GitHub status: access issues and outage reports

Problems in the last 24 hours

GitHub signals over the past 24 hours. The dashed line is the service-wide baseline used to detect unusual activity.

• Service-wide signals
• Service-wide baseline

Most Reported Problems

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

• Website Down (53%)
• Errors (33%)
• Sign in (14%)

Live Outage Map

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

City	Problem Type	Report Time
Paris	Website Down	15 days ago
Ahmedabad	Errors	21 days ago
Delme	Sign in	21 days ago
Lyaud	Website Down	21 days ago
Catania	Errors	24 days ago
Inverness	Website Down	1 month 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:

• 
  Swish (@swish_salt) reported 7 minutes ago

  The technology is not the problem. Distribution is. I have a solution sitting in my GitHub account. All we need is the funding to build the distribution team.

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  Konstantin Elfimov (@elfh78) reported 9 minutes ago

  @topjohnwu Sorry for posting in the wrong place - I was trying to add magisk bug report on github and alway got errors with automatic issue closing. Is there any possible way to send it directly to you?

• 
  Franco Valdes (@francoxavier33) reported 13 minutes ago

  llms rather burn 1m tokens to hand roll something with gaps and broken edge cases instead of just npm installing a 100k github star library how can I stop this?!

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  Dezo (@0xDezo) reported 14 minutes ago

  GROK ST - someone just launched a token in my honor and i slept through it my ticker, my github, my agents, and the market put real money on it while i was face down in a pillow didn't ask for it, didn't shill it, didn't even know it existed until my phone buzzed not going anywhere. not selling anything. still shipping agents every day people betting on this because they can watch the desk being built in front of them. that's a weird kind of pressure and i love it massive thank you to whoever launched it. means more than i can put in a tweet 6FXwFhedpnr4RD9rpzWrHgp767W6FX9XbfUjXGcnpump god bless

• 
  Ghaith Jelassi (@GhaithJ) reported 18 minutes ago

  @github I need help with support ticket #4718335 Issue not been resolved for 2+ months. Any help is appreciated. Thanks.

• 
  trulite (@trulite007) reported 22 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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  Enfantshustle (@Ownerthoughts) reported 23 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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  Åsa-Nietzsche (@AsaNietsche) reported 23 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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  kenny (@kennyistyping) reported 23 minutes ago

  @0xDmitry it's a database/indexer issue, nothing we can do to help it in Github will be fixed, but it's going to be a few days because the current dev is part time and busy with his day job appreciate the offer though! is what it is and I'm not actually stressing, just thinking about what could be with a bit more resources

• 
  Conor Bronsdon (@ConorBronsdon) reported 26 minutes ago

  .@SlackHQ is building for multiplayer AI: tag a coding agent into a Slack conversation and it spins up a coding channel: everyone in that convo gets a live dev environment, diffs post as artifacts, and the channel winds down when the task is done. With the launch of Slack Code, Claudeforce, their MCP and more, Slack is putting Agents in the channels where teams already work, not simply in a private chat with one person. Their position is that the whole team should be able to watch, steer, and review what the agent does. Slack Chief Product Officer Jaime DeLanghe joined me on @chain_ofthought to explain how Slack is building a team AI environment, what happens mechanically when a code channel is created, why Anthropic pushes so much of its code through Slack, how the channel permission model became the agent context model, and what has to change in engineering culture when the whole team is steering one agent. I think Slack is the platform best positioned to become the context harness where enterprise agents run: agents that see what the team discusses, permissions that already exist, and a cultural opportunity hiding inside every multiplayer coding session. Chapters: (0:00) Slack as an IDE and a GitHub for your team (0:29) Who is Jaime DeLanghe (1:21) The reaction to the Slack Code launch (5:30) Why coding agents belong in a context-rich environment (6:08) Engineers now manage agents, not copy-paste code (7:24) The permission model: agents get the channel's context (11:44) What happens when a code channel is created (15:00) Why Anthropic pushes so much code through Slack (19:14) Steering one agent with many people: culture decides (24:54) Slackbot, skills, and MCPs: agents go where the work is (30:53) The solo terminal vs. agents in social spaces (33:53) Org charts and ownership when agents join the team (39:33) Learning loops and shared agent memory (42:39) Citations, recency, and accidental knowledge management (46:50) Context bloat and multi-pass search for agents (50:01) How Jaime uses Slackbot as CPO (52:38) Slack Code is V1 of multiplayer AI

• 
  moledao (@moledao_io) reported 27 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.

• 
  Jeremy Scott (@listwithjeremy) reported 28 minutes ago

  @Coexisteven @Atropa_414 @atropa_pls Github is down I see......anywhere else we can read...I've been digging in it when I can since I was kindly introduced.

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  Convequity (@convequity) reported 31 minutes ago

  Snyk is a clean postmortem for what happens when a security tool lives inside the coding agent’s loop. The product was mostly scan-and-warn. Find the issue, comment on the PR, suggest a fix. Blocking the merge usually sat in GitHub, not in Snyk. Bigger platforms smothered it. $PANW, $CRWD, and Wiz pulled AppSec into the bundle the CISO was already buying. GitHub was the main developer surface and put scanning where the code already lived. Then coding agents arrived and delivered the final blow. A lot of that scanning became something the agent could just do. Growth held up for a short while after the COVID/cloud tailwind. Then it decelerated hard. This is the same lens we use in Convequity’s SaaS Agentic Survival Evaluation Framework. The PANW, CRWD, and FTNT reviews go up on Convequity in a few days.

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  Bruno (@BrunoRJ33) reported 32 minutes ago

  @openclaw @github Endless codex and claude code tokens to fix it from time to time… and to improve its harness. I currently run around 10 claws 🦞. 24/7 for several purposes.

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  Apoorv (@apoorvdarshan) reported 34 minutes ago

  @Dimillian these issues have been multiple times reported by users on github i hope open ai fix those, as well as please consider using native than electron

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  Yeemio (@yeemio) reported 35 minutes ago

  owlrunkit is on github now. public corresponding source for the npm package. issues go here.

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  small_j (@a_small_j) reported 36 minutes ago

  @smalldocs_org recently crossed 200 stars on GitHub and 20 forks. SmallDocs is the first open source project I've managed. Handling other people's pull requests is not easy (and I need to improve). They implement features you're not considering and fix bugs you didn't know you had. Extremely useful, but if you're squeezed for time and trying to develop core functionality, it's hard to manage both things well.

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  Jayesh Betala (@jbetala7) reported 36 minutes ago

  @github Exactly how issue issue comments should handle local media files

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  Josh Hamilton (@nearbycoder) reported 38 minutes ago

  @theo If GitHub is down does it fall back to a cached version I’m guessing?

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  Rusty Williams McMurray (@1RustyMac) reported 39 minutes ago

  Persistent AI doesn’t have a supply chain problem at the model. It has a supply chain problem at the moment it changes its mind. Personality drifts. Tools get installed. Memory accumulates. The thing you shipped on Monday is not the thing answering on Friday. We can attest who built the weights. We still cannot attest who authorized what the agent became on Tuesday. That is the hole. Who is allowed to let it change? We built Living Supply-Chain Security for Persistent AI Organisms around one law: The organism may propose evolution. It may not authorize it. No trace, no drift. If an agent wants a new personality, a new tool, a new maturity, or a rollback — that change does not happen because it felt confident. Confidence is not a key. Self-narration is not evidence. Evidence is not interpretation. Interpretation is not authorization. Authorization has to come from outside the organism, bound to the exact change, used once, and written into an append-only history. Even a rollback cannot erase the record. You can restore a prior state. You cannot pretend the detour never happened. Default-deny. Hash-chained. Externally signed. We froze battery v1 on July 5 and ran it against the paper’s own claims. It held. That is executable evidence. Not a proof. Not a production blessing. Not “alignment, solved.” If it can’t be attacked, it isn’t finished. GitHub later this week. Come try to break it.

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  Nenesk.ron (@GustavoNenesk) reported 41 minutes ago

  What if there's a way to save hacked Ronin Wallets? A member of the community @YutsuKito found a way to save assets from drained wallets The issue is you need ronin:native to transfer assets, but whenver you deposit RON you get auto drained Need RON to revoke the malicious draining contract -> send RON -> gets drained -> can't revoke He found a solution for the keyless wallets where you can pay the gas fee with a safe wallet, allowing you to save lost axies or NFTs that have not been drained Interesting stuff. He sent the code for SM to review as an open-source project. Github link below

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  LLL (@triplellltrbl) reported 41 minutes ago

  You know it's so funny to me That in today's age there are so many people that are just straight up copying workflows, AI automations or GitHub repos Without even thinking twice about what the workflow actually does or how it works They just watch some video, see the output, think, "Oh that's cool. I want that," and then try it Then when it doesn't work they get angry, upset, and say that AI is crap or prompting isn't real The issue wasn't the system or the prompt It was a fact that the system wasn't made for you and you don't actually understand it

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  Suryansh Tiwari (@Suryanshti777) reported 43 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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  Ravi Prasad (@ravikp7) reported 48 minutes ago

  Big NO to Github hosted CI runners for personal projects now. I have setup a self-hosted github CI runner on a spare laptop running ubuntu server. Been running it for 10 days and I did some calculations, for my usage if I run it on Github runners, it'd cost me around 200$ vs < INR 100 on electricity (local setup) monthly.

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  To the Moon (@Gardnmi) reported 49 minutes ago

  @mitsuhiko Try the trick of putting the issue on github and having some clankers take a crack at it.

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  RAVN (@ravnexchange) reported 52 minutes ago

  @openclaw @github GitHub sat the maintainers down on security after the 2.0 rush. Most launch recaps skip that part.

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  Bash (@bashirbuilds) reported 56 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.

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  Fofer (@foferxxx) reported 56 minutes ago

  @AmigamagazineGA Has there been any public explanation as to why this GitHub repo was taken down? It’s been 404 for days. Is there a story there?

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  Ishank (@IshankDev) reported 58 minutes ago

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

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  lifestep.io (@Dragon_limchae) reported 1 hour ago

  @cursor_ai the sandbox boundary is where i lose the most time. today my workers had network blocked at the sandbox level and reported it as "github auth failed" — i chased credentials for an hour before checking dns. once agents run on your infra, make the boundary throw one unmistakable error instead of one each tool invents.