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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Bhuvnesh Arya (@Bhuvneshdot) reported 8 seconds ago

  One trend I'm watching very closely in AI-assisted software development. And I think it deserves more discussion than it gets. A few years ago, most developers learned by writing code. Yes, we copied snippets from Stack Overflow. Yes, we searched GitHub. Yes, we reused libraries. But we still had to stitch everything together ourselves. We wrote the glue code. We fixed the compilation errors. We handled the integration issues. We discovered the edge cases. We slowly built a mental model of the system because every line we added forced us to understand how the pieces fit together. By the time the application reached production, we knew where things lived. We knew which service called which API. We knew why a cache existed. We knew why that seemingly strange condition had been added three months ago. More importantly, when production broke at 2 AM, we usually knew where to start looking. Not because we had perfect documentation. Because we had built the system ourselves. --- Today the workflow is changing. A developer can describe a feature in a prompt. The AI generates hundreds or even thousands of lines of code. Another AI reviews the code. The tests pass. The pull request gets merged. The feature ships. From a productivity perspective, this is incredible. We're building software faster than ever. --- But I think we're quietly creating a new bottleneck. When a production incident happens, someone still has to understand the system. Someone has to debug the issue. Someone has to explain why this particular edge case only fails under production traffic. Someone has to know whether fixing one service will break three others. That requires a mental model. Not just generated code. --- I've noticed something interesting. The amount of code an engineer can produce has increased dramatically. The amount of code they truly understand hasn't increased at the same pace. Those are two very different things. --- Many organizations assume AI agents will eventually handle production incidents. Maybe they will. But today's production systems are messy. Distributed systems. Legacy integrations. Race conditions. Unexpected user behavior. Incomplete documentation. Business rules that exist only because of a decision someone made five years ago. Those aren't always problems an AI can solve in isolation. Eventually, a human engineer gets pulled into the incident. And that's where understanding matters more than generation. --- The engineer who generated the code isn't always the engineer who understands the code. That's a subtle difference. But I think it's going to become one of the biggest engineering challenges over the next few years. --- Writing code is becoming cheaper. Understanding systems is becoming more valuable. I don't think AI is reducing the need for software engineers. I think it's changing what great software engineers will be measured by. Less by how fast they can generate code. More by how well they understand, debug, and evolve complex systems. --- Models generate intelligence. Systems generate value. And I suspect the engineers who deeply understand those systems will become even more valuable in the years ahead.

• 
  Ashkan (@ashkans_dev) reported 2 minutes ago

  Anyone else having an issue with Codex not staying auth’d with GitHub using the gh CLI ?

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  Killbunny~ 🐰🔪 (@killbunny_) reported 3 minutes ago

  @kaneryu @V33V33V33V33V33 @CryptoCyberia Bro gatekeeping me from Github😔but yeah that's a problem with Devs, not end users. Also Github solved this years ago with GitHub Pages, a feature a large amount of people don't use. If you're expecting a normal Joe to use the thing (let's say a game mod), it's on the Dev to make a Site and distribute the bin. Totally different from uploading the source code of a service that actually requires technical knowledge to be deployed.

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  BlaDieBloe𐨆ۖۖۖۖۖۖۖۖۖۖۖۖۖۖۖۖۖۖۖۖۖۖۖۖ​ۗۗۗۗۗۗۗۗۗۗ (@BlieDieBlaDie) reported 10 minutes ago

  The scumbags of the universe !!!! Paying exploit thiefs without any problem ha @mour0ne . He only had one exploit bc he found it on github and stole it and then defended him self by html edit his join date on @Hacker0x01 . And the sad part of it all he came away with it !!!

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  Yume_X (@yume_arasaki) reported 14 minutes ago

  @__tinygrad__ Your AIs are rapidly becoming an extension of your mind. The opening volley was that it wasn’t possible to do this locally. That moat is fading away fast. It’s just a matter of time the closed US Labs realize their real moat is UX and harnesses and people will pay them for it. When hardware and optimizations and cost economics all collide, owning your own intelligence for individuals and companies is going to become a topic, ironically it’s exactly the same mindset that drives American closed LLMs to do the same thing. No company wants its trade secrets “uploaded to the cloud” to be trained so a competitor emerges from their hard work The Chinese and the rest of the world are not fully “open source”, they just do a weird dance switching open and closed, it wins them massive loyalty and clout. Today I replaced my main driver with just two sparks. For less than the price of a new card $8k vs $20-$30k . You can basically completely be AI self sufficient for most things. Yes, it’s a down payment and we should be honest that , AI hardware is going to get better so hardware is just going to depreciate, the break even maths for hardware is brutal vs renting at the moment I was a big fan of ChatGPT 4 , they decommissioned the model. Now I can’t ever be cut off. I have full control. I replaced it with Qwen 3.6 27b Dense , i can fine tune the models exactly how i want them and i don’t need to have it stuck inside some company. I can run the whole thing off-line. I don’t need to be paranoid about whether they honor the “butron” about not using your data. Btw guys if you forgot , GitHub by default has some setting where its on for sending your repo for “improvements”, switch it off if you don’t want your repos uploaded to Microsoft. If you have very proprietary stuff you shouldn’t even be using GitHub. You should host your own repo if you don’t want to secure it. The issue with “training” is unlike before the legal liability is difficult as it will be impossible for you to prove a product was made with your input. It’s the same issue as how artists have no way of claiming that models used their data to create some art that absorbed their style.

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  Piyu$h (@erornotfoundme) reported 15 minutes ago

  From pencils to keyboard From notebooks to GitHub From ABCD to DBMS From Arey to Array From mistakes to error We all grew up...

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  plumhusky (19m) (sawyer) (@plummydahusky) reported 17 minutes ago

  @iKG_HD to dox people 2) every update since about 5.7 has been in attempt to fix DRM. Multiple updates a day have been pushed in the past week. Unfortunately some people crack people's tweaks. There are entire jailbreak repos for it. Someone made a repo on GitHub with a copy of the

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  Cap-EO 👨🏾‍💻 (@EOEboh) reported 17 minutes ago

  2. Case studies, not project cards: A screenshot and a "View on GitHub" button is not proof. Show the problem, your constraints, the decisions you made and why. The result with numbers.

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  AI for all (@__aiforall__) reported 20 minutes ago

  OpenAI's unreleased Astra model produced formal proofs for 10 long-open math/CS problems: a non-sofic group construction, a disproof of Connes's rigidity conjecture. Lean certificates are public on GitHub — machine-checkable, not a claim you have to trust.

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  Wehk (@Wehk_k) reported 24 minutes ago

  @Ronnnnnnnner @Leo_Pier_ A dex paid would just fix or remove that github

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  MineBench - efficient computing power (@MineBenchdapp) reported 24 minutes ago

  We would like to ask for your help regarding our GitHub account. Our account was suspended even though our repositories do not contain malware or any harmful software. They primarily contain open-source mining-related components, similar to projects such as XMRig, which continue to be publicly available on GitHub. The suspension is creating a significant obstacle to the development of our application. We have contacted GitHub Support multiple times but have not received a meaningful response explaining the reason for the suspension. If possible, could you reach out to GitHub on our behalf or help us understand what the actual issue is? If that is not possible, we would appreciate any recommendations for a reliable alternative platform where we can continue developing and hosting our open-source project. Thank you for your time and support.

• 
  Michael ® SpeedevsWhale (@SpeedevsO) reported 26 minutes ago

  (use GitHub for sign in) (2025 and below GitHub) Is the requirement I think If your eligible you will get it

• 
  Poly (@poly0015iew) reported 27 minutes ago

  AN OPERATING SYSTEM THAT WRITES ITS OWN KERNEL DRIVERS HAS 28 STARS ON GITHUB 72,000 lines of C. one contributor. seventeen commits. i checked the numbers three times because the ratio didn't make sense. it's an x86_64 os from scratch whose only interface is a sentence. no shell, no commands, no ls, no cat. the author's own line is better than anything i could write about it: there is not one strcmp on the input path. that's how a kernel developer tells you he didn't cheat. the kernel does its own DNS and its own TLS in ring 0 - lwIP and mbedTLS compiled straight into kernel.bin, no host proxy of anything. the model gets 64 real syscalls as tools. prose on screen is the model, [brackets] are the kernel printing what it actually dispatched, from the real C return value. five separate defects were fixed to keep that line honest. now the part that made me put my coffee down. the kernel ships no audio driver and no knowledge of any sound chip. you attach a card, it shows up as an unclaimed pci device, and you type one sentence. it reads pci config space. writes a bring-up program in the kernel's own driver-vm instruction set. resets the codec. unmutes the mixer. builds a buffer descriptor list. starts the dma engine. installs itself as the system audio sink. then you can just ask it for notes. and in the recorded transcripts there's a run where the model correctly diagnosed a bug in this kernel's own printf - from inside the guest. forty years of teaching humans to speak kernel. one person spent seventeen commits teaching the kernel to speak human. twenty-eight people have noticed. 72,000 lines. 64 syscalls. zero strcmp. 28 stars.

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  Gezim (@tealtoronto) reported 28 minutes ago

  Do we just have skill to search GitHub before Claude builds something? Problem is that I don't think anyone bothers shipping these small snippets to GitHub at all.

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  Penelope (@Ladys_Winter) reported 29 minutes ago

  @vladuhat999 @LuminaMeow14 @V33V33V33V33V33 It objectively is terrible UI design when so many users can't find the LITERAL ONLY BUTTON THEY NEED, and github simps will go "well the website is made for other people! They are just forcing you to use it for no reason! NO UPGRADE OR UPDATES!!!!"