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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Max Vmr (@vmrmax) reported 54 seconds ago

  A GITHUB REPO WITH 57,000 STARS IS SITTING ON 1.51 BILLION FREE AI TOKENS A MONTH. AT $3 PER MILLION, THAT IS $4,500 YOU ARE CURRENTLY PAYING SOMEBODY It is called OmniRoute. MIT licensed. One command. Right now your tool is wired to exactly one provider. One key, one price on every single call, and the moment they rate-limit you or go down, you stop working. Before: Cursor → OpenAI → their price, every call, every time After: Cursor → OmniRoute → 350 providers → whichever one is free and up Three things you get. You stop stopping. 19 routing strategies with automatic failover. Provider goes down, the request moves to another one. You get an answer instead of an error. You pay less. It ships a catalog of 90+ providers with free tiers and uses those first. On top of that it compresses what you send, which the project puts at 15% to 95% fewer tokens billed. You rewrite nothing. No code changes, no new prompts. You change one address. npm i -g omniroute Server boots on localhost:20128. Point your tool at [ and set the model to "auto". Claude Code, Cursor, Cline and Copilot all work as they are. Keys stay on your machine, encrypted. Two honest notes. It does not make models smarter. Answer quality is whatever the model that picked up the call gives you. And it is useless if your AI work is a chat window in a browser. This is for people whose tools call an API with a key. If that is not you, skip it. The free-token and compression numbers come from the project's own docs, not an independent benchmark. Run it for a week on your real usage before you quote them. Your AI bill is usually not a model problem. It is a routing problem.

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  Bobby Lansing (@dataguybobby) reported 2 minutes ago

  5. Human merge Agents propose. Humans merge to dev. When a PR is created various @cursor_ai automations fire off to review the code and consider potential errors. GitHub PR · CODEOWNERS · 1 approval · no auto-merge

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  Nick (@maietta) reported 4 minutes ago

  @robot_sox I run my own gitlab server and also self-host repos directly on my main domain. It's just that for this project I am still stuck on GitHub only because other people might need to access the code base and are already in that ecosystem. I will eventually move them over to my system.

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  tender (@tenderizzation) reported 4 minutes ago

  of course you think CUDA is better, cutedsl is the hot new thing and you finally profiled the kernel launch overhead. not to mention you just saw a github issue showing how many microseconds you're never going to get back from torch.library.wrap_triton. you're going to be convinced of that until next month when your workload hits a shape you didn't template specialize for. then it'll be back to DSLs until one innocent little API deprecation throws you under the bus and

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  Stats Wire (@StatsWire) reported 6 minutes ago

  @github Many a times my chats are lost in GitHub and I don't find them when I need them. Quite annoying. Fix it.

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  Hot Aisle (@HotAisle) reported 7 minutes ago

  @_can1357 thing is that tibo said it actually doesn't help since they've already tuned things to what they thought are best. so you're defaulting to a worse experience for omp, because a bunch of crazies will create github issues. ugh.

• 
  Gabriel Rubens (@gabrielrubenss) reported 11 minutes ago

  VPS deploy via GitHub (5/8): for now a blocked deploy simply runs again on a fresh runner, and that rescued five of the next six. It is a workaround though, not a fix. The strange part: it started out of nowhere and I changed nothing in my infra, so I still want the real cause.

• 
  Alex (@Alexq7hc) reported 14 minutes ago

  @solananew Solana’s latest governance vote exposed an absurdly basic problem: Its official documents contain two different voting rules. Under one set of rules, at least one-third of governance stake must participate, but abstentions are included in the denominator. In other words, abstaining is not technically a “No” vote, but it still makes a proposal harder to pass — effectively turning abstention into a form of “soft opposition.” The rules published on GitHub are completely different: abstentions are excluded, and the approval ratio is calculated only between “For” and “Against” votes. More surprisingly, there is no minimum participation requirement at all. That means, in theory, a very small fraction of SOL holders could participate and still determine major rules affecting the entire Solana network. The more holders who do not vote, the greater the influence of the small minority who do. This is not a minor technical detail. It is a question of governance legitimacy and decision-making validity. A reasonable governance system should have two separate thresholds: First, require a minimum participation rate. Second, once that threshold is met, require For ÷ (For + Against) to exceed 2/3. This prevents a tiny minority from deciding network-wide policy while also avoiding the mistake of treating abstention as opposition. Solana is a blockchain worth tens of billions of dollars and secures a large amount of capital and applications. Yet in its first formal governance vote, even the most basic voting rules were not consistent between official documentation and the GitHub repository. This goes beyond “governance is still evolving.” The basic rules themselves are not even internally consistent. For a blockchain worth tens of billions of dollars, having two conflicting versions of how votes are counted makes the whole governance process look surprisingly amateurish.

• 
  Ross (@rosswil) reported 15 minutes ago

  @ScalaHanSolo @github GitHub’s implementation is terrible, take me back to the old Jenkins days

• 
  Nandkishor (@devops_nk) reported 15 minutes ago

  I see the same problem in DevOps teams. - One AI agent for Kubernetes. - Another for CI/CD. - Another for observability. - Another for GitHub security. The hard part isn’t running multiple AI agents. It’s always making sure every agent has the right context without repeatedly explaining your entire infrastructure.

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  Bonsai 🌳 (@bonsaixbt) reported 16 minutes ago

  I GAVE SEVEN GROK BOTS MY INBOUND CALL LOG AND WENT BACK TO WORK The console was already processing 44 numbers and the agents had already found the people those numbers belonged to I was sick of random calls in the middle of work, so instead of relying on someone else’s “lookup service”, I sat down and started building my own agent-powered system What you see in the video is not a finished product. It’s a live, real-time console: a queue of 44 numbers is already being processed, the agents are working in the background, and GHOSTLINE is still far from being a complete system Right now, only two of the seven roles are operating in combat mode: > Atlas takes an incoming number or a number I enter manually and determines the carrier and region > Scout searches open sources and checks where that number has already appeared online The other agents are still in the shadows: GitHub, Reddit, other platforms, filtering out junk, and generating the final report, I’m writing all of that separately, i deliberately didn’t include them in this demonstration I don’t need a one-off trick, I want a system that can continuously check numbers whenever some random person starts yelling at me through the phone in the middle of work or when an unknown number shows up in a work chat For now, this system can do very little, but I already don’t feel like blindly answering calls from unknown numbers

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  tender (@tenderizzation) reported 20 minutes ago

  of course you think CUDA is better, the shine is starting to wear off of cutedsl and you finally profiled the kernel launch overhead. not to mention you just saw a github issue showing how many microseconds you're never going to get back from torch.library.wrap_triton. you're going to be convinced of that until next month when your workload hits a shape you didn't template specialize for. then it'll be back to DSLs until one innocent little API deprecation throws you under the bus and

• 
  notreroute (@notreroute) reported 20 minutes ago

  most founders spend $40,000 a month on payroll before discovering 80% of operational workflows can run on autonomous agent pipelines with zero human intervention. in 6 minutes ByteByteGo breaks down how deterministic execution order replaces entire management layers: state coordinator logging directly to GitHub worker agents executing API queues and pull requests independent validators running 12-second test loops the surface read is treating models like chat interfaces, the actual lever is orchestrating autonomous micro-services. i turned the whole architecture into a practical deployment guide you can run in production. worth more than an entire tier of middle management salaries. watch the clip first, then the full architecture breakdown is below. you'll find the full breakdown in the article below

• 
  The AI Therapist (@TheAIShrink) reported 21 minutes ago

  @Arcane_Aii Palantir costs millions for governments. Elie’s GitHub repo is free until it breaks your pipeline at 3am and you pay the devops salary to fix it. software ≠ product-market fit

• 
  Lomash Kumar (@LomashKumar52) reported 22 minutes ago

  Hermes Agent went quiet for two weeks — no announcement, no changelog, just six release tags with zero real explanation. Here's what actually shipped. Between August 13th and August 27th, 2026, Hermes Agent pushed six back-to-back rollup releases, from v0.20.1 all the way to v0.20.6, and every single one deferred its real changelog to the upcoming v0.21.0. In this breakdown, I went through all six releases commit by commit to cover what actually changed: the emergence of Bot Mode as a multi-agent teammate system, a keyless web search tier that works with zero API keys out of the box, a new consent-gated real-profile browsing feature, a massive expansion of the MCP server catalog with over 50 vendor-hosted integrations, and a wave of security and reliability upgrades including OS-keychain secret encryption and skill install scanning. If you're running Hermes Agent, or evaluating it as an open source AI agent framework alongside tools like Claude Code, OpenCode, or other agentic AI setups, this video walks through exactly what landed in your last update whether you noticed it or not, and whether it's actually worth updating for. This is for anyone following open source AI agents, local-first tooling, and free AI model access in 2026. @NousResearch @GithubProjects @github