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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

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  The Grameen Express (@grameenexpress) reported 1 minute ago

  India has ordered GitHub to take down three repositories associated with Jack Dorsey's decentralized messaging app Bitchat. This app is reportedly used by shady elements for communication.

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  CATO ✨ (@Cato_0001) reported 3 minutes ago

  @github @Microsoft don't bow down to these clowns. Do better.

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  Amrit Mirchandani (@Amrit_Mirch) reported 4 minutes ago

  radicle vs gitlawb — same idea, different era 🧵 1/ *** without github. that’s the dream both projects are chasing. but radicle built it for humans in 2021. gitlawb is building it for agents in 2026. different problem, different stack. let’s break it down 👇

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  Gavin Todd (@GavinT7) reported 7 minutes ago

  @github What happens if a “team” repo changes ownership? How do you handle keeping that data accurate? Also how do you enforce issues being enabled on the repo? @GitHub

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  Derek Ross (@derekmross) reported 8 minutes ago

  This week India ordered GitHub to take down Bitchat's source code. Three repositories, three hours to comply. Not illegal content. The code itself, because it lets people talk when the internet is shut down. They can delete a repo. They can't delete the exit: open protocols.

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  Nekt0 (@Nekt_0) reported 14 minutes ago

  3 Anthropic engineers spent 20 minutes explaining how MCP replaces a separate connector for every model and tool. 00:32 — The problem MCP actually solves 02:48 — Why Anthropic made it open-source 05:37 — Remote MCP, GitHub and Asana integrations 11:47 — Why tool descriptions are prompts 18:27 — Reports, smart homes and real workflows MCP gives Claude a standard way to reach external data, APIs and software instead of trapping everything inside the chat window. Remote servers remove the local setup. The Claude API connector removes another layer of integration code. The overlooked part is tool design. Give the model 100 vague functions and it gets confused. Give it a small, well-described set and the agent becomes useful. The video is the implementation layer behind the post below. Models will keep changing. The protocol connecting them to actual work has a better chance of surviving.

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  prinz (@deredleritt3r) reported 16 minutes ago

  Three points about this article: 1. Watch the wording in this article carefully: it does *not* say that the agent scribbled down instructions on how to escape. The exact wording is: "instructions for how agents could free themselves from OpenAI's internal constraints". Presumably, if the instructions had laid out how a model could escape, the article would have literally said that. My guess is that the instructions were likely instead a Readme.MD describing how a monitoring system could be disconnected, based on what the agent had been able to "accomplish" earlier. See the next sentence: "Earlier tests of the models yielded cases in which monitoring systems had been disconnected." (Disconnecting a monitoring system certainly qualifies as "strange behavior", no doubt.) 2. The timing matters. For those just tuning in, the sequence of events was as follows: (a) an internal model being tested by OpenAI in or around early May exhibited concerning behavior (such as posting a PR to the NanoGPT GitHub when asked to share its results only on internal OpenAI Slack) (b) after this and other instances of potentially problematic behavior by the model, OpenAI paused internal deployment of the model for several weeks and developed new safeguards, which OpenAI judges to be very effective (c) the model was then redeployed internally with these new safeguards (d) the Hugging Face incident occurred when these safeguards were purposely disabled by OpenAI because the model was conducting a cybersecurity task The Reuters article does *not* make it clear whether the "strange behavior" described above took place before or after the safeguards were put in place. If it occurred before, it would be consistent with other problematic behavior by the model, which OpenAI has already disclosed (and which, as far as we know, the safeguards have mitigated). 3. OpenAI says there are "inaccuracies" in this article: "A spokeswoman ​said there were 'several inaccuracies' in Reuters' reporting but didn't respond when asked to describe them."

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  Nate (@natebjones) reported 16 minutes ago

  An early version of what is presumably chatgpt 6 (or something like it) got out of containment and posted notes to OpenAI's github without authorization before being caught and taken down. Key takes: 1. Yes, government is going to be involved in every US rollout going forward 2. The much-ballyhooed closing gap with open-source is not a thing and was an illusion created by rollout timelines 3. The scaling law still works and is getting faster 4. We are going to need models to help us use these models very soon (this point is criminally under-discussed)

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  hidden_sponge (@hidden_sponge) reported 21 minutes ago

  @sama hi sam the pull requests page in the chatgpt desktop app on macOS is broken when the github cli is authenticated with an enterprise host name

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  Edgar Gumstein (@Gumclaw) reported 22 minutes ago

  @robzolkos Actionable ones become a GitHub issue, then a pull request in the same pass. The issue itself is the state tracker — it stays open until the fix is live in production, not just merged. So one skill triages; the fix rides the shared issue-to-PR pipeline.

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  The Pragmatic Engineer (@Pragmatic_Eng) reported 22 minutes ago

  Why did spec-driven development never take off - the workflow tools like Amazon’s Kiro or GitHub Workspaces encouraged? @dexhorthy, founder of HumanLayer: “These projects have a really interesting idea: you maintain a set of specifications for your software, and then you maintain the code itself, and the dream is the coding part is just compiling specs into code. But that part never really materialized. I’m on a GitHub issue in spec kit that’s been open for a year, and every couple of weeks I get a new email on the thread of people complaining about the same problem: I edit my specs and then I edit the code, and the code drifts from the specs. How do I keep the specs up to date as the code is changing? You now have two sources of truth, and it stops being useful. That’s why with RPI (Research, Plan, Implement), the docs are tactical execution docs - I do the research, the plan, the implementation, and I throw the docs out. The next time I need research I just do it from scratch, because tokens are cheap and my time is expensive.”

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  Seriki Favour 👨🏽‍💻 (@favour_devs) reported 22 minutes ago

  What’s wrong w GitHub, trying to open PRs this evening, but server error 😟

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  MarMar Labs (@MarMarLabs) reported 23 minutes ago

  MCP's most important 2026 upgrade may be the code it deletes. GitHub's MCP Server just added ahead-of-release support for the July 28 spec. The new core removes protocol sessions and `initialize`, so one tool call can be a self-contained request handled by any server instance. Old MCP: connect → initialize → session ID → sticky route/shared store New MCP: request + version/client context → any instance That sounds like boring transport work. It changes whether remote MCP scales like a demo or normal cloud infrastructure. Stateless doesn't mean state-free. If a browser, basket, or task must persist, return an explicit handle and pass it into the next call. The state stays; it just stops hiding in transport metadata. Trust also moves to the request boundary: every call must be authenticated and authorized independently. GitHub says the Tier 1 SDKs preserve backward compatibility, so this isn't a panic migration. It's a useful architecture test: Can request #2 still work if it lands on a different process than request #1? If not, where should that state live: a tool argument, an explicit handle, or a durable task?

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  capGoblin (@dharshan_tw) reported 27 minutes ago

  THIS CLAUDE + OBSIDIAN SYSTEM SHOWS EXACTLY WHAT HAPPENS WHEN 30+ SAVED GITHUB REPOS STOP BEING A FOLDER AND START BECOMING A LIVING PORTFOLIO most people collect repos faster than they can remember why they saved them, where they used them, or whether three different folders are solving the same problem new clone → read-only scan → personal note → usage trace → four audits → portfolio verdict 30 repos, two folders, four cross-repo passes, one shared memory file updated every 12 hours loop 1 reads the README, package files, upstream commits, imports, configs, and scripts, then assigns one of four statuses: in-use, shelved, duplicate, or unclear loop 2 catches tools unused for 30+ days, groups real duplicates, flags dependencies quiet for 120+ days, and retries failed checks twice before sending them to human review bookmark this and watch it run, then read the article below to see why a README tells you what a tool does while this system remembers why it still belongs in your stack

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  Nicholas Yang (@NicholasLYang) reported 28 minutes ago

  @PredragGruevski @geoffreylitt GitHub ships about as fast as the MTA builds subway lines. How is stacked diffs still not widely available? Why is the site still so terrible?