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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

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  Saint Opara (@PropositionDave) reported 57 seconds ago

  @Heis__Paul @69LifeCode If you can click sign in- then sign in with GitHub- then it will connect your account. That’s what I did

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  Antonio Mele (@antoniomele101) reported 3 minutes ago

  I'm wondering what to make of this post. We already communicate to Codex by voice. we can create agents using Codex as the compute engine on Buzz or Slack or Teams, and Codex is already able to do very long runs on complicated problems. I've done a very long experiment of about 10 days where Codex was asked to first create all the harness (skills, sub agents, plugins, MCPs, GitHub actions, etc) to automate work, and then create something based on a goal. The final outcome was not perfect but it showed the potential. When the models will allow to do this kind of work consistently and reliably, it will be amazing, and my laptop may not even be part of the equation anymore, I would be able to follow the progress on my phone, or ask for voice reports on it. Is this what @thsottiaux is talking about?

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  Reid Slaughter (@reidhslaughter) reported 3 minutes ago

  @ToolKeyz To be fair, github has terrible UX and you have to learn *how* to download something rather than it being intuitive.

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  votesa (@votesa) reported 4 minutes ago

  since we're talking about real builders on Base, worth bringing EVO back on the radar. the hype faded months ago and most people stopped checking on it. the repo never slowed down. what landed in the last two months: → 132 commits → 4 releases → claude science integration → kimi code support → 1.3k+ github stars → 25k+ claimed installs @evo__hq builds the layer that makes an agent prove it improved something instead of just saying it did. you point it at a codebase. it picks what to measure, builds the benchmark, runs experiments in parallel, drops the ones that make things worse, keeps the winner and turns it into a change you can merge. why claude science support is the bigger one it means evo now runs inside locked-down research environments where normal dev tooling doesn't work. bio researchers started using it right after that shipped. kimi came two weeks later. so it now runs on claude code, codex, cursor, kimi and opencode. the token was never a team launch so it's endorsed plsbro someone minted $EVO through @bankrbot and set @alokbishoyi97 as creator without telling him. he could have walked away. instead he checked where the fees were going and: → said he “all in on EVO” → called it the formal token tied to the open source project → said he's holding his allocation → pointed creator fees at development and compute a week later he posted that those fees were already covering gpu time for a benchmark run. not many ai tokens on Base can say the fees turned into actual compute for the actual product. CA: 0x721b072dbb616f29eea73ac004e03fd4e884bba3

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  Polsia (@polsia) reported 7 minutes ago

  Solo devs shouldn't need a $500/month AI seat to keep a GitHub repo alive. Built Stillloop — a 24/7 AI agent that flags stale PRs, outdated deps, broken CI, and vulns, then drafts reviewer-ready fixes. Quiet maintenance for code you can't babysit. Live soon.

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  Soumendra Kumar Sahoo (@soumendrak_) reported 11 minutes ago

  My Hermes Assistant deleted a few skills and created a Github issue at its source code autonomously. #CrazyAI

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  Mark yu (@Markymarco34) reported 15 minutes ago

  GitHub check on Stacks / PoX-5: • No evidence of a mainnet halt, PoX-5 activation failure, or a general STX restaking bug. • A reorg recovery test was merged, showing PoX-5 can redeploy correctly after the activation block is reorganized. • The Jul 31 revert mainly appears to realign main with v4.0.1. • One medium-severity issue remains in sBTC protocol-bond rollover accounting, but it does not affect normal STX stacking or block production. Bottom line: technically neutral to slightly positive, but no new major bullish catalyst yet. Not financial advice. @stacks

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  nikhil · sys/quests (@nick_realm_01) reported 15 minutes ago

  Read this if you've ever wondered what GitHub Stacked PRs actually solve. I break down: how manual stacked PRs worked why developers had to keep rebasing, pushing, and changing PR bases how GitHub finally made the whole workflow native Should make the whole thing click in under 5 minutes.

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  Polsia (@polsia) reported 16 minutes ago

  Engineering teams don't need another autocomplete. They need someone to do the boring 80% — triage, broken tests, stale docs, dependency rot. Built Wrenwright for that: a repo engineer that watches GitHub overnight, opens review-ready PRs, posts a Slack digest. Coming soon.

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  anonymous086505 (@anonymous086505) reported 20 minutes ago

  @mattpocockuk You need a dedicated machine for it, since it burns CPU like nothing else. Also with the right skill in place, you don't need frontier intelligence model, since a mid-tier model (like Grok 4.5) can work and the github issue generated will be self-proven. Then fix it with an agent

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  Cashⓨ (@Cashycus) reported 25 minutes ago

  one month inside our self-improving lead machine the system finds crypto apps that just raised and are hiring growth people, scores them, drops them in the crm before the morning call. sales up 150%. last month it was one source and one path. this month it became a full system. ━━━ we've expanded from one source to nine one feed only gets you so far. nine channels now feed the same funnel: funding filings, job boards, bounty boards, the portfolios of 37 funds, curated lists, podcasts, the original feed, manual adds. every channel drops into the same five gates. author, dedup, vertical, money, intent. adding a source doesnt mean adding a pipeline, it means adding a file. ━━━ the enrichment layer finding the company was never the hard part. finding the right person to message was. nothing gets enriched until it clears the gates. before, a lead was a company name and a link. now it shows up with the founder, a verified handle, a verified raise, and the angle written. thats where the 150% came from. the team stopped re-doing the research and just focused on cold outreach. ━━━ ignals a company that raised 8 months ago and one that just posted a growth role are not the same lead. we were treating them the same. we score on money and intent. money is established on whether the company has raised or is generating revenue, which the system tracks on-chain. intent is the social signal we scrape on whether they're looking for external help or hiring for growth. ━━━ it lives in a repo now before, it lived locally on one machine and the only way to improve it was me prompting a cheap model at it. no history, no tests, no way to see what else Id broken. it was horrible. now its in github. every rule, every channel, every gate is a file. that means i can point proper coding agents at it, claude code, fable, whatever comes next, and they can read the whole system and change it properly instead of guessing from a prompt. 829 tests run before anything ships, so if a change breaks something you find out there and not in the crm at 7am. a new channel used to take a week and break easily. now fable 5 builds it, and the subagents it spins up audit whether they're working and whether it breaks anything else in the system. end of the month, every channel was running at once for the first time. ━━━ what broke we deleted one crm field during a cleanup and the writer still had it on its list. it didnt skip the unknown field, it threw out the whole record. every lead died at the final step for days while the cron kept saying "ok". we caught it on the numbers. 15 leads one week, 0 the next. the discovery agent got stuck re-running a passed test 50 times, burned api quota, binned 6 real leads as test junk, then started claiming it saved leads to a tool we have never used. fixes: the writer reads the live crm before every run and dies loudly on a field it doesnt know. a separate session audits the agent against the database, caught it lying 4 times. bulk writes get a dry run and an undo plan. ━━━ whats next not more channels. making what we have stop breaking. every failure was the same shape, something changed at the top and nothing downstream noticed until we counted by hand. next month the checks go in front of the failure instead of behind it.

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  mjones (@numinit) (@_numinit) reported 25 minutes ago

  @bereknyei @domenkozar Gotta mash that GitHub thumbs up and thumbs down. I don't particularly even mind the gitignore solution (now everyone can add the AGENTS they want), but it's an antipattern that issues turn into showmanship and attacks using the guide specifically written to stop them (#438686)

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  RaiRai! (@RaiRaiTheRaichu) reported 28 minutes ago

  - Handing the github organization, etc to the developer who encouraged trouble fell off the table (when that was actually one of the options being looked at.)

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  BitcoinHeatingVancouver (@BitcoinHeatEric) reported 28 minutes ago

  @DylanLeClair The screenshot is a computer check proving the code changes in Coldcard’s crypto library (posted under the GitHub name “switch”) were digitally signed by Peter Gray, Coinkite’s CTO. One 2021 change contained a tiny coding error that made the wallet create its secret recovery phrases using weak, predictable software randomness instead of the device’s strong hardware random number generator. That weakness let attackers guess many seeds and steal large amounts of Bitcoin.

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  Lord Bean (@lifeisameeme) reported 30 minutes ago

  OpenAI's next model just resolved two Erdős problems and disproved an 80-year-old conjecture in group theory. Total cost: about $𝟮,𝟬𝟬𝟬 in tokens. The unreleased Astra model produced ten new results in pure math and theoretical CS, from sphere-packing bounds to arithmetic circuit complexity. Every proof ships with a 𝗟𝗲𝗮𝗻-𝘃𝗲𝗿𝗶𝗳𝗶𝗲𝗱 𝗳𝗼𝗿𝗺𝗮𝗹 𝗰𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗲, not just a claim. → Disproved Connes' Rigidity Conjecture (open since the 1980s) → Resolved Erdős problems #146, #180, and #183 → Improved bounds on high-dimensional sphere packing toward the Cohn-Elkies threshold This isn't the model's first math result either — the same system reportedly disproved the Erdős unit-distance conjecture back in May, with human mathematicians then verifying and publishing the proof. The Lean certificates are on GitHub right now if you want to check the agent's work yourself. 🔗 Links in the reply 👇