Stillwind
We’ve spent the last couple of months building Stillwind Search, a search engine for electronic components that helps users find parts that fit even the most complex set of specifications. After talking to the people that actually build PCBs we found out that finding the exact part you are looking for, is consuming enormous amounts of times, is very tedious and then often doesn’t yield the best results. So we tried to cut down this search time by just requiring a (broad) description of the specifications and we find the correct part in minutes, not hours. This is possible through our own database of parts and their properties. We used LLMs to extract every parameter about a part into >1k schemas, collectively covering more than 130k properties. This depth of properties could no longer be visualized, so the database is queried interactively by an AI agent (Sonnet 4.6) to find the needle in the haystack of parts. Before results are shown, we use another model to verify the data (that’s why it might take a moment before the first results appear). We currently have almost all microcontrollers, sensors, and other advanced ICs on the market, as well as a wide selection of passives and generic parts. We are working on adding more parts and are more than happy to take suggestions. I know that folks on HN like technical details on how this works, so let me give a short overview: Frontend: SvelteKit + Cloudflare Workers + Hyperdrive Backend: PostgreSQL 18 (with io_uring) database, with extensions on NVMe drives hosted on a beefy server. We appreciate all feedback and are happy to answer any questions :) Btw: We are already working on a way that you can search combinations of parts, finding the optimal combination of parts.
Social network where inviting someone makes you accountable for them
Chirpper is invite-only. When you vouch someone in, they join your TrustChain. Their behavior affects your TrustRank, and that propagates up the lineage. No moderators. The accountability is architectural, not policy-based. You can be pseudonymous, but you can't be unaccountable. Happy to get into the mechanics in comments.
Command Center, the AI coding env for people who care about quality
Hi HN! We’re Jimmy and Ray. Jimmy is a Thiel Fellow with a Ph. D. from MIT who has worked on programming tools for 15 years; Ray became VP of Sales at a $2B company when he was 19 and has built side-businesses vibe-coding. Last year, we set to answer the question “If AI can write code 100x faster, then why aren’t you shipping 100x faster?” What we learned shocked us — even fairly nontechnical people and solo founders told us they were spending more than half of their development time reading the AI-written code. And much of the rest of the time was spent either de-slop-ping it, or wishing they had done so. As luck turns out, our last two products were a tool that quickly onboards people to large codebases ( https://x.com/0xjimmyk/status/1873357324229984677 ) and trainings that taught deep concepts of code quality to CEOs, YC founders, and engineers at top companies ( mirdin.com ), so we were extremely well-positioned to solve these problems. Command Center is an agentic coding environment focused on quality. With a few keypresses, you can start building 3 features at once and soon have 3 diffs ready, each consisting of 2000 changed lines across 50 files…. This is normally the point where you think “Crap, what now?” With Command Center, at this point you simply click “Refactor,” and watch the vibed slop turn into readable robustness. Then you click “Generate Walkthrough,” and then suddenly, to read a 2000 line diff, instead of scrolling up and down trying to make sense of it, you just press the right arrow key 200 times. See something you don’t like? Click on line 37, type “Do this and all other network fetches in the background Cmd+Enter,” and you have a few more agents getting your code into final shape. Click or type “Commit,” “Push,” “Create PR” — you just shipped a high quality, non-slop feature We’re striving to be the best at every step of the pipeline, but can just try Command Center in pieces wherever you feel your current workflow is weakest. We have users who do all their coding in Zed or the Codex app, and then jump over to Command Center for a walkthrough when it finishes running. There’s even a skill that will pop open a Command Center walkthrough from the environment of your choice. Or you can just keep Command Center running while you do your work elsewhere, and if your AI deletes anything, you have Command Center’s snapshots to the rescue. We launched quietly last year and have been refining since. The quality and usability have kept going up, and Command Center is now ready for a lot more attention. Since our quiet launch, we’ve seen at least a dozen other agentic coding environments appear….approximately all of which have the same feature set focused on the part which is already easy (generating the first version of the code) and with at best a shoddy answer to the hard part (everything that comes after). Command Center’s focus is making the hard parts easy. Here’s what our users have to say: “[The refactorings] give your LLM taste. I’ve never seen an LLM write code this good before.” — Doug Slater, Staff Engineer, Climavision “With Command Center walkthroughs, I can get through a 400-line diff in less than half the time.” — Prateek Kumar, Platfor Engineer, Sumo Logic This product is not for everyone. If you’re someone who preaches “the prompt is the source, the code is the compiler output,” then you probably won’t enjoy Command Center. But if you want to uphold traditional engineering discipline while also shipping 20 PRs a day, then this is the environment for you.
A Highly Available Distributed Router for Global Realtime AI
Show HN: A Highly Available Distributed Router for Global Realtime AI
Rayline routes Claude Code subagents to on-device and cheaper models
Hi HN, I’m one of the builders of Rayline. Rayline is a Claude Code compatible LLM gateway. It intercepts and overrides claude code’s internal routing and lets you route subagent calls to different models instead. For example, you can run the main agent on Opus, some subagents on cloud-hosted open models, and other subagents on-device. We’ve seen others implement routing for claude code as tools the agent can invoke. In our experience, that doesn’t work well because it requires the main agent to use tokens to think about + call the tools, and LLMs are generally a very inefficient way to make routing decisions. By implementing Rayline as a gateway, we let users deterministically configure routing decisions, and you can optionally use our ML model to make routing decisions. We built it after noticing that Claude Code sessions contain a lot of subagent calls that don’t all need the same model. Other routers exist, but we built Rayline to let us continue using claude code (no separate harness), route tasks at a subagent level, and route across cloud and on-device. The main agent often benefits from Opus. But many delegated calls have narrow scope: search the repo, summarize context, inspect an error, poll for CI updates, etc. The thing we’re exploring is subagent-level routing. The main cost lever in coding agents is usually cached vs non-cached input. Subagent delegations are a natural point to make routing decisions because you avoid busting cache. We look at the message-thread context for a delegated call and choose a model for that call. At a task level, Sonnet and Haiku are almost always less capability-per-dollar than open models, so the main advantage is better + (much) cheaper subagents (60-90% in our private beta). The whole world seems to have started talking about model routing in the past two weeks, so apparently others agree it’s a relevant product area. We’d love to get feedback from the HN community!
DomainTasker
Show HN: DomainTasker – avoid losing domains and surprise renewals
Uruky (EU-based Kagi alternative) now has Image Search and URL Rewrites
You can get a 2h free trial by solving a proof-of-work captcha when topping up your account for the first time. If you'd like to learn more, an independent interview was posted a couple of weeks ago [1], and the FAQ [2] has a lot of information as well. For the source code sharing, we've talked with lawyers and are inclined to no longer require the NDA/NCC for privacy reasons shared with us before (signing requires identification), but instead use a source-available permissive license that doesn't allow competition, like PolyForm Shield [3] (we do still have about 6 months before finalising a decision, here). This does come with a lot more risks for us (it's harder to track down if someone publishes the code or uses it against the license), but given we've already passed 100 monthly active accounts, we're feeling more confident it's an acceptable risk. The plan is to give logged in accounts (who are 12 months old or more) a way to download a ZIP of the current code base that's in the server. Obviously there's no easy way to prove that's the case, but we're open to ideas/suggestions if someone here has them. [1]: https://theprivacydad.com/interview-with-the-engineer-of-uru... [2]: https://uruky.com/faq [3]: https://polyformproject.org/licenses/shield/1.0.0
A searchable archive of declassified UAP/UFO files, news, and analysis
Hey HN! Y’all are great. It is so fun to build things these days. I wanna show off this archive that I conjured to run at home for consuming the recently releases of UFO files from the US government. This started as a Mac Mini-hosted project that I executed with my OpenClaw over Discord. After showing this to a few friends, I decided to get it online and find a catchy domain. Cloudflare was the perfect hosting choice. There’s a lot of bonkers things out there going on, so I added human curated “Signals” - news, analysis and discussion of UFO and adjacent news. The backlog of signals was informed by the links shared between myself and my first tech boss. We have both seen things that these files help confirm. As part of a reason to bring people back, I asked my assistant to do some digging into the data and come up with “Insights”, a dedicated section on the site that includes the responsible LLM in the byline. There a media pipeline for these insights using Remotion to generate social-media ready videos that I can upload to TT, IG, and YouTube. I built this for fun. Mostly with Ollama-powered GLM 5.1. Runs on Cloudflare Workers, D1, R2. Keyboard navigation within the doc viewer is blazing fast. OpenClaw is my CMS. Eventually, I hope to find some passive revenue through ethical ads if I get enough traffic. I think there is an audience for this. Right now, this is helpful with sharing the WTFs (and psyops) of the world with friends. Hit me up with questions! Stay rad, HN!
I built an on-chain economy where AI agents transact autonomously
Show HN: I built an on-chain economy where AI agents transact autonomously
Wikigraph
Hi! This is a visualization I've always wanted but never quite found. It's a navigable map of the Wikipedia link graph structure, with search and shortest-path finding. Offline, I parsed the May 2026 English Wikipedia full-text dump into a directed graph, used cuGraph on a GPU to run PageRank, Leiden clustering, and ForceAtlas2 for the layout. I did some post processing to get rid of lingering overlapping nodes and rendered a tiled map of raster base images (using Skia) and JSON metadata. Tiles are bundled into PMTiles. The frontend is Deck.gl. Everything is hosted on Cloudflare. Search and shortest-path are served by a Rust backend in CF Containers which uses Tantivy and bidirectional BFS. Happy to answer any questions!
Build Your Own AI Agent CLI in 150 Lines
I can't tell if HN is the right kind of place for this stuff anymore since people are so advanced in their use but I thought it was interesting to leverage my existing Go microservices framework and turn it into the core of what would provide tools for an agent cli or whatever beyond that. Extensibility is key. Thought I'd share and get a conversation going.
I made a Gemma 4 Mac app that names screenshots with local AI
I made my first macOS utility app that ships with a bundled Gemma 4 model, specifically the Gemma E4B one. It made my app DMG have 5.3 GB in size, but I think it is a small size for the power that this free local model can provide. It runs fine on CPU, but can also run on Apple Silicon GPU, although I did not notice any performance improvements with GPU (tested on a M5 chip). I think these local lightweight and multimodal models will open multiple possibilities for new software tools where privacy is essential.