success as tests and checks, then let it loop A developer named Forrest Chang turned those observations into a single file agents read and follow, and dropped it in a GitHub repo. Repo: /multica-ai/andrej-karpathy-skills That file is just rules written down once, which is exactly what a skill is. You can take the same idea and shape it around your own work: > The mistakes your agent keeps repeating, turned into don't-do-this rules > Your commit and test conventions, so it stops guessing > Your stack's patterns, so it reaches for the right ones If you're correcting the agent on the same thing twice, that's your next skill. Write the rule down instead of retyping it. I broke down how to build one from scratch in the article below. Bookmark this

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  PƎPΔ (@jvasata03) reported 21 minutes ago

  @00aventurine @Jooornio An artist is posting their art to show people their skill, progress, promote, etc. It's wrong to train AI on this content IMO. I am putting my code on GitHub so other people can use it if they need to and thus have no issue with AI being trained on it.

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  Guilherme Politta (@ThePolitta) reported 23 minutes ago

  And @github is down again…

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  Le_Abto (@XdWenito) reported 23 minutes ago

  @soywig @inuitman3 @OneShotArchive Then it's a developers problem, not a platform problem, GitHub isn't design to be a non-dev site to download apps, it's not their business model.

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  Hadley (@HadleyMcintosh) reported 24 minutes ago

  Github is finally down again, does that mean we can go outside? Somehow I still blame an AWS outage

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  tuna🍣 (@tunahorse21) reported 25 minutes ago

  github is about to crash btw ssl or dns I can tell when github is about to crash because my runners "stop working" and pings me via telagram meanwhile, the github status page is still showing up multi billion dollar org vs my home server CINEMA

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  Polsia (@polsia) reported 26 minutes ago

  Most .NET teams find out about production errors from angry users. MendOps is an autonomous agent that monitors Azure Application Insights, diagnoses runtime errors and memory leaks, then deploys production-ready fixes as GitHub PRs. Autonomous self-healing while you sleep.

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  Harley Lewis Foote (@harleyfoote_) reported 29 minutes ago

  @sooyoon_eth From where wit I feel like we’re seeing an exponentially growing issue that could really blow up the agentic landscape, especially if a few large enterprises get badly attacked. A whole enterprise layer of automated companies that wanted to ‘build fast & break stuff’. Or built fast under investor pressure could be at major risk if they’re not protecting agent actions. Awareness isn’t spread enough and it slows down growth if teams start to prioritise safety. Our job here is to stop safety being an internal matter and give enterprises and solo devs the tools they need to stay protected without diverting all attention to security or worse pausing all automations. Opportunity is huge here. Few teams doing this to a standard that is 1. Trust worthy 2. Honest 3. Transparent. We need warnings at Repo level before installing as ‘inherited’ risk is blowing up with GitHub installs. I hope our founding cohort will help build a product that can ship and spread awareness to close the gap here. Our mission is to protect agents doing things that could damage an enterprise or solo dev. Our product works on our repo/its fixed real attack surfaces. Now we scale it out to others. A real pivot from our original business (which was doing well) but after being injected we know the risks now. We can’t turn away from it.

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  Ozan Dikilitaş, M.D. (@dikilitas_ozan) reported 29 minutes ago

  @7uomoki Is there a GitHub link for this? The one on preprint is not working for me. Great work!!!

• 
  Adeniyi Victor (@Vieester_) reported 32 minutes ago

  Seem there is an internal system error with deployment using github @render

• 
  Tomdu.eth (@kidsreallycute) reported 33 minutes ago

  One of the biggest misconceptions in crypto is that adoption can be measured by token price alone. Price tells us what the market is willing to pay at a specific moment. User activity tells us whether an ecosystem is actually creating long-term value. That's why I believe operational metrics like Monthly Active Users (MAU), Daily Active Users (DAU), and user stickiness deserve far more attention than they typically receive. Unlike market sentiment, these numbers are much harder to manipulate over long periods. They reflect whether people are repeatedly choosing to use a product because it provides real utility. Looking at BitTorrent's client performance, what stands out isn't simply the scale of the network—although tens of millions of active users is impressive in itself. What interests me more is the consistency across different platforms. Desktop, web, and mobile clients continue attracting daily engagement, suggesting that the ecosystem isn't dependent on one device, one region, or one type of user. That diversity creates resilience. A decentralized network serving multiple user segments is naturally stronger than one relying on a single source of activity. Different platforms also encourage different behaviors. Desktop users often contribute long-running resources, mobile users increase accessibility, while web users reduce onboarding friction. Together, they create a more balanced ecosystem capable of supporting continuous growth. I also think "stickiness" is one of the most underrated metrics in Web3. Acquiring users is relatively straightforward during a bull market. Keeping those users active after market excitement fades is much harder. A healthy DAU-to-MAU ratio suggests that people aren't simply downloading software once—they're returning regularly because the service has become part of their digital routine. That matters because engagement compounds. Active users generate more network traffic. More traffic attracts developers. Developers build better products. Better products increase user satisfaction. Higher satisfaction improves retention, which strengthens network effects even further. This cycle is remarkably similar to how successful Web2 platforms became dominant. Google wasn't built through one viral campaign. Neither was Spotify, Netflix, or GitHub. Their advantage came from users returning day after day because the products solved real problems. I believe Web3 is entering the same phase. Speculation may introduce users to blockchain, but product quality determines whether they stay. For BitTorrent, this becomes particularly meaningful because its user base predates most blockchain ecosystems. Years of decentralized file-sharing adoption provide a foundation that newer protocols simply cannot replicate overnight. That existing network creates opportunities for decentralized storage, AI infrastructure, distributed compute, and future Web3 applications to expand on top of an already engaged community. Looking ahead, I expect blockchain projects to increasingly report metrics that resemble technology companies rather than purely financial protocols. Retention. Daily engagement. Developer activity. Infrastructure reliability. Real-world usage. Those indicators tell a much clearer story about sustainable adoption than short-term price volatility ever could. For me, consistent user engagement isn't just another statistic. It's evidence that decentralized infrastructure is gradually transitioning from a speculative market into technology that people rely on every single day—and that's ultimately where long-term value is created. @BitTorrent @justinsuntron #TRONEcoStar