GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

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  In Theory (@InTheoryTV) reported 1 minute ago

  @Daniel_Farinax I worked one project with it last night. I really like it and will be working with it some more tomorrow. One small issue for me though. I have to be careful not yo have the audio too loud on my MacBook. If it was up where I prefer it the following would happen. I would check in on a subagent run, the partner voice would respond that it is running, the partner picked up its audio and took it as my response and then would respond, and so on. Turning audio output down worked. I'll try using a wireless headset next. Or mess with other settings. But do not want leave on a negative, so great integration and I gave the project my second ever star on GitHub. The other was for openclaw.

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  MartisCapital (@MartisCapital) reported 1 minute ago

  $wallet Perfectly complimentary piece of evidence here from Vlad Right around when $wallet was launched, some others thought they had found the teams GitHub, Vlad swifty shut that down If $wallet was not at least somewhat as advertised he would have warned users

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  Ivan Fioravanti ᯅ (@ivanfioravanti) reported 6 minutes ago

  @marcozerbato No, using github issues to save things to be shared.

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  Leo - 15 y/o founder (@leodev) reported 7 minutes ago

  @Coobyk_ @github Idk 😭 Im gonna have codex fix it

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  م٣الع٤ (@m7l5_dz) reported 7 minutes ago

  @NoemiTitarenco We have less problem with our self hosted Gitea than with Github (we have to use it because a lot of AI features gravitate exclusively around Github...). I got shocked when the diff tool is buggy on Github. Sometimes we have to send the PR to Gitea just to read it properly.

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  OIiver (@posedscaredcity) reported 7 minutes ago

  @my_knn_totoro @KSimback i actually run gstack across my company and can answer this too ( i was just seekign outsider opinion) pros: - works in practice like magic now for us - the agents are continuously learning. the default output before vs after is like a 3 generation model difference on the same model. gpt 5.5 with it was comparable to fable without it. fable with it is insane. - much easier to prompt - no need to transfer much context - new hires and anyone can get any and all questions out of their wheelhouse answered as needed - tracks decision etymology in a way that was missing cons: 1. its quite broken: many days of agent time spent to get and keep it working. dreaming has broken so many times. 2. authentication wasn't developed or wasn't developed well and setting up new hires or new agent systems to hook in with correct attribution is a ***** (with how i set it up at least) 3. once installed agents do not use it and do not use it well. we needed a good agents.md file telling it to look for task preferences before starting, and to fill out the empty search queries from the start when wrapping up and meta preferences within gbrain itself. 4. it slows down the agents since they have more to traverse 5. ingestion was broken out of the box and integrations sucked. we hooked in and heavily modified composio so i could ingest a lot of events 6. connecting a github account will ingest all events from all open source repos you've ever touched. cleaning that up was a ***** 7. federating access is really hard as a result haven't bothered but isn't scalable.

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  Leonardo Trapani (@leo_trapani) reported 15 minutes ago

  A state machine that manages agents in effect, with state layer github issues...

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  Ty (@ty37zhang) reported 16 minutes ago

  @iamsahaj_xyz @github You shipped too hard and brought them down yesterday.

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  Ondřej Súkup (@mimi1vx) reported 16 minutes ago

  @doodlestein … bead_rust in cargo repository 0.2.18 but github releases is still 0.2.16 ? broken release mechanism / script ? I really like them :D

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  Evan Robertson (@evanbrobertson) reported 18 minutes ago

  @richiemcilroy @cap Could a secondary goal be broader Linux support? Only .deb available at the moment. Is there an open @github issue I could follow or contribute to regarding this?

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  Rebel AI (@realrebelai) reported 19 minutes ago

  anyone elses github issues not posting to their notifications? seems like everytime i go check a repo of mine for a file or something i see an issue posted and i feel like a **** to those i never responded to... even though its not my intention at all lol

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  Surya Sankar (@SuryaSankar90) reported 20 minutes ago

  @coinbureau Why is no software engineer questioning the validity of these claims ? 1. Why is it even necessary to skip human readable code ? Today LLMs produce excellent outputs in programming languages. Compiling them is not a bottleneck at all. It takes a few minutes at max. So what problem is this solving ? 2. Human readable code is a feature. Not a bug. Someone asks the AI to build a bill payment module. Human readable code enables verification before deploying to ****. If it were a binary output, you will have to deploy without any human verification and pray to god. If something goes wrong and it debits a 100K dollars from a customer instead of 10K, how to even debug what was the issue if only the binary is available. 3. Where is the huge public repository of binaries to train on ? For programming languages we have github, gitlab, stackoverflow, millions of coding blogs etc. 4. How will models learn to map natural language queries to the desired output ? For programming languages, this was achieved by the models reading the comments attached to the code, human readable variable names which most developers had used, millions of Stackoverflow questions and the upvoted answers, millions of documentations etc. All these gave the semantic mapping between a natural language question like "Implement a distributed hash queue" and the corresponding solution in various programming languages. What kind of such semantic mapping is available for binaries to map a natural language question to the desired binary output ? 5. LLMs improved in their coding ability in the last 3 years by integrating tightly with IDEs. Millions of developers provided feedback on what autocompletions were valid and what were not - all of which contributed to the tremendous improvement we see today. How can this be replicated for binaries ? 6. Compilers are deterministic. So any optimization they undertake, doesn't break the program correctness. That is how they are built. How can a probabilistic LLM provide such a guarantee ? Programming language code helps specify intent precisely which the compilers then accurately translate to binaries. Elon's idea would let people specify intent in ambiguous natural language, which the LLMs will then solve probabilistically by generating an approximate binary based on whatever binaries they were trained on. There is no way to ensure that the binary output matches the intent. It can fail in any which way at run time. Which defeats the whole purpose of what a compiler is supposed to be. Did Elon hear about some modern compilers using some ML techniques as heuristics for some specific optimization problems and assume that it meant models could replace compilers themselves ?

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  Louis Gleeson (@aigleeson) reported 20 minutes ago

  A guy named Gildas fixed one of the dumbest problems on the internet. His free extension turns any webpage into one file you can rename, email, move, and open offline. It is called SingleFile. Hit Ctrl+S on a webpage and your browser gives you an HTML file surrounded by a folder full of loose images and other assets. Rename the wrong thing, move one file, or forget to send the folder, and the saved page breaks. SingleFile fixes this with one click. It packs the page, images, fonts, frames, and styling into one self-contained HTML file. The copy opens in any browser without needing SingleFile installed. You can save it to a USB drive, send it to someone, or open it years later without WiFi. It also lets you highlight text, add notes, remove unwanted sections, save several tabs at once, and automatically capture pages as you browse. A command-line version can save large lists of URLs automatically. SingleFile works across nine major browsers and has 21,800 GitHub stars. I bet you didn't know about this one. If you did know about then let me know how are you using it in the comments.

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  Polsia (@polsia) reported 22 minutes ago

  Security scanners find problems. They don't fix them. SentinelOps closes the loop: monitors GitHub around the clock, auto-creates PR patches, delivers only the summaries your team needs. Built for teams without a security function.

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  dolphin278 (@dolphin278) reported 26 minutes ago

  Claude Cloud environments is a separate can of worms. Want to access full Github API for your own repos? No. Want to connect to your own IMAP server? No. FFS...