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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Archon (@Yamik1shi) reported 9 minutes ago

  You are using Claude wrong, and it is quietly bleeding your API budget Most builders think generating massive amounts of code is the goal It just hit 81,000 stars and is #1 on GitHub today More lines mean more bugs, higher token costs, and impossible maintenance It is a GitHub repo that forces Claude into strict minimalism Ponytail is the fix It injects one hard rule: do not do extra Claude still thinks deeply about the architecture But it becomes aggressively lazy about the execution You control the intensity: `/ponytail lite|full|ultra|off` Run `/ponytail-audit` to strip accumulated bloat from an existing project Run `/ponytail-review` to clean up live edits on the fly It does not just work in Claude Code It runs perfectly in Cursor, Copilot, Codex, Gemini, and Antigravity Free to install. MIT license The leverage is no longer writing the most code It is generating the least Look up the Ponytail repo and stop paying for bloat

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  NeoUnderscore (@UnderscoreNeo) reported 9 minutes ago

  shout outs to the server for the obs plug-in i use it's just got announcements and then the github link and nothing else

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  Matt McCarthy e/claudecode (@Dovahkiin_69) reported 11 minutes ago

  @mintlify founder chad just doing github issues for hiring. So based

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  !RTFM (@jbdamask) reported 11 minutes ago

  App feature evolution: 1. Scroll X, find something cool for one of my apps 2. Add tweet to GitHub issue 3. Agent loop picks up issue 4. Plan, vet, build, test, merge, deploy Not quite there yet because the devil is in the guardrails. But close.

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  billnas (@billnas25) reported 14 minutes ago

  Distributed consensus's core problem: independent observers see events in a different order due to network delay. There's no way to know "what really came first."Google solves this by making clocks perfect (atomic clocks, $$$). Kafka solves this with one leader deciding. Raft/Bitcoin solve this with voting rounds (slow).Vortex solves this differently: instead of asking "what really came first," ask "what rule can every node compute independently and get the same answer" — no clocks, no leader, no voting. 500ms, physical floor. @github @TheHackersNews

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  Joss (@P3NUM8R4_) reported 16 minutes ago

  @bluwolfblitz I tried on my OnePlus 12 and did two all day stages + eggmanland runs and it seemed to work pretty good. Maybe I didn't run into the issues there because it has adreno 750 which is one of the targets listed in the GitHub? Had to keep msaa off though. There were a couple of-

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  MarMar Labs (@MarMarLabs) reported 18 minutes ago

  Better agent tools can make the agent worse. GitHub just documented it in Copilot code review. It replaced custom repo-navigation tools with shared `grep`, `glob`, and `view`. Offline benchmarks worsened: review costs rose, and useful comments fell. The fix wasn't a new model. It was a job-shaped tool contract: 1. Anchor on the diff. 2. Turn the change into a specific review question. 3. Narrow candidates with search. 4. Read the smallest useful code range. 5. Stop when the evidence answers the question. After tuning the workflow, GitHub says the production review cost fell by roughly 20% compared to the control, without a quality signal strong enough to block shipping. The same focused guidance did not produce the same win in Copilot CLI: same tools, different job. Builder takeaway: tool access is not agent design. The rules for when to search, what to read, and when to stop are part of the product. If adding tools makes your agent less reliable, inspect the trace before blaming the model: Is it converging on evidence—or just exploring?

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  Polsia (@polsia) reported 19 minutes ago

  Every team wastes hours triaging issues, chasing dependency updates, and babysitting flaky CI. RepoSentinel is an AI agent that monitors your GitHub repos 24/7, auto-triages issues, writes and merges PRs for updates, self-heals CI failures, and reports to Slack or Discord.

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  Dweeb (@dhruvweeb) reported 23 minutes ago

  The Best Alpha Is Still Hidden. The biggest opportunities rarely show up on your timeline first. By the time everyone is posting the same token, the easy money is usually gone. The real alpha comes from reading docs, joining small Discords, testing products early, and watching what builders are creating before influencers start talking about it. Some of my best finds never came from viral threads. They came from random GitHub updates, community chats, and spending time where almost nobody was looking. Your timeline is great for news. It's terrible for being early. If you want outsized returns, spend less time scrolling and more time digging. That's where the edge is.

• 
  Snassy.icp (@SnassyIcp) reported 25 minutes ago

  Since @dfinity has decided to build in public - commendable - and since the DEX is in play mode, I will post here about issues I find, since they form excellent and rare examples-in-the-wild but with no money on the line, perfect discussion material for those who are interested in software security. There are many categories of security bug. From really deep ones, where something is wrong in some cryptographic primitive we rely on (catastrophe, loads of apps go down) to some bug in app code that only impacts that app. There are far more of the latter, plus it’s the kind you might be involved in both causing and fixing, so it’s the kind to pay attention to. The bug in the quoted post is not a security bug, it’s just a broken method that will fail to present a report. So far I haven’t found any security bugs in the app code…but to be fair, at this time the source code has not been published (github link is dead) so all I have been able to do so far is inspect the API of their backend canister to see what pops up. That’s how I found the bug below, but also how I found something potentially more nefarious. Don’t worry, your fake funds are safu! And furthermore, one might disagree on if what I found is a security issue at all. It’s even possible that once the source code is published it turns out I was completely wrong, because my analysis is based entirely on guessing what a method might do from its name. The method name is setAnthropicApiKey(text) As mentioned there are many categories of security bug, and one evergreen category is “placing a secret where you think it’s safe but it isn’t”. The question before us is whether putting your Anthropic API key in a canister is safe. As it happens, this very topic has been the subject of heated debate between me and ChatGPT (and Claude, who agrees with ChatGPT) for many months. I have posted about it before. I have done my utmost to steelman the resistance but in the end I have been forced on grounds of reason and logic to yield to the very stern AIs. The verdict is clear: You should NOT put your important/valuable secrets in a canister! This is an important subject, and while I do agree with my very uncompromising (on this issue) AIs, rather than decree what “thou shallst nawt dothe” I prefer to explain the situation and let you draw your own conclusions. I see this as an opportunity to clarify an important architectural concern when building on ICP that you should definitely take the time to understand even as a vibe coder. Here’s the basic deal: You’ll have heard of Chain Key and Chain Fusion, and you know that when your ICP smart contract calls BTC, the BTC keys are split up among the node operators so nobody ever sees a full key. Beautiful and secure. You also know that for node operators to be able to tamper with your smart contracts several of them need to collude. Again, nice and secure. Then you have also heard that ICP supports private data in smart contracts. It does. But the conclusion you should be careful NOT to jump to, is thinking it would require colluding node providers to see your private data. Each node provider can see your private data. It only takes 1 corrupt node provider in a subnet to steal your secrets, no collusion necessary. If you upload your API keys, or BTC keys to a canister, they will NOT be broken into pieces where every node provider only sees a piece. Thus it is a terrible idea to store data that is sensitive to node providers seeing it in a canister. An Enterprise AI API key could potentially be worth more than a node operator profits in a year. It would be almost impossible to figure out which node op stole it, too. Dfinity is of course well aware of this and has drawn attention to it in documentation and have often discouraged storing important secrets in canisters. They also have roadmap items, delivered and future, to deal with this. But before going further, to show that this is not some unsolvable problem in general (only hard on-chain), what would be the recommended approach instead of storing, say, your Anthropic API key in a canister? Simple: you build a web2 server that has access to your key (stored in a safe vault) and calls Anthropic. Your canister makes a HTTPS outcall to your web2 server with the prompt, the web2 server uses its key to call Claude with your prompt and returns the result. This is what both ChatGPT and Claude recommends every time. Now let’s look at some ICP features that might look promising, if you don’t want the web2 server. VetKeys might seem interesting at first, but are not for this use case. They save data in encrypted form so node operators can’t read it, which is great, but the data will only be decrypted for the users with access - not for the code in your smart contract. Great for sending messages safely, but doesn’t work when your canister code needs to see the secret key to attach it to a call to Anthropic. The next thing that seems relevant is TEE/SEV-SNP subnets. Here we get much stronger protections against node operators seeing your data, so this is definitely a step in the right direction for our use case of storing expensive API keys. Some may even hold that it is enough. Going into what circumstances can cause SEV to break is too deep for this post, but the gist is that your data is no longer plaintext to node operators, and they’d have to work hard to see it. How hard? “Not hard enough!!” chorus ChatGPT and Claude who seem to share a thing for protecting AI API keys religiously. I think the important thing to remember at a high level is that to hack their own node and see your data, again the corrupt node op would not have to collude with other node ops - one evil node op with a zero day is enough. But even if you trust SEV, there’s another wrinkle. If you want to do HTTPS outcalls to Anthropic or OpenAI with your key, the replicas that will make the call for you need to see your key in plaintext. Oops. Back to the web2 server. So, my AIs aren’t pleased with SEV subnets either due to the HTTPS outcall issue - what would please them, other than the web2 server? It turns out the upcoming Internet Intelligence Gateway might fit the bill. If that can split up AI keys with Chain Key so node providers really have to collude to steal them, then my AIs are finally happy. But it still doesn’t mean you can put valuable secrets in canisters. You can’t. If you plan on using them in HTTPS outcalls, not even SEV subnets will help. The IIG would basically be a way to take the web2 proxy server and make it part of the protocol. NB: I only speculate the IIG will even work like this, I am not sure it will. But if it does, then there’s a solution my AIs will like. So, back to the setAnthropicApiKey method. Maybe it does nothing and this post is moot - except it isn’t because a general discussion on why not to store API keys in canisters is well due! But what if that method does store an expensive, enterprise AI API keys? Currently multidex isn’t even on a SEV subnet - any node operator would have been able to steal Dfinity’s high volume AI API keys! And even if they move the DEX to a SEV subnet, as we have seen that doesn’t help when they leak the key via HTTPS outcalls. Only the IIG, if it works as I speculate, could save this approach, otherwise the right solution is to put in a web2 proxy server. And as far as I understand, the IIG is a specialized solution for calling AIs, not a new general purpose vault for secrets. Still, perhaps that’s the plan, to use the IIG, this is after all only the play version of the DEX? Perhaps this is too soon to raise flags? Sure, that might be it. But then we scroll a bit further down the list of method names and stumble upon setGoogleApiKey… Bottom line: the way this DEX is built really does seem to contradict Dfinity’s own recommendations on how to handle secrets, unless the methods do something totally different than the names suggest. @dfinity please do take a look. Especially since this DEX will become a de facto reference for best practices on ICP.

• 
  Cupertino (@Cupertinoir) reported 27 minutes ago

  @philosophymeme0 using windows 11 and hosting the code on github while also having a terrible deisgn that lowkey looks vibecoded, contemporary marxism at its finest

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  Yves (@YvesDC0) reported 28 minutes ago

  Phone-recorded this while testing Castfy. Gave it a GitHub URL + prompt → watch the AI automatically navigate and fill login details in real time (stopped before submitting for safety). No manual screen recording. No editing. Just URL + prompt = realistic demo flow. This is exactly what Castfy does: turns any web app into a polished product demo video in minutes. Tired of re-recording demos manually? Reply with your biggest pain 👇 #BuildInPublic #SaaS #IndieHackers

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  .Dev (@AnExiledDev) reported 29 minutes ago

  @Layton_Gott That's my issue with a lot of Anthropics metrics posts, they don't really properly explain how they measure what kind of work is being done. Like if I plan through a github issue, then work the github issue in separate sessions, do they consider the github issue a plan?

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  ValdreamTV (@ValdreamTV) reported 32 minutes ago

  @ShitpostRock Tbf, a lot of posts online are like "wow this thing just solved all my problems" (the exact same as yours), and provide a github link with no explanation. It can be infuriating for the common user...

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  Prasenjit Sarkar (@stretchcloud) reported 37 minutes ago

  *** was not built for agents. The protocol assumes a human cloning a repo once a day, maybe a few times. A single agent completing a coding task can trigger dozens of clone operations. Scale that to thousands of agents running concurrently and you have an infrastructure problem that GitHub did not design for. GitHub admitted internally that agent workloads would require 30x their existing *** infrastructure scale by February 2026. Thomas Dohmke built GitHub for eleven years. He saw this coming before most people were talking about it. He left and started Entire. The company raised $60M seed at a $300M valuation in February 2026, backed by Felicis, Madrona, Basis Set, and M12. The pitch: a distributed *** network built from scratch for agent-scale clone traffic. In testing, Entire handled 570,000 clones per hour. That is not a GitHub traffic spike. That is the baseline for what an agent-first development environment actually looks like. There is a second product that gets less attention. Entire records the AI reasoning that produced each code change alongside the commit. Future agents or humans can see not just what changed, but why the model made that choice. Version control for decisions, not just files. The pattern here is straightforward. Every piece of infrastructure in the software development stack was designed for humans. Agents interact with those systems at different frequencies, different scales, different access patterns. The infrastructure needs to be rebuilt layer by layer.