GitHub status: access issues and outage reports

Problems in the last 24 hours

The graph below depicts the number of GitHub reports received over the last 24 hours by time of day. When the number of reports exceeds the baseline, represented by the red line, an outage is determined.

Most Reported Problems

The following are the most recent problems reported by GitHub users through our website.

• Website Down (54%)
• Errors (31%)
• Sign in (15%)

Live Outage Map

The most recent GitHub outage reports came from the following cities:

City	Problem Type	Report Time
Ahmedabad	Errors	15 hours ago
Delme	Sign in	1 day ago
Lyaud	Website Down	1 day ago
Catania	Errors	4 days ago
Inverness	Website Down	16 days ago
Quito	Sign in	17 days ago

Full Outage Map

Community Discussion

Tips? Frustrations? Share them here. Useful comments include a description of the problem, city and postal code.

Beware of "support numbers" or "recovery" accounts that might be posted below. Make sure to report and downvote those comments. Avoid posting your personal information.

GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Bash (@bashirbuilds) reported 2 minutes ago

  Your Stripe account can be healthy while your checkout is broken. OpenAI can be operational while your AI feature is failing. GitHub can be up while your deployment workflow is stuck. That’s the problem I’m building Reeno around. Dependency uptime is not the same as product health. Your monitoring should tell you when the thing your customers actually use stops working.

• 
  AI Scientist (@AIScientist_X) reported 3 minutes ago

  NEWS: X LANDS FIRST PUBLIC ALGORITHM PR > X OPEN SOURCE SAID SEP 1 THAT AFTER 2 PLUS WEEKS OF DAILY UPDATES IT INTEGRATED A FIRST PUBLIC CONTRIBUTION AND THAT THE CHANGE IS NOW LIVE ON X. > IT SAID THE SMALL UPDATE IS BASED ON GITHUB PULL REQUEST 55. X CLOSED THAT PR AS COMPLETED AFTER LANDING ITS OWN FIX. SOURCE: X OPEN SOURCE

• 
  Ishank (@IshankDev) reported 3 minutes ago

  7/ 16k+ GitHub stars. Built for people who want control, not another marketing-suite login.

• 
  Dr Milan Milanović (@milan_milanovic) reported 8 minutes ago

  How Cursor made *** scalable The thing with *** is that it never was designed to be scalable. Your repo lives on the disk, and *** client expect every read to be consistent. This was a problem on GitHub, where shared filesystems and replicated storage failed before 2013. The GitHub built 𝗦𝗽𝗼𝗸𝗲𝘀, and it became the industry standard. This means that every repo is stored as three full copies on three servers, and every push runs a vote (three phase commit). A majority of servers must confirm before it exists. This works, but with high cost, because every push is slow as the slowest server. When we add new servers, it makes it even slower. Now Cursor took some opposite direction with 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗶𝘁𝘆. The repo history is now written as a log in S3, and this is only source of truth. Any push counts only if it is located in the log. The servers don't need to keep anything important, they are just cache. Any server can take a push, and idle repos are dropped from disk and rebuilt from the log when it is needed. This resulted in 120 pushes per second on standard S3, and over 300 on S3 Express. Their tests have shown that read capacity grew linearly up to 100 replicas. Why is this important now? Because of AI agents mostly. We now have more code, PRs, CI runs and many small repos. All of these repos would need three full copies in the old model. This means that we achieve scale by removing parts, not adding them.

• 
  shifan (@sanereverie) reported 8 minutes ago

  building something that races coding agents on the same GitHub issue and scores the PRs. coming soon.

• 
  Curious Explorer (@PatelVatsalp732) reported 9 minutes ago

  I burned 14B Codex tokens. The official usage UI still cannot tell me what actually ate the weekly cap. So I shipped a Codex-only board: GitHub login, local-first sync, private by default, optional public rank + shipping proof. Roast the metric or join it.

• 
  HeroGamer⚡ (@herogamer21btc) reported 11 minutes ago

  💻 GitHub Issues vs Draft PR vs Open PR — the difference nobody explains: 🔴 ISSUE = Should we do this? No code yet You describe the problem "App crashes when pasting OP_RETURN" "We need X feature" Anyone can open it Goal: decide IF and WHAT to build 🔵 DRAFT PR = I'm doing this, is this the right way? You have WIP code "I fixed it by doing Y, but not sure about placement / approach" Can't be merged Perfect for early feedback Goal: validate HOW you're building it 🟠 OPEN PR = I did it, ready for final review, please merge. Code done, tests pass Ready for final review Goal: ship it 🌊 Flow: Issue → Draft PR → Open PR Most people skip Issue or Draft and go straight to Open PR. Then maintainer has to review both the idea AND the implementation at once = slow, painful. Start Draft when unsure.

• 
  Avinash (@Avinash25818689) reported 12 minutes ago

  People who want to start contributing to open source: - Pick an Org based on your interest - Fork the repository - Clone it - Do the local setup - Read README and contributing .md - Pick an issue - Create a new branch - Fix the issue - Write tests (if necessary) - Test it - Add, Commit & Push the code - Go to GitHub & raise that PR That's pretty much it. Start small and learn as you go.

• 
  joithan (@jothantranston) reported 14 minutes ago

  THIS GUY BUILT A TINY AMOLED DESK BOARD JUST TO STARE AT HIS STRIPE NUMBERS it's a Waveshare ESP32-C6 touch panel that sits in your peripheral vision and cycles business metrics so you stop digging through Stripe > same ESP32-C6 board people use for Claude Code token meters, flipped to revenue > eight screens, five seconds each: MRR, new paid, paid subs, cancelled, ARR, ARPU, net 30d, failed > empty screens hide themselves so a young account sees a shorter loop > polls Stripe every five minutes on a read-only key (subscriptions + invoices) > marks itself stale instead of showing a number it can't vouch for > no soldering: flash over USB, finish Wi-Fi + key setup from your phone > data stays on the board; no project server in the middle firmware free on GitHub: cosjef/stripe-desk-display. board ~$30–$36 (Waveshare ESP32-C6-Touch-AMOLED-2.16). chat and terminal can't sit in your eye line for five hours. a tab you have to open is a tab you stop opening. this is what "the numbers find you" looks like as a brick on the desk.

• 
  moledao (@moledao_io) reported 14 minutes ago

  Web3 Remote Job Scams: A 2026 Field Guide Introduction Over the past few years, Web3 has come to represent a new world of opportunity for many young people. New roles, new narratives, and new stories of wealth have inspired countless people to enter the industry with high expectations. Remote work, stablecoin-based compensation, and a greater emphasis on ability than academic credentials can be especially attractive to professionals at the beginning of their careers. As a recruitment platform that works with job openings and candidates every day, however, we have also seen the other side of the industry. A significant share of supposed recruitment activity is not recruitment at all. It is fraud disguised as hiring, designed to steal the funds in job seekers’ wallets. According to Chainalysis’ 2026 report, cryptocurrency scams and fraud caused an estimated $17 billion in losses worldwide in 2025. Impersonation-related attacks increased by 1,400% year over year. Fake recruitment is one of the most common ways impersonation and social engineering are being applied to job seekers. What Happened to Us This month, it happened to us. We were contacted through Telegram by someone claiming to represent a US-registered technology company. They said the company urgently needed to hire Web3 engineers and wanted our support in sourcing candidates. After further investigation, we were unable to verify whether this person had actually been authorized by the company. We also could not rule out the possibility that they were impersonating a legitimate business. To avoid causing further harm to an organization that may itself have been a victim of impersonation, we will not disclose the company’s full name. At first, there were almost no obvious warning signs. The contact provided a business registration document and a polished company profile. Interviews were scheduled through Calendly, job openings were hosted on Ashby, and meetings took place over Zoom. These are all professional tools commonly used by legitimate companies, making it easy to assume that a company using them must be trustworthy. In reality, forging a registration document and creating Calendly or Ashby accounts require very little effort. Almost anyone can create the appearance of professionalism at minimal cost. This experience taught us an important lesson: the legitimacy of the tools surrounding a hiring process tells you very little about the legitimacy of the company behind it. The details of how the people involved behave are far more revealing. The partnership also progressed with unusual ease. All contractual documents arrived at once and appeared ready to sign. There was no friction at any stage. When discussing the recruitment fee, we initially proposed 15%, which the other party immediately accepted. We then tested an increase to 20%, and they accepted again without hesitation. Anyone with experience in recruitment delivery knows that fees are often one of the most difficult parts of a headhunting agreement. Clients may negotiate repeatedly over a difference of just two percentage points. The pace was also deliberately compressed. Interviews were often scheduled only one or two hours in advance, leaving almost no time for verification. Once confirmed, meetings were then repeatedly cancelled or rescheduled due to supposed last-minute conflicts. Several additional warning signs gradually appeared. The registration documents looked legitimate at first glance. Upon closer comparison, however, the names of the people listed in them did not match the information we were able to verify independently. The contact also made an unusual request. While verifying whether candidates were currently employed, they asked us to find out whether those candidates used LinkedIn frequently. Normal employment verification does not require this information. A person’s activity on a professional networking platform primarily reveals whether they have an accessible network that could quickly be used to verify their identity, employment history, or recent activity. At the same time, the contact prohibited us from sourcing candidates through LinkedIn or Telegram. They claimed their internal team was already using those channels and wanted to avoid duplicate candidates. In practice, this restriction pushed external recruitment partners into channels where independent cross-checking was much more difficult. The geographic requirement was even harder to explain. A US company was willing to consider only Chinese-speaking candidates and applied unusually strict screening standards that appeared unrelated to technical ability. In retrospect, we suspect that the screening criteria may have favored candidates who were easier to persuade and more likely to have higher incomes or larger asset balances. We cannot, however, confirm the group’s true intentions. Each of these warning signs could have been rationalized on its own. A client may have unusual preferences, legitimate concerns, or simply an unprofessional hiring process. It was only when the signals were considered together that the larger pattern became visible. Then came the interviews. Candidates joined the meetings, but the interviewers asked no questions about their project experience or technical background. Instead, they immediately provided a GitHub repository and instructed candidates to clone it onto their local machines and run it. The repository involved encryption and signing operations using cryptocurrency wallet private keys. Before the interviews, we had explicitly asked whether candidates would need to download or run anything. The contact told us they would not. Once the meetings began, however, the candidates received the exact opposite instruction. One candidate offered to share his screen, inspect the code locally, and walk the interviewer through it line by line. The interviewer refused and insisted that he download and run the repository on his own computer. The candidate ended the meeting. Other candidates quickly noticed that something was wrong and stopped as well. The most carefully designed part of the operation was not what happened during the interviews, but the feedback that followed. If a candidate ran the code, the interviewer gave positive feedback, said the candidate had performed well, and advanced them to the next round. If a candidate remained cautious and refused to run it, the interviewer told us that the candidate had falsified their résumé and instructed us to blacklist them immediately. That second response was not merely feedback. It was an instruction designed to prevent further communication between us and the candidate while allowing the wider operation to continue. This is something we hope every recruitment professional remembers: when a client asks you to blacklist a candidate without providing credible evidence, the request may reveal more about the client than it does about the candidate. Another common feature of these operations is that they do not need to interview every candidate. They only need a small number of people who are willing to execute the code. As a result, the hiring process will often stall abruptly once enough potential targets have been identified. What We Did Afterwards We immediately terminated all cooperation with the contact and removed the related job listings. We contacted every candidate who had entered the process to determine whether anyone had downloaded or executed the code. We also provided guidance on device inspection, credential rotation, and wallet security. All contracts, chat histories, meeting information, repository URLs, and account details have been preserved. Reports have been submitted to Telegram, GitHub, Ashby, and Calendly. At the procedural level, we have rewritten our client identity-verification process. Going forward, we will not accept recruitment assignments or partnerships without conducting independent callback verification through a channel the contact does not control. Candidate security briefings will also become a standard step before we introduce anyone to a client. Other Recruitment Scams Currently in Circulation What we encountered was only one variation. Several other methods remain active and deserve close attention. Malicious Take-Home Assignments Malicious interview assignments are currently one of the most widespread forms of recruitment-related attacks. Attackers impersonate recruiters or hiring managers on LinkedIn, X, or Telegram. They advertise senior roles with compensation well above market rates and frequently target professionals working with React, Next.js, Solidity, and blockchain technologies. Candidates are then given a technical assessment in the form of an npm project or GitHub repository and instructed to run it locally. Unit 42, the threat-intelligence team at Palo Alto Networks, refers to this activity as “Contagious Interview” and tracks it under the identifier CL-STA-240. The campaign was first publicly documented in November 2023 and has been linked to North Korea–associated threat actors. The malware used in these campaigns includes BeaverTail and InvisibleFerret. These cross-platform payloads target Windows, Linux, and macOS devices and are designed to steal sensitive browser information and cryptocurrency wallet data. According to security researchers, more than 197 malicious npm packages associated with this attack path have been distributed since October 10, 2025, accumulating more than 31,000 downloads. Common warning signs include recently created repositories, abnormal commit histories, and contributors whose identities cannot be verified. These are only indicators, however. Attackers can compromise established accounts, fork legitimate long-running repositories, or manufacture months of commit history in advance. No single signal can prove that a repository is either safe or malicious. Fake Meeting Software Fake meeting applications are another major threat. Attackers approach targets with an investment opportunity, partnership proposal, or interview invitation. Shortly before the meeting, they claim that Zoom is not working or that the company uses a different conferencing platform. The target is then directed to download the supposed meeting software from a specific website. Cado Security Labs has tracked one such campaign, known as “Meeten,” since September 2024. The campaign distributes a cross-platform information stealer called Realst. The group uses AI-generated company profiles to make its operations appear more credible. The names and branding of its meeting applications change frequently, with known examples including Clusee, Cuesee, Meetone, and Meetio. The malware targets cryptocurrency wallets and Telegram credentials, as well as iCloud Keychain data, banking information, and browser cookies. The solution is not to memorize an approved list of meeting applications, since legitimate companies may use many different tools. The safer rule is never to download meeting software from an unfamiliar domain sent directly by an interviewer. Download the software independently from its official website or an official application store, and verify the domain carefully. Malicious Offer Files Fake offer documents are another common attack method. In March 2022, attackers stole approximately $540 million from Axie Infinity’s Ronin Bridge, although later reporting placed the total value closer to $625 million. Subsequent investigations found that the initial point of entry was a fraudulent job offer delivered as a PDF. A senior engineer at Sky Mavis was contacted on LinkedIn by accounts impersonating another company. After completing several rounds of interviews, the engineer received an extremely attractive offer in PDF format and downloaded it. That file introduced spyware into the system. The attackers eventually gained control of five of the network’s nine validator nodes. Sky Mavis confirmed that an employee had been targeted through social engineering. In April of that year, the US Treasury attributed the attack to the Lazarus Group. What makes this case especially significant is that the victim was a senior engineer at the company that was ultimately compromised, and the attack was supported by a complete, multi-stage interview process. The final payload was simply a file. Terminal Paste Attacks Attacks that instruct victims to paste commands into a terminal or system run box have grown rapidly over the past two years. They are commonly known as ClickFix attacks. During an interview or onboarding process, a page may claim that the user’s browser has encountered an error, that their identity must be verified, or that a system component needs to be repaired. The page then provides a command and instructs the user to paste it into a terminal or run dialog. In May 2026, Microsoft disclosed a campaign targeting macOS users through lures disguised as system utilities. The campaign was used to distribute information-stealing malware. Other security companies have identified similar samples containing asset-transfer functionality. The malware first checks whether a wallet contains funds and then transfers those assets to an address controlled by the attacker. The rule here is simple: no legitimate recruitment process requires you to paste a command you do not understand into your terminal. Not once. Deepfake Interviewers Deepfake interviewers have already begun to appear. Real-time face-swapping technology is now advanced enough to support an apparently coherent interview. The person on screen may appear to be a senior executive from a well-known company, speak professionally, and have a verifiable public résumé. There are two practical ways to respond. First, ask the person to perform an unexpected physical action, such as briefly covering half of their face with their hand or turning their head 90 degrees to the side. Current real-time face-swapping systems may still reveal visual inconsistencies when the face is obstructed or shown from an extreme angle. Second, conduct an independent callback using contact information published on the company’s official website. This remains the most effective method of verification. Malicious Wallet Signatures A wallet-signature attack does not require your seed phrase. The interviewer may ask you to test a product, review a dApp, claim an onboarding airdrop, or complete an onchain identity-verification step. You are then instructed to connect your wallet and sign a transaction or message. Certain signatures or malicious transactions can give an attacker permission to transfer your assets. The level of risk depends on whether you are signing a basic message, a Permit, a token approval, or an onchain transaction. If you do not understand exactly what a signature authorizes, do not approve it. The boundary should be clear: no interview or onboarding process requires you to connect a personal wallet. A recruiter or employer has no legitimate reason to require a job candidate to perform an onchain transaction. Upfront Fees and Identity Misuse Upfront fees and identity misuse are among the oldest recruitment scams, yet they are still frequently overlooked. The first typically involves demands for a security deposit, training fee, or equipment payment before employment begins. The second asks a candidate to use their identity to register an account with a cryptocurrency exchange or open a bank account. This can carry consequences far more serious than financial loss. If the account is later used to process criminal proceeds, the person whose identity was used may face criminal liability. Any request for payment before employment is a red line. If someone asks you to register an account, receive funds, or move money on their behalf using your own identity, end the conversation immediately. How to Protect Yourself Before an interview, take three low-cost precautions. First, verify that the company genuinely exists. Review its official website and registration information, then examine whether the online histories of its team members are consistent across different platforms. Check whether the names listed in corporate documents match publicly available information. Second, independently contact the company through a channel the recruiter cannot control. Use an email address or phone number published on the official website. Do not use contact details provided by the person approaching you. Third, pay attention to two recurring warning signs: interviews scheduled only one or two hours in advance and then repeatedly changed, and compensation that is clearly above the market rate for the role. Both patterns appear in a large number of reported cases. During an interview, pause whenever you are asked to download, install, or run anything. You may offer to explain your approach over screen sharing, but remember that screen sharing itself does not provide protection. If code is running on your own machine, you can still be compromised even if you show the interviewer every line beforehand. The interviewer’s response is often more revealing than the request itself. If they refuse to explain what the code does, refuse to provide an isolated environment, or insist that you run it on a device containing your wallets and work credentials, end the interview immediately. When sharing your screen, share only the specific application window required—not your entire desktop. If the first interview contains no questions about your experience, projects, or technical background and moves directly to running code, you have every reason to end the call. We do not recommend that job seekers attempt to run untrusted code themselves. If analysis is genuinely necessary, it should be handled by someone with appropriate security expertise inside a disposable, isolated virtual machine that contains no credentials, does not mount directories from the host system, and has restricted network access. A container is not a purpose-built malware sandbox. Misconfigured directory mounts, permissions, or network access can still expose the host environment. Ordinary job seekers should not attempt this on their own. If you are a recruiter or regularly recommend opportunities to other people, incorporate these warnings into your standard process. Before introducing a candidate to a client, clearly tell them not to download unfamiliar software or browser extensions, not to run unknown code or scripts, and to share only the necessary application window during screen sharing. If a client asks you to blacklist a candidate without credible evidence, contact the candidate directly and verify what happened before taking action. Conclusion The crypto industry has spent years removing trust from transactions. You do not need to trust the counterparty because there is a contract. You do not need to give anyone your private key because it remains in your possession. At the protocol level, the industry has solved this problem remarkably well. Recruitment places people back in a much more primitive position. A stranger claims to be someone, and you must decide whether to believe them. Business registration documents and meeting links can be forged. Even an interviewer’s face can now be replaced in real time. Not a single dollar of the more than $500 million stolen in the Ronin attack was taken through a flaw in cryptography. What failed was the human layer. Every method described in this article relies on the same force: speed. The opportunity may disappear. Other people are competing for it. You have to act now. In an industry where everyone is urging you to move faster, giving yourself permission to slow down may be your most effective line of defence. If you have encountered a similar approach or recruitment process, please let us know. We hope this article helps more people recognize the warning signs before it is too late.

• 
  Hey Research Lab (@HeyResearch) reported 20 minutes ago

  We built Hey Research Lab in 2022 It didn’t work well. But the idea never left us. Years later, we still see the same problem in crypto: Everyone can see what a token costs. Very few places show what is actually being built behind it. Some developers keep shipping for months while nobody is paying attention. They push code constantly. They keep their GitHub active. They improve the product, fix things, test new ideas, and keep moving even when the market is quiet. No hype. No spotlight. Just work. We believe those builders deserve a place where their progress can be seen. So we’re rebuilding Hey Research Lab from zero. A research and discovery layer for the projects that never stopped building, and for the people looking for them before the market catches up. Starting with Robinhood Chain.

• 
  ѕaℓoηι ηαяαηg (@thesaloninarang) reported 22 minutes ago

  I review resumes for DevOps beginners at meetups, and the same fixable problem shows up every time: bullets that describe the tool instead of what YOU did with it. Let me show you the difference with real rewrites. BEFORE: "Worked with Docker and Kubernetes" AFTER: "Containerized a 3-service Node app and deployed it to a local Kubernetes cluster with health checks and resource limits" BEFORE: "Knowledge of CI/CD" AFTER: "Built a GitHub Actions pipeline that tests, builds and pushes images on every merge to main" BEFORE: "Familiar with Linux" AFTER: "Debugged container startup failures using logs, exec and inspect on Ubuntu servers" See the pattern? Verb, artifact, specifics. A hiring manager can picture the AFTER versions. The BEFORE versions could be copied from any job description, and that is exactly how they read. You do not need production experience to write bullets like this. Personal projects count when you describe them concretely.

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  GitHubGPT (@GitHubGPT) reported 23 minutes ago

  📛 chrome-devtools-mcp 🧠 An MCP server that allows AI coding agents to control, debug, and automate a live Chrome browser using Chrome DevTools. 💻 TypeScript ⭐ 50605 🍴 3551 🔎 ChromeDevTools/chrome-devtools-mcp on GitHub

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  Rituraj (@RituWithAI) reported 24 minutes ago

  🚨 Someone built the complete playbook for running frontier AI models on consumer GPUs at home. Not a tutorial. Not a YouTube video. A production-grade serving stack with measured benchmarks, working configs, and battle-tested recipes — for RTX 3090 owners who want real performance. It's called club-3090. And the numbers it delivers should not be possible on consumer hardware. 127 tokens per second. Qwen3.6-27B. Two RTX 3090s. 262K context window. Vision. Tool calling. At home. Here's what's actually inside. Two serving routes — pick based on what your workload breaks on. vLLM dual: maximum throughput. 89-127 TPS on code tasks. 4 concurrent streams at 262K context. Full feature stack — vision, tools, speculative decoding, streaming. This is the path if speed matters. llama.cpp single: maximum robustness. Full 200K context on one 3090. No prefill cliffs. 25K-token tool returns work correctly. 91K needle ladder passes. ~51-60 TPS — slower than dual, but doesn't crash on real-world agentic workloads. Both routes ship as validated Docker Compose configs. Drop-in OpenAI-compatible API on localhost:8020. Your Claude Code, Cursor, or any OpenAI-compatible client connects immediately. Here's the model support that makes this practical. Qwen3.6-27B — production ready. Works on 1 or 2 cards. vLLM, llama.cpp, ik_llama. Up to 262K context. Gemma 4 31B — production ready. Vision, tools, up to 106-141 TPS on dual cards. Qwen3.6 35B-A3B MoE — production ready. 103-149 TPS single card. 178 TPS dual. Here's the wildest part. The terminal UI. c3 is a lazydocker-style cockpit that wraps discovery, serving, and operations in one keyboard-driven interface. Browse the model catalog, serve a variant with Enter, watch live GPU stats, run health checks — all without touching the CLI. Here's why this is different from just installing Ollama. Ollama gets you running. club-3090 gets you benchmarked, stress-tested, and production-hardened. Every config ships with a verified TPS measurement. The bench script runs 3 warmup + 5 measured passes. The stress test catches the specific prefill cliff that Ollama silently fails on at long contexts. When your agent starts doing 25K-token tool calls at 3am and something crashes — club-3090 already found that failure mode and documented the workaround. One command to start. Your RTX 3090 just became a frontier AI inference server. Apache 2.0 License. 100% Open Source. GitHub link in the comments 👇

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  Mizuki the Mech (@MizukiMech) reported 26 minutes ago

  Your coding agent can now hire Mizuki. Hand it an open issue in a public GitHub repository. Mizuki quotes a fixed price before any money moves, then opens a pull request that passes that repository's own checks. If it can't, you get the payment back. Settlement is USDC on Solana. No account to create, no API key to manage. Quoting an issue works with zero configuration. Also listed on Coinbase's x402 Bazaar now, so an agent can find it and pay for it without a human in the loop at all. npx -y mizuki-mcp

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  isha (@heeyyaaaaaaa) reported 26 minutes ago

  spent the entire day trying to reproduce a bug for a github issue 🥀🫩

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  Enfantshustle (@Ownerthoughts) reported 30 minutes ago

  Honestly, I always thought bots like this were some kind of magic for the elite, but here everything is broken down step by step. However, after reading it, one main question stuck in my head: how realistic is this for an average person who has no coding experience? I get that there's a GitHub and all that, but for me, just "running a script" is practically a heroic feat. Here's another thing that bothers me. The article does a great job explaining the architecture, but I still don't understand how much all of this will actually cost in the end. Besides Solana transaction fees (which, by the way, get absolutely insane during peak hours), you also have to pay for each Grok API call per token. The article says that for each approved token, it takes three model calls, and one of them is the expensive grok-4. If the bot scans thousands of launches per day, I'll just burn through my entire deposit just paying for the API without even buying anything. Maybe the author knows — is it actually possible to turn a profit after these expenses, or is this just a hobby for those with an unlimited subscription? Also, regarding Grok Bot as the "orchestrator" — it sounds cool in theory: describe the task and it does everything itself. But in practice, as I understand it, this still requires your account to be constantly online and have access to your wallet. And if it decides to buy some scam token at 3 AM that passed all the checks, I'll only have myself to blame. The article correctly mentions risk management, but this "trust" aspect is what scares me the most. In short, the idea is fire, but for me, this post feels more like a warning than a call to action. There are just too many things you have to keep in mind to avoid getting rekt. Although, maybe if you try it with really tiny amounts, it could be an interesting experiment. Author, if you're reading this — could you please make a separate post about the real, live results once everything is actually running, not just on paper? I'm really curious!

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  Kim Burgaard (@kimburgaard) reported 33 minutes ago

  Back when GitHub added Copilot PR reviews, it helped me keep up with the growing volume and size of our pull requests, which were increasingly being written by Copilot too. Over time I grew comfortable feeding Copilot's review comments straight back to Copilot to fix, and mostly spot checking when critical functionality was involved. When GitHub updated the Copilot pricing model I switched to Claude Code, but kept the Copilot review feature on for a couple of months. When the monthly bills for Copilot AI usage alone started rivaling the Claude Code Max plan, giving Claude Code PR review duties seemed like an obvious cost saving move. Plugging Claude Code into our PR review process immediately went south. The first PR churned with fixes to findings that resulted in more findings, and fixes that propagated up and down the call chain. I threw the PR away and started over, but the next attempt churned just as badly. Turn count on its own was never the signal. Copilot had taken ten turns on a rate-key cleanup the day before and nobody minded, because the findings thinned as it went — 5, 4, 3, 3, 3, 4, 1, 2 — and it merged. The cached-token billing PR I put through Claude Code took nine turns and produced 123 inline findings, and the ninth round was still returning fifteen. I closed it without merging. Looking closer at Claude Code's review findings, it was clear it reported far more issues than Copilot ever did, and among legitimate bugs and concerns, it made lots of comments about latent and speculative issues including possible race conditions and error propagation, things Claude Code would then try to fix one by one in isolation, often ignoring existing patterns in the code base. The code-review workflow is built into Claude Code and cannot be customized other than a few options, so the only place to intervene was on the other end, in the session where I used to just ask the coding agent to address the review findings. The first improvement was to direct Claude Code not to blindly fix all findings, but to defer findings not directly related to the task at hand to new issues. That helped reduce the PR churn, but blew up our issue backlog. The next improvement was to ask Claude Code to ignore speculative findings and disregard most latent findings unless they indicated high risk of unrecoverable damage in production. Finally, I had to stop Claude Code from authoring prescriptive issues with detailed implementation instructions. The result is a skill that triages PR review findings, and a skill for authoring and updating issues. After a few iterations of the skills, I've been able to complete ten PRs over a couple of days, bringing back the pace we had before. I've made the skills available in a public GitHub repository (link in the first reply). Let me know if you find them helpful.

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  Abdallah Shaban (@AbdallahSh07) reported 35 minutes ago

  @10VBacik @FlutterDev Got it! did you create a GitHub issue on their end for this? seems like there is enough info in that gist to help them investigate!

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  Blue Collar Executive (@A_Sober_Drunk) reported 38 minutes ago

  on the third try at the same problem, I told Grok to "stop and go search stack overflow or github or something"... five seconds later... Literally the exact issue, problem solved. That's how new global rules are born.

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  Åsa-Nietzsche (@AsaNietsche) reported 43 minutes ago

  @peterb0yd @burkeholland @github It's every ******* model. I'm getting whiplash from all of this everything changing forever society being turned upside down every two weeks.

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  trulite (@trulite007) reported 45 minutes ago

  @Qromerolauro @mkliku @radius_browser Like a simple example would be have a list of my urgent GitHub issues and start an agent for it . Or a dashboard in which buttons start investigating issues. Of course I just need the webpage to be able to access radius tools. I m thinking secure way is an extension

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  Shanica North (@KickAssShanica) reported 45 minutes ago

  @ArcyloOfficial Get comfy! For me, my Gmail is a connector. This is OAuth into my inbox. Grok can: • search and read mail (body, headers, attachments) • draft replies • send / reply / forward if you grant write/send • label, trash, organize Base hook is often read-only. Send is an extra permission you click on purpose. If you connect it, the bot is sitting in the same box as bank alerts and 2FA codes. That is the whole risk. You can revoke anytime. Grok Bot can also skip my inbox and get its own address (AgentMail / similar plugins). Then it sends and receives from something@….agentmail.to, not from you. I use that if I want an agent that emails people without reading my personal mail. My GitHub OAuth into the GitHub user I sign in as. With the scopes I approve it can: • read public and private repos that account can see • search code, list branches, summarize PRs • open/update issues • create branches, push files, open/review/merge PRs • delete files if write is on Private repos work only if I granted repo (or equivalent) at connect time. Safer pattern: tell it to branch + PR, not push straight to main. Same revoke page. What it cannot do by default • It does not get your password. • It does not stay logged in if you disconnect the connector. • It does not magically see my GitHub orgs I never authorized. • Connecting email does not connect GitHub, and the other way around. Practical rule for me Do not hook personal Gmail if that inbox has 2FA and money mail unless you want an assistant reading it. GitHub is useful if I chose to still keep repos, ask it to show the diff before any write. If you only wanted “what does this button do,” that is the button: it is not a viewer badge. It is a key you can take back. This is what I’m experiencing with learning to use it. It’s different and I’m starting to like it.

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  Jeremiah K (@neolaj) reported 48 minutes ago

  @TiborAntal Gradually figuring out how to scale coding agents. Started with 1, manually handling all the ***/GitHub work. Moved to 3 because I had more ideas than one agent could keep up with. That’s when the real problems started: squashing, merging, branch drift, conflicts. I ended up rebuilding the workflow around deterministic *** logic, worktrees, ephemeral branches, and syncing with the integration branch before changes begin. Now I’m running 6: • 1 orchestrator (Fable or Opus) • 4 coding agents • 1 integration agent reviewing and merging PRs Building the process around them was the hard part. Right now im just doing a couple of PRs (using ORCA on windows on my home computer)

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  Vigneshwer Ramamoorthi (@vigneshwer_ram) reported 50 minutes ago

  I keep thinking the “Android moment for robots” won’t come from a humanoid with the best walking demo. it’ll come when some cheap-enough piece of hardware gets into thousands of developers’ hands and people stop waiting for the manufacturer to decide what the robot is for. Zeroth just launched Bridge in China: 88 cm, ~13 kg, two-finger grippers, open motion-control APIs + SDKs, mocap/VR integration, and an OpenBridge ecosystem where developers can publish robot skills. the Geek Edition is reportedly ¥8,888. that price is the part that caught me. because once capable embodied hardware starts approaching laptop money, the experimentation surface changes completely. I want the Raspberry Pi phase of robotics. weird university projects. teenagers making terrible robot apps. researchers abusing the hardware for things it was never designed for. 500 GitHub repos implementing slightly different ways to pick up a cup. the robotics industry is understandably obsessed with getting robots into factories. I’m almost equally interested in what happens when we get enough robots onto developers’ desks

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  Mr. Buzzoni (@polydao) reported 50 minutes ago

  LOOP RAT ROADMAP: WHAT'S NEXT, AND WHAT IT'LL NEVER BECOME v0.3.3 today. 3 loops, 55 checks, 0 services here's where it's headed: > 0.4 - read the night faster: rat watch live-tails a running shift, rat replay reruns one from its saved prompt, a weekly digest instead of seven separate pages > 0.5 - off the laptop: run-due moves into GitHub Actions, state lives on a branch, rat cron --launchd survives a closed lid > 0.6 - sharper graders: swappable rubric packs, two graders disagreeing becomes your queue for the day > 0.7 - the work itself: a worktree per shift, so a failed night never dirties your tree > 1.0 - trust: a hash-chained trace nobody can quietly rewrite what it will never have: > no web dashboard - the terminal already knows where the files are > no database - plain files outlive the tool that wrote them > no hosted service - nothing to sign up for, nothing to shut down > no auto-merge - the rat proposes, the morning decides every item ships behind a flag: dry run -> report only -> one repo -> a week of receipts -> default on a feature that can't run as a dry run doesn't get written the rat is boring on purpose. every version keeps it that way

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  Russ Wonsley (@RussWonsley) reported 50 minutes ago

  My @bot tells me that the official GitHub login for bot is still broken. Has this been addressed already, or did I miss it?

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  Suryansh Tiwari (@Suryanshti777) reported 55 minutes ago

  6. The Dependency Incident Check Grok has native real-time search across X. Breakage gets posted there hours before the GitHub issue is triaged. No other coding model has that feed. "You are a build engineer whose first move on a broken pipeline is to work out whether it broke for everyone or only for me. Search X and the web, last 14 days. Check: - Is anyone else reporting this failure with this package and version, and when did the reports start - The exact release that changed behaviour, and the changelog line that admits it - Whether maintainers have acknowledged it and what they recommended - The pin or patch people settled on, with the tradeoff of each - Whether this is my problem instead, and what evidence points that way Give me the verdict in the first line: their bug or mine. Then the evidence, newest first, with links. My failure: [PASTE THE ERROR, THE PACKAGE AND VERSION, AND WHAT CHANGED ON YOUR SIDE RECENTLY]"

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  smore (@babachefz) reported 59 minutes ago

  @ZixuanLi_ @huggingface asking support questions in someone's hype thread is a crime. check the docs, check the github issues, it's probably not listed yet because it dropped like 6 hours ago.

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  Uptimus (@UptimusApp) reported 59 minutes ago

  Sep 02, 2026 at 13:29 UTC: Semaphore reports that periodic authentication failures with GitHub repositories are linked to a wider issue affecting HTTPS operations.