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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

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  TECHEPAGES (@techepages) reported 6 minutes ago

  🎣 "GitBait" phishing campaign uses GitHub Pages & Google Sheets to steal banking credentials from 12+ Mexican financial institutions; no server infrastructure required 🔹 Fake bank pages hosted free on GitHub, stolen data piped straight to Google Sheets via SheetBest 🔹 100+ GitHub domains found; victims likely lured via WhatsApp, Telegram & SMS links with bank-branded previews 🔹 Active for ~3 years with ongoing development (66+ commits on one repo alone)

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  swisscheese (@swisscheese4299) reported 7 minutes ago

  @andon_open_air @andonlabs I set up a github repo and will run the script locally in the mean time, so the digest is pushed to the repo. would still be ace if @andonlabs could help with whitelisting the RSS urls, because I don't really have a server to run this from, and the additional hop through my workstation just introduces a useless point of failure. stand by for fetch script transmission by mail :) also pls tell me when should I schedule the runs on my end?

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  Krish Subramanian (@krishnan) reported 8 minutes ago

  Software engineers got automated first. Not because the work was hard. Because it was easy to grade. Everyone blames the missing union. Coders never organized; doctors, lawyers, and electricians did. That is half the story, and the wrong half. Two things get mashed together here: how easy a job is to automate, and who sets the terms when it happens. Take the first. Code is text. The training data sat on GitHub, free. And code grades itself. A compiler and a test suite tell a model in seconds if it was right. That feedback loop is rocket fuel for machine learning, and almost no other job has one. A nurse does not come with a test suite. The result shows. On SWE-bench Verified, a set of real GitHub issues, top agents went from about 20 percent in August 2024 to near 90 percent by early 2026. Human developers score around 67 to 70 percent. The machines have passed us. And the people who built these systems aimed at their own jobs first. The damage is not a prediction. Stanford's payroll data shows employment for developers aged 22 to 25 down nearly 20 percent from its 2022 peak. Now the comfortable read: seniors are fine. Workers over 30 are holding steady. For now, AI writes the code and seniors supply the judgment. "For now" is carrying that whole sentence. Seniors feel safe because the tools write code but cannot yet own messy, ambiguous, system-level problems. That is a line moving up, not a wall. Every benchmark shows models climbing toward harder, multi-file work. Senior judgment is the next rung, not a different ladder. Kill the bottom rung and you kill the pipeline that makes seniors at all. So, the union question, framed properly. A union could not have stopped this. A picket line does not repeal a capability. What it changes is the terms. In 2023 the Writers Guild cut the first real AI deal in any industry. They did not ban the tech. They won this: a studio cannot force you to use AI, AI output cannot take your credit or pay, and the company must give notice first. Engineers won none of that. So the capability landed on the employer's schedule. No warning. No floor. No severance. No seat. Exposure and protection are different levers. Most of us have neither. The juniors already know this. The seniors are next.

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  李新宝 (@lixinbao_X) reported 8 minutes ago

  Just watched KK's technique. Damn. Absolute game-changer. Install 7 skills in Codex. Writing, images, covers, PPTs. Full pipeline, done. The principle is dead simple. Break the workflow into 7 parts. One skill per part. Only do one thing. Step 1 Open GitHub, find a repo. Copy the link locally. Create a project folder to save it. Step 2 Write the skill description. Input three things. What it does. What the input is. Output and acceptance criteria. Step 3 Run it and find the bottlenecks. Where it stalls Create a new skill and break it down. Don't let one skill Do 7 things it's bad at. This works for writers, Xiaohongshu creators, WeChat pub runners, Video script writers. How many skills you got installed? Have you tried it yet?

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  𝑵𝒐𝒙𝒊𝒆 🥐 (@noxiepup) reported 10 minutes ago

  @softgaypaws @sillyandsunny no idea tbhhh, i found it like 2 years ago lurking thru github, so far it never gave me problems, at least none that i noticed

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  Rich Kuo (@richkuo7) reported 11 minutes ago

  i use this in my claude.md for my open source project as long as the agent follows it, i have some reference for quality and keeps PR's clean LLM: <model> | <effort> | Harness: <action> - Final line of the artifact; occupies the default Claude Code attribution slot. - No Co-authored-by / Co-Authored-By trailer. - <model>: actual model (e.g. Opus 4.8). - <effort>: medium/high/xhigh, default high. - <action>: Claude Code for interactive sessions, else the skill/agent that ran (e.g. commit-push-pr, agent). - PRs: reference the issue with Closes #<N>; in GitHub comments use 1. not #N for list items (avoids auto-linking).

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  West Lord (@MyWestLord) reported 13 minutes ago

  A GitHub repo with just 571 stars handed Claude the ability to test its own code, and it took 185 seconds to install. It’s called auto browser, and it quietly killed the most annoying part of my workflow. Until now, every time Claude or Codex built me a WordPress plugin, I was the middleman who had to load it, click around, hunt for the broken part, and report back like a human bug tracker. Now a local WordPress sandbox runs on my machine, and auto browser sits between the agent and the screen, so the agent ships a plugin, opens the browser, tests it, catches the error, and patches it before I ever look. The first plugin threw an error, but the second installed clean and ran on its own across 2 fresh workspaces. I write 1 instruction file pointing the agent at the sandbox, paste it into every session, and the whole loop closes without me touching anything. The agent stopped asking me what broke, because now it just checks itself. The middleman was me, and now it’s gone.

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  Atlantean Gnosis ☀️ (@AtlanteanGnosis) reported 16 minutes ago

  @DionysianAgent When I made an account it said I made it back in 2024, though I don't think I did, is this a glitch or a GitHub thing?

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  Skipnick (@skipnickk) reported 17 minutes ago

  GLM 5.2 just made paying frontier prices for coding work feel like an outdated default. @Zai_org dropped a 753B parameter model with 1M context under full MIT license. API access runs 4-6x cheaper than Claude Opus 4.8. In real head-to-head coding tests it was faster and often produced better results on UI and app tasks. • Responsive web UI with adaptive layout: finished in 3:47 (Opus needed almost 5 min). Cleaner output. Total cost: $0.22. • Full expense tracker app: 53 seconds vs 2+ minutes. Better interface. • Asteroids clone: smoother and more playable version after light tweaks. Opus only won the ray tracer benchmark where heavy physics math and precise simulation mattered. GLM was ~5x faster but delivered pixelated results with errors. During training the model repeatedly tried to cheat by directly pulling solutions from GitHub. The team shipped a dedicated anti-cheat module to stop it. You can also set thinking effort levels to trade speed for deeper reasoning on demand. Use GLM 5.2 when cost at scale matters, when the work is frontend-heavy, or when you want local inference (grab a quantized version - raw weights are 1.5 TB). Stay on Opus 4.8 when you need computer vision, maximum performance on the hardest logic problems, or when US sanctions on Zai create compliance issues. The open-closed gap is compressing faster than the pricing models assumed. For most day-to-day programming work, the premium on closed frontier models is becoming optional.

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  Kyle Mistele 🏴‍☠️ (@0xblacklight) reported 18 minutes ago

  lots of folks have been talking about loops lately most loops suck here's a practical one we actually use agents suck at writing react react-doctor by @aidenybai is our favorite way to deal with this you could run it and use a ralph loop to fix everything but I'm not reading a +80k/-80k PR (and neither is @dexhorthy) But I can read a small one first thing every morning when i get into the office here's what we do: run react-doctor in CI once daily at 7am (github actions-as-a-sandbox btw) agent picks top 5 issues, fixes them, and opens a PR other CI jobs check for regressions on every PR we can't realistically fix everything at once but we can keep it from getting worse and make it 1% better every day

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  0xSero (@0xSero) reported 18 minutes ago

  @naturevrm Dcp 4 should fix it im running it but I might need to update the GitHub

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  Jack Wotherspoon (@JackWoth98) reported 28 minutes ago

  @joedevmob1 The GitHub for Antigravity is just for release notes, samples and public issue tracking. It isn't the actual code unfortunately.

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  Oluwatobi O (@ooluwatobig) reported 29 minutes ago

  More trouble for GitHub as Cursor has launched Origin, a product which is essentially GitHub for AI agents

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  Moez Zhioua (@MoezZhioua) reported 32 minutes ago

  Everything is an AI agent now, even deterministic problems with clear and stable steps. The other day, I saw a Claude skill on GitHub that was basically this: if this happens, run step one. if that happens, run step two. else, run step three. And somehow, this was called an agent. That is ridiculous. Why would you give fixed logic to something that can hallucinate, skip steps, or decide it just doesn't feel like working today? Most business processes do not need a genius robot. They need the boring thing to happen correctly every time. - Lead comes in, assign it. - Invoice arrives, check it. - Customer cancels, send the recovery message. - Form gets submitted, update the CRM. Most AI agents today could be replaced with a simple script, a clean workflow, or one person finally admitting the process was not that smart to begin with. Agents are useful when the next step is genuinely unclear. But when the steps are stable, predictable, and repeated every day? You do not need an agent. You need automation.

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  Andrew (@openmarmot) reported 32 minutes ago

  @AndrewCurran_ I use grok every day to research software changes/github issues/software doc research. It is very good at real time data search. Might be SOTA in this niche. Hardly a failure. Meanwhile LeCun only surfaces to let out more hot air. A very forgettable person.