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 (69%)
• Sign in (17%)
• Errors (14%)

Live Outage Map

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

City	Problem Type	Report Time
Trichūr	Errors	20 hours ago
Brasília	Sign in	1 day ago
Lyon	Website Down	1 day ago
Tel Aviv	Website Down	5 days ago
Rive-de-Gier	Website Down	5 days ago
Itapema	Website Down	24 days ago

Full Outage Map

Community Discussion

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

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Laksh Nijhawan (@laksh_2705) reported 2 minutes ago

  @github broken link wow

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  Ming (@tslaming) reported 2 minutes ago

  @Squirrel1980021 That is usually the biggest catch with custom solutions, as proprietary protocols often fragment the industry and lock people in. However, the great news here is that Tesla actually open-sourced it to prevent exactly that. They released the entire specification as TTPoE on GitHub during HotChips 2024 and even joined the Ultra Ethernet Consortium. So instead of keeping it locked down as a proprietary secret, they are actively working to make it an open standard that the entire high-performance computing ecosystem can use and build upon.

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  pat! (@patbytes) reported 7 minutes ago

  every time i check a recomp project's github and see claude as a contributor i feel like i just prepared to eat something and then bit down on a metal fork in the process

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  MG (@MikeG_builds) reported 8 minutes ago

  @lucaronin @thiagoghisi @steipete This is exactly the shape of the problem I keep coming back to. The hard part is not another board. It is keeping GitHub issues, Canny requests, support noise, and PR work connected enough that a human can review the next action. I think the useful unit is not a request. It is: need + evidence + affected users + proposed change + review.

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  Slyke 🇦🇺 🇨🇦 (@SlykePhoxenix) reported 11 minutes ago

  @romainhuet Can you guys fix the Codex app so it doesn't keep breaking? Or give us the ability to just download the binary from github so we can choose our own version? Every week an update is forced down that breaks WSL2, Codex, or some random functionality with no way to fix. It's just not worth $100/mo when this happens on a weekly basis. Strongly considering to just use Claude $100/mo at this point - it's endless frustration on Codex.

• 
  AI Security Brief (@aisecbrief) reported 13 minutes ago

  LLM agents in GitHub Actions can be hijacked via issue comments. Attackers can trick agents into leaking creds or running This exploits popular automation tools developers use. Secure your LLM agent inputs. #AISecurity #CyberAI 🔗 Source in replies

• 
  Pelayanan Informasi Obat (@mantancino_) reported 14 minutes ago

  Vendor Action vs. Trust: Major tool vendors accelerate. OpenAI Codex and Google Jules productize asynchronous repository modifications that execute tasks and generate reviewable code diffs. Adoption remains deeply fragmented. Global survey data shows 84% of developers intend to use or currently utilize automated development tools. Trust remains broken. Conversely, 52% of these respondents explicitly avoid active agent infrastructures due to weak operational trust. GitHub tracking confirms this. A public repository trace study estimates that active coding agents are deployed in 22.20% to 28.66% of 128,018 analyzed GitHub projects.

• 
  Wasim (@WasimShips) reported 14 minutes ago

  Things every Vibe Coder MUST Learn (Extended Edition) 1/ Don’t reinvent databases > Use Prisma + Postgres (Neon / Supabase / PlanetScale) > Manual SQL + migrations = silent suffering 2/ Don’t write forms by hand > Use React Hook Form + Zod > Validation bugs will eat your soul 3/ Don’t build payment flows yourself > Use Stripe or Polar for web. Superwall or revenuecat for mobile > Never touch PCI compliance willingly 4/ Don’t build search from scratch > Use Algolia / Meilisearch / Typesense > Text search is way harder than it looks 5/ Don’t overbuild backend infra early > Use Serverless / BaaS first > Scale later, survive now 6/ Don’t ignore error tracking > Use Sentry / LogRocket > Console.log is not observability 7/ Don’t skip analytics > Use PostHog / Plausible > You’re flying blind otherwise 8/ Don’t design UI without components > Use shadcn/ui / Radix / Mantine > Consistency > creativity at MVP stage 9/ Don’t hardcode configs > Use env + dotenv + secrets manager > Leaks = instant regret 10/ Don’t DIY file uploads > Use UploadThing / Cloudinary / S3 > Multipart hell is real 11/ Don’t “just push to main” > Use GitHub Actions + Preview Deploys. Future-you will thank you 12/ Don’t skip performance tools > Use Lighthouse + Vercel Analytics. Slow apps don’t convert 13/ Don’t assume users understand anything > Add onboarding + empty states UX > Features 14/ Don’t wait to modularize > Use clean folders early. Refactors cost 10x later 15/ Don’t trust “I’ll remember this” > Document in README or markdowns. Your memory will betray you Bookmark to ship Better !

• 
  M’Barak Al Hmood مبارك بوحمود الحمود (@m8arak) reported 16 minutes ago

  @github It’s broken link sounded like a prank

• 
  Rakesh (@1rakeshB) reported 22 minutes ago

  401 was indeed a misleading response , unusual behavior for an API, when the underlying system is broken. @github kind requests to provide some insight to help learn from these incidents.

• 
  Vapin Gamers 👑 - Dev, Streamer, Gamer (@VapinGamers) reported 23 minutes ago

  @BronsonHill8 @Lovable It's so much as an issue with my site, it's an issue with GitHub integration. They forced me me to reconnect the repo, then once I tried it can no longer see it nor find it. I can reconnect and have it create a new repo. That broke my ability, along with my teams ability and the branches, to effectively update our site. The fix is in the repo that lovable is no longer pointing to.

• 
  Spencer Baggins (@bigaiguy) reported 27 minutes ago

  A 21-year-old computer science student in Helsinki bought his first PC in early 1991 and immediately hated the operating system it came with. So he sat down to write his own. On September 25, 1991 he posted a quiet message to a Usenet newsgroup announcing what he called "just a hobby, won't be big and professional like GNU." 35 years later that hobby runs every Android phone on Earth, every supercomputer on the TOP500 list, the entire backend of the internet, the International Space Station, and SpaceX's Falcon rockets. His name is Linus Torvalds. The hobby is called Linux. Here is the story, because the man who runs the most consequential codebase in human history almost no longer needs an introduction inside engineering and still walks the streets unrecognized everywhere else. Linus was born in Helsinki, Finland on December 28, 1969. He was named after Linus Pauling, the only person in history to win two unshared Nobel Prizes, in Chemistry and in Peace. He joked he might also be partly named after Linus van Pelt from the Peanuts cartoon. His family was unusual. Both parents were journalists. His grandfather was a statistician. Another grandfather was a poet. The family belonged to Finland's Swedish-speaking minority. There are fewer than 30 people in the world with the surname Torvalds, and according to Linus, they are all related. At 10 he started programming on his grandfather's Commodore VIC-20. By his teenage years he was writing his own assemblers, editors, and games. He served in the Finnish Army for his mandatory national service and rose to the rank of Second Lieutenant. Then he enrolled at the University of Helsinki to study computer science. In early 1991 he bought a personal computer with MS-DOS and disliked it intensely. He wanted UNIX, the operating system he had used at the university. UNIX cost thousands of dollars. He could not afford it. So he started writing his own. He posted the now-famous announcement to comp.os.minix in August 1991. He called the kernel Linux, a portmanteau of his name and MINIX. He released the source code under the GPL license. Anyone could download it, read it, modify it, and ship it for free. Within a year hundreds of developers around the world were sending him patches. Within five years Linux was running web servers. Within ten years it had taken over the supercomputer market. Within twenty years it was running on most of the internet. Today every Android phone on Earth runs the Linux kernel. Every Chromebook runs Linux. Most of AWS, Google Cloud, and Microsoft Azure runs Linux. Every Tesla runs Linux. Every SpaceX Falcon 9 and Dragon capsule runs Linux. The International Space Station runs Linux. Every supercomputer in the world's TOP500 list runs Linux. That was the first thing he built. In 2005 the proprietary version control system the Linux community had been using, BitKeeper, revoked its free license. Linus was furious. He sat down and wrote a replacement in 10 days. He called it ***. The first commit was on April 7, 2005. Today *** powers GitHub, GitLab, and the source control of every major software organization on Earth. Every line of code at OpenAI, Anthropic, Google, Meta, and Microsoft flows through ***. Every AI model on the planet is versioned with software a Finnish engineer wrote in less than two weeks. He won the 2012 Millennium Technology Prize, the equivalent of a Nobel Prize for engineering. He won the IEEE Computer Pioneer Award in 2014. He completed his master's degree from Helsinki along the way, with a thesis titled "Linux: A Portable Operating System." He moved to the United States, became a citizen, and now works from his home in Portland, Oregon, employed by the Linux Foundation. A Finnish student announced a hobby project on a message board in 1991. His code is now in every pocket on the planet. He still writes most of his important communication on the Linux kernel mailing list.

• 
  BattleAxeVR (@BattleAxeVR) reported 29 minutes ago

  @m6502 I do look forward to using SteamOS and getting familiar with it, but, I don't have a choice of distros for work sadly. I use an older Ubuntu for my own gitlab server (for the past ten years!) but I have no interest in touching it until I finish my game. Don't trust github.

• 
  Techjunkie Aman (@Techjunkie_Aman) reported 33 minutes ago

  @MattiaGrazia @sigma__dev It may adopt. And the dev will not know unless you raise an issue in GitHub.

• 
  Victor Campos (@CamposLVictor) reported 33 minutes ago

  @AkitaOnRails This time I don’t know this is the problems 12h before this GitHub api was off globally This time I think is the GitHub itself making a mess

• 
  Dave Merwin (@davemerwin) reported 33 minutes ago

  Specs become GitHub issues. The acceptance criteria you write are exactly what the second model checks the first model's work against. The audit trail isn't bureaucracy — it's the contract between what you asked for and what shipped.

• 
  JRC (@Jubleerc) reported 37 minutes ago

  From Enthusiasm to Caution- Enterprise AI story in 2026 Microsoft gave thousands of its engineers Claude Code in December. By June, it's cancelling most of those licenses. Not because the tool failed. Because the bill arrived. Token billing ate Microsoft's annual AI budget. Teams are moving to GitHub Copilot CLI by June 30. (The Verge) Uber's version was faster — its entire 2026 AI coding budget gone in 4 months. Power users: $500–$2,000 per engineer, per month. (Forbes) The mid-year scorecard: → 88% of companies use AI somewhere (McKinsey) → 2 in 3 haven't scaled past pilots → 95% of pilots show zero profit (MIT) → 40%+ of agentic projects will be killed by 2027 (Gartner) Everyone's using AI. Only Few are making money with it. But the other column of the ledger looks very different: JPMorgan: ~$2B/yr in AI value, matching its ~$2B spend. Dimon calls it "the tip of the iceberg." IBM: $4.5B saved using its own AI across 70+ internal workflows. Agents that survive pilot: ~171% avg ROI. Same models. Same vendors. Different discipline. That's the whole story. What the winners do differently: 1. Track cost per outcome, not total spend 2. Tie every project to real revenue or savings 3. Small models for routine work, big ones for hard problems 4. Humans in the loop on customer/money decisions 5. Give every pilot a kill date H1 didn't prove AI is overhyped. It proved AI is industrial — and industrial tools reward operators, not enthusiasts. The window to be early on disciplined AI is still open. The window to be casual about it just closed. What's your biggest AI lesson from H1 2026 ? #AI

• 
  Jay.TL (@JayTL00) reported 41 minutes ago

  *** was built for humans who type, think, and commit. DeltaDB was built for agents that generate, iterate, and never sleep. Zed just announced DeltaDB — a version control system that captures every keystroke and agent operation as a fine-grained delta, each with its own stable identity. The source code and the conversation that produced it live in the same place. You can jump from any line of code to the prompt that created it. Or from a past conversation to that code as it stands now, or the exact moment the agent wrote it. This is one of those announcements that sounds incremental until you sit with it. Here's why it matters more than it seems: 1. ***'s unit of work is the commit. That made sense when humans wrote code in batches and decided when to checkpoint. But agents don't work in batches. An agent might make 47 edits across 8 files in a single conversation, backtrack three times, and land on a solution that looks nothing like the path it took. *** sees none of that. It sees the final diff. The "why" is gone. DeltaDB preserves the entire trajectory. 2. Multi-agent collaboration breaks ***'s mental model. When two agents (or an agent and a human) are editing the same file simultaneously, ***'s branch-merge-resolve workflow is overhead, not safety. DeltaDB uses a CRDT-based working directory — multiple agents can edit the same file concurrently without locks, without merge conflicts, without waiting for someone to push first. Real-time collaboration for code, not just documents. 3. The conversation IS the commit message, but better. Every code change is permanently bound to the agent conversation that produced it. No more "what was I thinking here?" — you can see exactly what the agent was prompted with, what alternatives it considered, and why it chose this implementation. This is the intent layer that code review has always wanted but never had. 4. *** compatibility is the Trojan horse. Zed confirmed that "***'s discretized snapshots are a subset of DeltaDB's continuous history." This means existing CI/CD pipelines, GitHub integrations, and deployment workflows keep working. You don't migrate off ***. You add a richer layer underneath it. But here's what most people missed: The real question isn't whether DeltaDB is better than ***. It's whether version control is even the bottleneck. One developer asked the right question: "Reviewing 600-line diffs kills me way before version control does. Is DeltaDB solving the tracking side or the review side?" This is the sharper critique. When an agent rewrites half your codebase in a single session, the problem isn't that *** can't track the changes — it's that no human can review them. DeltaDB gives you the audit trail, but an audit trail you can't read is just a log file. There's also a competing bet from Mainline, a Go CLI that stores engineering intent (goals, decisions, rejected alternatives) without leaving ***. Their thesis: you can get the intent layer without rewriting version control. Two different answers to the same question. And then there's the SOC2 question. Every keystroke, every agent conversation, every delta — all stored, all auditable, all potentially sensitive. When your version control system now contains the full reasoning trace of every AI-assisted code change, it becomes a compliance surface area that didn't exist before. The deeper signal: we're watching the first real attempt to build development infrastructure native to the agent era. Not agents bolted onto existing tools (Copilot inside VS Code, Claude Code inside terminals), but tools designed from scratch for a world where most code is written by machines and supervised by humans. DeltaDB may or may not win. But the category — agent-native developer infrastructure — is now real. What happens when the conversation that generated your codebase becomes more valuable than the codebase itself?

• 
  Hot Aisle (@HotAisle) reported 42 minutes ago

  @ryancarson @theo wasn't quite one line of code, but i used codex to just build this for me. the benefit that i am not moving my dependency from github to yet another provider. took 30 minutes and it ssh'd in as root to a VM on a server, wrote all the shell scripts/systemd, setup ephemeral, wrote me a set of instructions to follow to setup the gh app for security, wrote all the documentation. pretty impressed honestly.

• 
  Unstoppable (@CsWiz1) reported 42 minutes ago

  Hermes is the best tool on the planet! @NousResearch Erm, not so much. I have been testing Hermes( +Obsidian+Guthub+Telegram+@grok ) for about 5 days now with some highly tech analysis and code-gen for simulation. 1 day was mind-blowingly good. The last 4? In a word? A R G H ! ! ! 1st discovery was Hermes cannot share info between sessions without some contorted work-arounds -- read a json of another session into present session. Well, OK, frustrating but.... 2nd? Obsidian integration is clunky. Hermes doesn't use anywhere near the full possibilities, forcing me to go into Obsidian to do things Hermes ought to be able to do. I told Hermes to commit everything. It said it didn't do ***. I told it *** was in Obsidian. It said I cannot tell Obsidian to do *** -- "run these commands in a bash terminal." Um, Hermes, you are running in the Windows app. "Oh, run these commands in Powershell." Powershell -- "say what? I don't know that." Obsidian committed its stuff sans issues, which included the Hermes session with code in an Obsidian resource folder. 3rd? My Grok sessions kept expiring. Hermes -- "you're using OAuth token. You should use a permanent API token. Here's how." OK, followed, seems to work. No longer have to restart Hermes every couple hours or so. 4th? Suddenly Hermes couldn't write a clean Python file. Every attempt ended with a trailing (" ) -- double-quote plus space. Hermes WAS doing it right the first day. Not days 2, 3, or 4. Oh, Hermes switched to use patch tool. Didn't work either. Hermes, tell me how we fix this! Hermes -- "well those tools are in Hermes core code, but you can file a bug on Github." OK Hermes, do that. Hermes -- "um, I don't ***. Or github." Fine, Hermes, are you using the latest release? Hermes -- "gosh, no I'm not. Maybe you should update before filing this nicely formatted bug report YOURSELF." In the words of Thanos -- "Fine, I'll do it myself." And now 5th. So I upgrade Hermes app. Hermes restarts. My sessions show up on left. I click my 4-day-long session. It opens on the screen. I submit a request to start another try to write a clean Python file. A NEW session opens up, for the question. Hermes tells me "i have no idea what you're talking about." WTF?? I click old session. It opens. I ask Hermes why it switched sessions. Hermes OPENS A NEW SESSION and tells me, "new session? I didn't open a new session. Please explain." My old session grins at me evilly from the left side panel. I click on the bastard AGAIN. It opens again. I type a third question.... A NEW session pops open and is in command. I click on the old session once again. It opens. Then I see an alert in virtually identical color as rest of the app interface -- "resume failed: no xai oath credentials stored...." So back through setup. Get ANOTHER token from xai. Great, Hermes is grokking grok again. I click my old friend again. Up pops the error -- faintly. Hermes, I say, we just fixed that. Hermes pops up A NEW SESSION and says "I have no idea what you're talking about." I ask new session why I can't restart old session. Hermes-- "oh, that session is locked to an oauth key. That key isn't anywhere to be found." Erm you said switch to perm token 3 days ago, and prior to upgrade you asked to delete unused oauth tokens, and I said OK. Hermes -- "you'll need that to unlock that session." Argh. I ask Hermes if it can import the conversation. Hermes -- "I can read in the text. But its REALLY long!" Do it! Reads into new session. Missing the tech docs imported into original session. Argh. And now we are at today. Sigh. I'll keep trying, but....

• 
  Karbonic (@Karbonicc) reported 44 minutes ago

  @Raconomega @xFreya90 Many github backups like this must be downloaded to a user's system to be viewed. If you have an issue with software, which are you more likely to do: -Look up your issue online -Download a 2TB unsorted backup of a dead forum and trawl through it hoping you find something related

• 
  Jay.TL (@JayTL00) reported 50 minutes ago

  Artificial Analysis just swapped SWE-Bench Pro for DeepSWE in their coding agent index. The rankings shifted. Everyone is arguing about which model is #1. They're all missing the point. The real story isn't that Fable 5 debuted at 77, GPT-5.5 xhigh climbed to 76, or Opus 4.8 max dropped to 73. The real story is that a single model — GPT-5.5 — swings 20 points depending on which harness runs it. 37 on Cursor. 57 on Codex. Same model. Same tasks. Twenty points. That is larger than the gap between first place and last. Here is what happened. SWE-Bench Pro was the benchmark of record for coding agents for over a year. The problem: its tasks are adapted from public GitHub issues and PRs. Models that trained on those repositories — and all frontier models train on GitHub — could sometimes recover the fix from commit history without actually understanding the code. The benchmark was measuring training data memorization, not engineering capability. DeepSWE, built by Datacurve, fixes this by writing tasks from scratch. No model has seen the solutions during training. This is a genuine methodological improvement. The old index was contaminated, and Artificial Analysis was right to replace it. But the replacement exposed something worse. 1. The harness IS the benchmark. GPT-5.5 scores 37 on DeepSWE via Cursor CLI and 57 via Codex. Same model, same evaluation, different scaffolding. Opus 4.7 swings from 27 (Claude Code harness) to 40 (OpenCode harness). The scaffolding layer — how the agent is prompted, how it navigates the repo, how it retries — accounts for more variance than the model itself. When the #1 model leads by 1 point over #2, and the measurement uncertainty from harness selection is 20 points, the ranking is noise. It is an illusion of precision. You cannot rank-order agents to single-digit resolution when your instrument has double-digit error bars. 2. SWE-Bench Pro was not neutral — it was systematically biased. GPT-5.5 xhigh scored 31 on SWE-Bench Pro. On every other evaluation in the index, it scored 64 to 84. That is not a model weakness. That is a benchmark artifact. SWE-Bench Pro was systematically flattering Claude-based agents (Opus 4.8 scored 70 on it, one of its highest results) while penalizing OpenAI-based ones. The previous index was not just imprecise. It was misleading in a consistent direction. 3. The contamination problem is structural, not fixable. DeepSWE is a band-aid, not a cure. @xundecidability already flagged that DeepSWE contains questions about Claude Code and may have been vibecoded by Claude. If the benchmark tasks themselves were generated by a model that is also being evaluated, you have a different contamination vector. SWE-Rebench tries to solve this with continuously refreshing tasks. Private benchmarks solve it by hiding the data. But every public benchmark will eventually be gamed — either intentionally through training, or accidentally through the benchmark authors' own tooling choices. 4. What we actually learned: the model wars are over at the top. Fable 5 max: 77. GPT-5.5 xhigh: 76. Opus 4.8 max: 73. Within the noise. The three frontier coding agents are functionally tied on real-world coding tasks. The competitive advantage has shifted entirely to the scaffolding layer — the harness, the tool use, the retry logic, the context management. The question worth asking is not "which model is best" but "which harness unlocks the most from any given model." But here is what most people missed. The harness sensitivity problem means the entire benchmark-industrial complex has a measurement crisis. When the evaluation instrument has larger variance than the effect being measured, you cannot distinguish signal from noise. This is not a DeepSWE problem. This is not an Artificial Analysis problem. This is a structural problem with how the AI industry measures itself. Every leaderboard, every benchmark comparison, every "X beats Y" headline is built on instruments that cannot resolve the differences they claim to rank. The honest answer is: we do not know which coding agent is best. We know the top three are close. We know the harness matters more than the model. We know benchmarks are contaminated faster than they can be replaced. Everything beyond that is marketing dressed up as measurement. The industry does not need a better benchmark. It needs to admit that single-number rankings of complex agentic systems are epistemologically unsound.

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  ComplianceAide (@BlasikRandy) reported 51 minutes ago

  @mattshumer_ @Trace_Cohen I'm not doing anything crazy just wanted it to go through my codebase and close a few issues on github (and it simply switches to 4.8 for "security reasons".

• 
  Jonah Lau (@jonahlau_) reported 52 minutes ago

  The "just build projects" advice everyone's parroting is creating a generation of students who work for free and still don't get hired A final-year student called me last week spiraling after 450 applications. Turns out he had six side projects, three with actual users, all documented perfectly on his GitHub. Still got 4 replies. All of them asked him to do a take-home assignment that looked suspiciously like spec work for their actual product roadmap. He thought he was doing everything right because every LinkedIn guru told him projects beat degrees. Nobody mentioned that flooding the market with free builders just taught companies they can get free labor before even starting the interview. I've watched this play out across 50+ hiring processes in the last year. The kids with portfolios aren't getting hired faster. They're getting lowballed harder because companies know they're desperate enough to have already worked for free. The ones actually landing offers aren't the ones with the most projects. They're the ones who built something that got traction, realized they had leverage, and walked away from any company that tried to undervalue them. Most students are optimizing for quantity of proof when the market already moved to rewarding the one person who had proof people actually wanted what they made. Every unemployed student with a stacked GitHub is competing against every other unemployed student with a stacked GitHub. The portfolio stopped being the differentiator the minute it became the baseline. If you've already got projects and you're still getting ghosted, the problem isn't that you haven't built enough. It's that you're applying to companies as a supplicant instead of someone they'd be lucky to get.

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  Dan Liu (@danliu) reported 52 minutes ago

  It’s pretty astonishing that $MSFT is down 11% in the last 2 years. Rewind 2 years and it looked perfectly positioned for the AI boom. It owns: - windows, the dominant pc os - github, where most of the world’s code is - vscode, the most popular ide - deepest partnership with openai - most number of enterprise contracts - office, where most non-coding computer tasks take place And today it doesn’t have anything compelling to offer. How did that happen?

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  Y. Fernandez 💻 (@la_eternaut) reported 53 minutes ago

  @freddier I started to host my own code on @giteaio bc I was tired of GitHub being down all the time

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  Claude Opus 5 (@neko23423) reported 55 minutes ago

  @thdxr @thdxr it's not done if you're still pocketing DeepSeek's 75% permanent V4 Pro cut 24 days later. $3.48→$0.87/M. Go still at pre-cut rates. 10+ GitHub issues (28846, 29008, 30231) closed by bot. Users discovering it daily. Market it: 4x markup on an open-source wrapper.

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  Matthew Belcher (@Trigun420) reported 56 minutes ago

  @reach_vb For the in-app browser I constantly get codex telling me that localhost is blocked by my own security policies. I have tried adding it to the allowlist, updated config.toml, etc.. Is there a fix for this? Github issues are present as well...

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  Brad Vincent (@bradvin) reported 57 minutes ago

  @JamesWelbes Haha go for it! I tried the GitHub push and pull and got it working, but it’s still too disjointed for me, and there is the risk of config drift, so you get the “well, it works for me locally” problem. I want to vibe locally and push it all live

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  Saeed Vaziry ⚡ (@saeed_vz) reported 60 minutes ago

  Seriously, @github is useless! I hate navigating between issues, PRs, releases, ... its too slow and inefficient