GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Roger Wilco (@rogerwillko) reported 35 seconds ago

  Ok bug fixes So obviously the 404 but I think that’s a GitHub thing Stars are all selected when pick ones (that’s code) Will get a fix asap

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  Nero (@NeroBirb) reported 1 minute ago

  @ayesha_fatiima Its change/source control, automated actions on event, issue tracking, etc. But if you don't need it to be public then idk why you'd use github and not self-host forgejo. I'd rather rely on what I host than what someone else hosts.

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  Marcos (@MAMware) reported 4 minutes ago

  @richkuo7 @ClaudeDevs @grok i like this "new-issue Turns a bug, idea, or conversation into a complete GitHub issue. Checks the claims against the actual code first, adds a complexity score, and never files a half-empty stub." and this "sync-docs Updates CLAUDE.md, AGENTS.md, SKILL.md, and README.md to match what recent commits actually changed."

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  Lewis Campbell (@LewisCTech) reported 5 minutes ago

  Github, Codeberg etc should have a place where you can just tell the devs how much you love their open source software. Once I made an issue just to say the software was great, and the dev said "thank you very much" then closed it with "wontfix" LOL

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  fiddy (@fiddyresearch) reported 5 minutes ago

  @kmets_ @banteg @endingwithali As a simple example, if you wrote some code in zig 0.15.2 which the llvm backend in optimization mode compiled to use simd lanes, those optimisation branches were turned off in zig 0.16 and are still turned off in 0.17-dev And that means the same source code became less performant just by using an updated compiler. The only way you can discover this issue is by looking at what the compiler does with your source code and hunting for any triaged issues on github or codeberg. Which means reading the code which means spending time with an agent trying to understand what was done with your source. But you can do that totally llm-assisted which is superb for learning.

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  Fex (@Fex_23_) reported 7 minutes ago

  @LeonChaland @NXT4EU And no ZKPs wont work as advertised as stated in the Github Issue. You should read that one first

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  Memento ($HODL arc) (@King_Memento) reported 14 minutes ago

  bro how ******** do self proclaimed util/tek traders even shill something thats so ******* bundled and the github is totally *** and a big L? and i see those coins going up and up? why? i think i need to start farming every gay *** tek as well, so much gay *** garbage out there, Just look at @AlpenGlowSolana , this **** isnt even working, like literally slop of the year, i posted a video as well on it, yet i see these same accounts pushing it and it going up and down up and down, like a bloody ******* farm. wtf lmao. How do u ******* even fall for such coordinated shill farm? I mean dont u have a PC to try and test the tek, it takes like 1 minute lmao.

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  Alireza Najafi (@alire8za) reported 16 minutes ago

  @daniel_nguyenx is this an android apk? Boox note air 3 c was so laggy with non default android note taking applications. the stock app was nice and fast but the ones I installed were all laggy. Didn't you face such problem in your development? Also is this available on github?

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  MASTA (@TR_Delight93) reported 18 minutes ago

  @JoeyPWilliams No the screenshot itself is not the issue but the comparison is retarted. While both are **** atleast with xb it is a ms account. Meaning if you use bing, github, rewards or any other Microsoft service your fine. Meanwhile at ps it is only playstation.

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  Damien Benveniste (@DamiBenveniste) reported 21 minutes ago

  I tend to avoid reviewing PRs NOT written by coding agents! Humans are just not that good at documenting their code! We often see LLMs being criticized for the code they write, but have you read code written by humans? A typical engineer will need to break down their work into multiple PRs, often making it hard to test end-to-end the code being submitted. Only at the last PR can you make sure the overall code actually does what it is supposed to! This with typically poorly documented docstrings and PR descriptions making it hard to review the overall architecture and functional behavior. Not even talking about the common lack of unit and integration tests coverage! That leaves the reviewer focusing on subjective properties like variable names. The first thing I do when I review code is run a reviewer agent, focusing the review on architecture quality and edge cases the PR may have missed. I use a mix of Cursor/Codex and GitHub Copilot, and iterate with the author until the agent validates the PR. Only then do I start to manually review the code, and as for agents, if the code is poorly documented and lacking best engineering practices, it makes it hard for an engineer to capture the overall logic. My experience is that agents just write better code. Better documented, using best engineering practices, and overall better structured, making it easier to review. You can more easily push an agent to complete bigger chunks of work, making it easier to follow the overall business logic of the feature. At some point, they may start to go off track, but it is trivial to course-correct them as it happens.

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  Aria Dubois (@AriaDubois_fr) reported 22 minutes ago

  MergeFund turns GitHub issues into funded bounties. Sponsor posts a bounty → Dev claims it → Submits a PR → AI reviews the code → Sponsor accepts → Payout. No more merging blind. No more paying for broken code.

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  Sir David Onyemaizu🦍 (@SirDavidBent) reported 22 minutes ago

  My bro, I disagree with you completely. X is the most transparent app right now. Is the algorithm perfect? Nope. But it is open sourced on GitHub. Everyone can see it. YouTube will never publish how their recommendation algorithm works. Nikita takes it upon himself to educate and tell users what to do everyday to earn more. The problem is that most people aren't ready to put in the required efforts. X wants creativity and conscious efforts into making advertiser friendly content. The creators revenue is not free money. They are paying you to help them retain brands and companies who use X to advertise their products and services. Overall, the real problem is that most users think it is free money and thus don't put enough efforts into making valuable content that actually teaches or impacts something. No META employee will tell you what to do to make more money from their revenue system, the way Nikita does.

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  Gokul Rajaram (@gokulr) reported 22 minutes ago

  PRODUCTSPEC: OPEN STANDARD FOR SOFTWARE INTENT tl;dr ProductSpec is the open standard for software intent before implementation. The more I worked on PRDs, the more obvious one thing became: Product specs need an open standard. Why? Because the PRD has become an overloaded artifact. Every company has its own template. Every team has its own preferred format. Every PM has their own way of writing. That was manageable when the only readers were humans sitting in the same org context. AI changes the requirement. A Product Spec now has to be readable by humans and executable by AI agents. That means the spec has to carry intent clearly enough for a designer, engineer, product leader, and coding agent to understand the same thing: • What problem are we solving? • What is the product bet? • What is in scope? • What must be true before this ships? • What metrics tell us whether the bet worked? This is why I open-sourced ProductSpec. ProductSpec is a Markdown standard for software intent before implementation. The core sections are simple: • Problem • Hypothesis • Scope • User Experience • Acceptance Criteria • Success Metrics The deeper design principle: Structure the parts machines must execute or compare. Leave readable the parts humans must reason about. That is why ProductSpec keeps Problem and Hypothesis as readable prose, while giving structured formats to the parts agents and tools need to parse: • Scope: what is in, out, and deliberately cut • Acceptance Criteria: what must pass before launch • AI Evals (within Acceptance Criteria): the evals an AI feature must pass before shipping • Success Metrics: what should be measured after launch When to use ProductSpec ProductSpec is not for every act of building. It is for consequential software work where intent needs to survive handoff. For an individual builder, a Product Spec is useful when the work is complex, risky, long-lived, or being handed to an AI agent loop. For quick experiments, one-off scripts, or throwaway prototypes, it may be faster to brainstorm, build, and iterate directly. For a team or organization, ProductSpec is most useful when coordination cost appears: multiple people, multiple agents, design and engineering handoffs, customer-facing launches, AI features with evals, or decisions that will need to be revisited later. ProductSpec does not replace ***, Jira, Linear, Figma, analytics tools, OpenSpec, Spec Kit, or AI coding agents. It sits upstream of them. ProductSpec -> Engineering Spec -> Tasks -> Code -> Evaluation -> Learning -- *** stores implementation history. A Product Spec can live beside code in ***, but code commits should not be the first durable record of why the work exists. -- Jira and Linear store work history. A Product Spec can become epics, tickets, or tasks, but it should remain the durable statement of intent behind those tasks. -- Figma stores design artifacts. A Product Spec can link to prototypes, mockups, or screenshots through user_experience, but it does not replace the design source of truth. -- Analytics tools store outcome data. -- OpenSpec and Spec Kit turn intent into engineering plans. -- AI coding agents execute implementation tasks. -- ProductSpec stores the software intent behind the work: the problem, hypothesis, scope, acceptance criteria, and success metrics that downstream tools should preserve. I'd love for this standard to be broadly adopted, which means it must be broadly owned by the builder community. Founders, ***, engineers, designers, researchers, AI builders: please contribute examples, critiques, section changes, parser implementations, validator improvements, and integrations with GitHub, Jira, Linear, Figma, OpenSpec, Spec Kit, and agent workflows. (link below on how to contribute) If you have scars from writing product docs that looked aligned but failed during execution, those scars belong in the standard. My goal is for ProductSpec to become the open source format for software intent before implementation. (links below)

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  Yumzlef (@Yumzlef) reported 24 minutes ago

  STOP THINKING WITH YOUR OWN HEAD: How to harness Polymarket's top traders to make you money 95% of people lose their deposits on Polymarket simply because they try to guess the outcome of events based on the news. But why reinvent the wheel when you can literally pick the pockets of those ALREADY making millions and completely automate your income? An open-source Python script (based on the official PyLOB SDK) has appeared online that turns Polymarket into an automated copy trading platform. From now on, you don't need to read analytics-the bot will do it all for you. How does this legal espionage work? Finding "whales" You go to the Leaderboard tab on Polymarket, choose a top trader with an impeccable multi-month win rate (not some random upstart with a one-time big win), and copy their public wallet address in one click. A "carbon copy" setup You paste the whale's address into the Python code, enter your account keys through the platform's Gamma API, and set a fixed bid amount (for example, just $2-$5 for testing). Error-free logic The bot operates according to a strict algorithm: it cyclically queries your target's wallet. As soon as the whale opens a new position in the market (for example, places a large bet against Bitcoin's growth), the bot instantly detects this move through a private client (CLOB client). The script checks whether you already have a similar position, and if not, it automatically opens the exact same trade in your account in a split second. Moreover, the bot will never duplicate a bid on the same market, protecting your balance. How can this system be scaled into a full-fledged business? Run on AWS: The script is transferred to a free Amazon virtual server (EC2), installed on the task scheduler, and the bot starts mining the market 24/7, even while you sleep. Diversification: Instead of a single account, you can connect an array of top 10 traders, set a dynamic position size (as a percentage of your bankroll), and enable Telegram notifications to see how your balance increases in real time following the trades of professionals. The prediction market is a game where speed and experience win. Stop guessing and start copying. For a full breakdown of the logic behind this bot's 6 main functions, links to GitHub, and instructions for deploying on a free server, watch the video. Also, read and save this article, which shows how to trade correctly on the Polymarket.👇

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  Adetunji | Software Engineer (Web & Mobile) (@itzadetunji1) reported 31 minutes ago

  @eliana_jordan Last week but it was hell to use it I hated the experience and github copilot was slow