Show HN: Dari-docs – Optimize your docs using parallel coding agents
6 by byhong03 | 1 comments on Hacker News.
It’s well known at this point that documentation needs to be optimized for AI agents - we’re all pointing our Claude Code / Codex / Pi agents at documentation, and expecting the models to figure out how to implement a product. This, however, changes the entire optimization problem when writing documentation. Good documentation now becomes more objective - you are solving the very concrete problem: can a dumb harness running the dumbest model implement this reliably? Humans can typically compensate for inconsistent terminology or scattered context across pages, but for agents, this often will waste time (or even just completely confuse the agent). We’ve been building a small project around this called dari-docs: users can upload their documentation via website or CLI and run agents across different providers to see where they falter. You can upload your documentation, feed a list of tasks, and ask agents with varying intelligence / cost levels to complete those tasks in parallel. When a run is complete, you get back a list feedback markdown files from each agent run and can apply changes based on agent feedback. Managed service: https://ift.tt/wZHKUYe , repo link: https://ift.tt/NKAgr1G The agents actually try to use the product end-to-end. They search through the docs, follow instructions, run commands, try examples, and attempt to debug failures. Importantly, this is not a static LLM review of the documentation. The agents are actually attempting the integration. You can also enable live verification with test credentials so the agents can actually verify workflows against real APIs: dari-docs check . --live-verify --secret-env DARI_TEST_API_KEY --task "Create a checkout session"
If you’re building a CLI, API, MCP server, or SDK and actively maintaining docs for humans or agents, we’d love to work with you and test this on real workflows!
Hack Nux
Watch the number of websites being hacked today, one by one on a page, increasing in real time.
New ask Hacker News story: Ask HN: Does root have to be uid 0? Does uid 0 have to be root?
Ask HN: Does root have to be uid 0? Does uid 0 have to be root?
3 by axismundi | 2 comments on Hacker News.
what's so special about root/0?
3 by axismundi | 2 comments on Hacker News.
what's so special about root/0?
New ask Hacker News story: Ask HN: How are agentic workflows meant to offset AI debt?
Ask HN: How are agentic workflows meant to offset AI debt?
2 by l33tbro | 0 comments on Hacker News.
I don't know quite how to put it. But projects I inherit and am supposed to get over the line have this same strange quality: they are 'undesigned'. I believe this may be because processes and context-related code that was previously considered with basic design principles and functionality seem not so much to be missing, but they have they seem to be simulated. Giving the impression of being considered, which is quite difficult for a project manager to catch. So I'm now spending a lot more time now going back and designing this 'undesigned' work. Rebuilding things manually that was abstracted past or missed entirley, which people at the project management level think "won't take you that long". Which I attribute to this insidious problem of things looking like they were designed. How is this meant to work when deployed at scale? When there is so much technical debt generated by AI, do the efficiency gains actually start to be losses? I'm not sure how agentic workflows can actually solve this. It seems as if you can have agents doing stuff, but they're still going to get a lot wrong and you'll need to drop someone in and rebuild.
2 by l33tbro | 0 comments on Hacker News.
I don't know quite how to put it. But projects I inherit and am supposed to get over the line have this same strange quality: they are 'undesigned'. I believe this may be because processes and context-related code that was previously considered with basic design principles and functionality seem not so much to be missing, but they have they seem to be simulated. Giving the impression of being considered, which is quite difficult for a project manager to catch. So I'm now spending a lot more time now going back and designing this 'undesigned' work. Rebuilding things manually that was abstracted past or missed entirley, which people at the project management level think "won't take you that long". Which I attribute to this insidious problem of things looking like they were designed. How is this meant to work when deployed at scale? When there is so much technical debt generated by AI, do the efficiency gains actually start to be losses? I'm not sure how agentic workflows can actually solve this. It seems as if you can have agents doing stuff, but they're still going to get a lot wrong and you'll need to drop someone in and rebuild.
New Show Hacker News story: Show HN: Number Gacha, a gacha game distilled to its essence
Show HN: Number Gacha, a gacha game distilled to its essence
3 by babel16 | 0 comments on Hacker News.
Number Gacha is a half-parody, half-real gacha game where you roll, unwrap, and battle numbers. Play on Desktop for the best experience!
3 by babel16 | 0 comments on Hacker News.
Number Gacha is a half-parody, half-real gacha game where you roll, unwrap, and battle numbers. Play on Desktop for the best experience!
New Show Hacker News story: Show HN: Better.ftp – cycling app for FTP tests without subscription
Show HN: Better.ftp – cycling app for FTP tests without subscription
2 by niecore | 0 comments on Hacker News.
I built a free iOS app so cyclists can stop paying $20/mo just to retest their FTP. The ramp test itself is a 25-minute Bluetooth interaction with a known protocol. It shouldn't require rent. This app is opensource, free, no ads, no tracking nor third party integrations because I just wanted to have a fun side project and have no interest in monetization. If you are a cyclist, I would kindly ask for feedback on the app especially on the ftp test protocol instructions, trainer-model compatibility, and bug reports App store link: https://ift.tt/1sh0d2G GitHub (opensource project): https://ift.tt/2xoiIm9 Demo gif: https://betterftp.cc/promo.gif
2 by niecore | 0 comments on Hacker News.
I built a free iOS app so cyclists can stop paying $20/mo just to retest their FTP. The ramp test itself is a 25-minute Bluetooth interaction with a known protocol. It shouldn't require rent. This app is opensource, free, no ads, no tracking nor third party integrations because I just wanted to have a fun side project and have no interest in monetization. If you are a cyclist, I would kindly ask for feedback on the app especially on the ftp test protocol instructions, trainer-model compatibility, and bug reports App store link: https://ift.tt/1sh0d2G GitHub (opensource project): https://ift.tt/2xoiIm9 Demo gif: https://betterftp.cc/promo.gif
New ask Hacker News story: Booking.com and Weaviate
Booking.com and Weaviate
2 by CShorten | 0 comments on Hacker News.
Vector search looks easy, until you hit production scale. I'm super excited to share a new episode of the Weaviate Podcast with Başak from @bookingcom on production-scale vector search, RAG, and agentic AI with @weaviate_io! The podcast begins by discussing Booking's tipping point into adopting vector search and emerging use cases. The scale of Partner-to-Guest messaging alone is insane! There are nearly 250,000 such exchanges daily , and Booking's Agent is already helping with 10s of thousands of these! Başak describes how the team navigated increasing scale and workload complexity. They ran an exhaustive evaluation of Weaviate with 100M embeddings and tests often left out of common ANN benchmarks. This includes Filtered Vector Search, Multi-Threaded Concurrency, and testing with simultaneous Reads and Writes. The podcast concludes with Başak's career journey to Booking and her thoughts on Travel Agents! YouTube: https://www.youtube.com/watch?v=O9edM9ZS_FQ Spotify: https://spotifycreators-web.app.link/e/8tc6Dyb7e3b
2 by CShorten | 0 comments on Hacker News.
Vector search looks easy, until you hit production scale. I'm super excited to share a new episode of the Weaviate Podcast with Başak from @bookingcom on production-scale vector search, RAG, and agentic AI with @weaviate_io! The podcast begins by discussing Booking's tipping point into adopting vector search and emerging use cases. The scale of Partner-to-Guest messaging alone is insane! There are nearly 250,000 such exchanges daily , and Booking's Agent is already helping with 10s of thousands of these! Başak describes how the team navigated increasing scale and workload complexity. They ran an exhaustive evaluation of Weaviate with 100M embeddings and tests often left out of common ANN benchmarks. This includes Filtered Vector Search, Multi-Threaded Concurrency, and testing with simultaneous Reads and Writes. The podcast concludes with Başak's career journey to Booking and her thoughts on Travel Agents! YouTube: https://www.youtube.com/watch?v=O9edM9ZS_FQ Spotify: https://spotifycreators-web.app.link/e/8tc6Dyb7e3b