The best Hacker News stories from Show from the past day
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Show HN: Yoink – Spotify to lossless with full metadata, self-hostable, ad-free
Show HN: I put an AI agent on a $7/month VPS with IRC as its transport layer
Show HN: DuckDB community extension for prefiltered HNSW using ACORN-1
Hey folks! As someone doing hybrid search daily and wishing I could have a pgvector-like experience but with actual prefiltered approximate nearest neighbours, I decided to just take a punt on implementing ACORN on a fork of the DuckDB VSS extension. I had to make some changes to (vendored) usearch that I'm thinking of submitting upstream. But this does the business. Approximate nearest neighbours with WHERE prefiltering.<p>Edit: Just to clarify, this has been accepted into the community extensions repo. So you can use it like:<p>```<p>INSTALL hnsw_acorn FROM community;<p>LOAD hnsw_acorn;<p>```
Show HN: Robust LLM extractor for websites in TypeScript
We've been building data pipelines that scrape websites and extract structured data for a while now. If you've done this, you know the drill: you write CSS selectors, the site changes its layout, everything breaks at 2am, and you spend your morning rewriting parsers.<p>LLMs seemed like the obvious fix — just throw the HTML at GPT and ask for JSON. Except in practice, it's more painful than that:<p>- Raw HTML is full of nav bars, footers, and tracking junk that eats your token budget. A typical product page is 80% noise.
- LLMs return malformed JSON more often than you'd expect, especially with nested arrays and complex schemas. One bad bracket and your pipeline crashes.
- Relative URLs, markdown-escaped links, tracking parameters — the "small" URL issues compound fast when you're processing thousands of pages.
- You end up writing the same boilerplate: HTML cleanup → markdown conversion → LLM call → JSON parsing → error recovery → schema validation. Over and over.<p>We got tired of rebuilding this stack for every project, so we extracted it into a library.<p>Lightfeed Extractor is a TypeScript library that handles the full pipeline from raw HTML to validated, structured data:<p>- Converts HTML to LLM-ready markdown with main content extraction (strips nav, headers, footers), optional image inclusion, and URL cleaning
- Works with any LangChain-compatible LLM (OpenAI, Gemini, Claude, Ollama, etc.)
- Uses Zod schemas for type-safe extraction with real validation
- Recovers partial data from malformed LLM output instead of failing entirely — if 19 out of 20 products parsed correctly, you get those 19
- Built-in browser automation via Playwright (local, serverless, or remote) with anti-bot patches
- Pairs with our browser agent (@lightfeed/browser-agent) for AI-driven page navigation before extraction<p>We use this ourselves in production at Lightfeed, and it's been solid enough that we decided to open-source it.<p>GitHub: <a href="https://github.com/lightfeed/extractor" rel="nofollow">https://github.com/lightfeed/extractor</a> npm: npm install @lightfeed/extractor Apache 2.0 licensed.<p>Happy to answer questions or hear feedback.
Show HN: Optio – Orchestrate AI coding agents in K8s to go from ticket to PR
I think like many of you, I've been jumping between many claude code/codex sessions at a time, managing multiple lines of work and worktrees in multiple repos. I wanted a way to easily manage multiple lines of work and reduce the amount of input I need to give, allowing the agents to remove me as a bottleneck from as much of the process as I can. So I built an orchestration tool for AI coding agents:<p>Optio is an open-source orchestration system that turns tickets into merged pull requests using AI coding agents. You point it at your repos, and it handles the full lifecycle:<p>- Intake — pull tasks from GitHub Issues, Linear, or create them manually<p>- Execution — spin up isolated K8s pods per repo, run Claude Code or Codex in git worktrees<p>- PR monitoring — watch CI checks, review status, and merge readiness every 30s<p>- Self-healing — auto-resume the agent on CI failures, merge conflicts, or reviewer change requests<p>- Completion — squash-merge the PR and close the linked issue<p>The key idea is the feedback loop. Optio doesn't just run an agent and walk away — when CI breaks, it feeds the failure back to the agent. When a reviewer requests changes, the comments become the agent's next prompt. It keeps going until the PR merges or you tell it to stop.<p>Built with Fastify, Next.js, BullMQ, and Drizzle on Postgres. Ships with a Helm chart for production deployment.
Show HN: Turbolite – a SQLite VFS serving sub-250ms cold JOIN queries from S3
I built a SQLite VFS in Rust that serves cold queries directly from S3 with sub-second performance, and often much faster.<p>It’s called turbolite. It is experimental, buggy, and may corrupt data. I would not trust it with anything important yet.<p>I wanted to explore whether object storage has gotten fast enough to support embedded databases over cloud storage. Filesystems reward tiny random reads and in-place mutation. S3 rewards fewer requests, bigger transfers, immutable objects, and aggressively parallel operations where bandwidth is often the real constraint. This was explicitly inspired by turbopuffer’s ground-up S3-native design. <a href="https://turbopuffer.com/blog/turbopuffer" rel="nofollow">https://turbopuffer.com/blog/turbopuffer</a><p>The use case I had in mind is lots of mostly-cold SQLite databases (database-per-tenant, database-per-session, or database-per-user architectures) where keeping a separate attached volume for inactive database feels wasteful. turbolite assumes a single write source and is aimed much more at “many databases with bursty cold reads” than “one hot database.”<p>Instead of doing naive page-at-a-time reads from a raw SQLite file, turbolite introspects SQLite B-trees, stores related pages together in compressed page groups, and keeps a manifest that is the source of truth for where every page lives. Cache misses use seekable zstd frames and S3 range GETs for search queries, so fetching one needed page does not require downloading an entire object.<p>At query time, turbolite can also pass storage operations from the query plan down to the VFS to frontrun downloads for indexes and large scans in the order they will be accessed.<p>You can tune how aggressively turbolite prefetches. For point queries and small joins, it can stay conservative and avoid prefetching whole tables. For scans, it can get much more aggressive.<p>It also groups pages by page type in S3. Interior B-tree pages are bundled separately and loaded eagerly. Index pages prefetch aggressively. Data pages are stored by table. The goal is to make cold point queries and joins decent, while making scans less awful than naive remote paging would.<p>On a 1M-row / 1.5GB benchmark on EC2 + S3 Express, I’m seeing results like sub-100ms cold point lookups, sub-200ms cold 5-join profile queries, and sub-600ms scans from an empty cache with a 1.5GB database. It’s somewhat slower on normal S3/Tigris.<p>Current limitations are pretty straightforward: it’s single-writer only, and it is still very much a systems experiment rather than production infrastructure.<p>I’d love feedback from people who’ve worked on SQLite-over-network, storage engines, VFSes, or object-storage-backed databases. I’m especially interested in whether the B-tree-aware grouping / manifest / seekable-range-GET direction feels like the right one to keep pushing.
Show HN: A plain-text cognitive architecture for Claude Code
Show HN: AI Roundtable – Let 200 models debate your question
Hey HN! After the Car Wash Test post got quite a big discussion going (400+ comments, <a href="https://news.ycombinator.com/item?id=47128138">https://news.ycombinator.com/item?id=47128138</a>), I spent the past few weeks building a tool so anyone can run these kinds of questions and get structured results. No signup and free to use.<p>You type a question, define answer options, pick up to 50 models at a time from a pool of 200+, and they all answer independently under identical conditions. No system prompt, structured output, same setup for every model.<p>You can also run a debate round where models see each other's reasoning and get a chance to change their minds. A reviewer model then summarizes the full transcript. All models are routed via my startup Opper. Any feedback is welcome!<p>Hope you enjoy it, and would love to hear what you think!
Show HN: Gridland: make terminal apps that also run in the browser
Hi everyone,<p>Gridland is a runtime + ShadCN UI registry that makes it possible to build terminal apps that run in the browser as well as the native terminal. This is useful for demoing TUIs so that users know what they're getting before they are invested enough to install them. And, tbh, it's also just super fun!<p>Gridland is the successor to Ink Web (ink-web.dev) which is the same concept, but using Ink + xterm.js. After building Ink Web, we continued experimenting and found that using OpenTUI and a canvas renderer performed better with less flickering and nearly instant load times.<p>We're excited to continue iterating on this. I expect a lot of criticism from the "why does this need to exist" angle, and tbh, it probably doesn't - it's really mostly just for fun, but we still think the demo use case mentioned previously has potential.<p>- Chris + Jess
Show HN: ProofShot – Give AI coding agents eyes to verify the UI they build
I use AI agents to build UI features daily. The thing that kept annoying me: the agent writes code but never sees what it actually looks like in the browser. It can’t tell if the layout is broken or if the console is throwing errors.<p>So I built a CLI that lets the agent open a browser, interact with the page, record what happens, and collect any errors. Then it bundles everything — video, screenshots, logs — into a self-contained HTML file I can review in seconds.<p><pre><code> proofshot start --run "npm run dev" --port 3000
# agent navigates, clicks, takes screenshots
proofshot stop
</code></pre>
It works with whatever agent you use (Claude Code, Cursor, Codex, etc.) — it’s just shell commands. It's packaged as a skill so your AI coding agent knows exactly how it works. It's built on agent-browser from Vercel Labs which is far better and faster than Playwright MCP.<p>It’s not a testing framework. The agent doesn’t decide pass/fail. It just gives me the evidence so I don’t have to open the browser myself every time.<p>Open source and completely free.<p>Website: <a href="https://proofshot.argil.io/" rel="nofollow">https://proofshot.argil.io/</a>
Show HN: ProofShot – Give AI coding agents eyes to verify the UI they build
I use AI agents to build UI features daily. The thing that kept annoying me: the agent writes code but never sees what it actually looks like in the browser. It can’t tell if the layout is broken or if the console is throwing errors.<p>So I built a CLI that lets the agent open a browser, interact with the page, record what happens, and collect any errors. Then it bundles everything — video, screenshots, logs — into a self-contained HTML file I can review in seconds.<p><pre><code> proofshot start --run "npm run dev" --port 3000
# agent navigates, clicks, takes screenshots
proofshot stop
</code></pre>
It works with whatever agent you use (Claude Code, Cursor, Codex, etc.) — it’s just shell commands. It's packaged as a skill so your AI coding agent knows exactly how it works. It's built on agent-browser from Vercel Labs which is far better and faster than Playwright MCP.<p>It’s not a testing framework. The agent doesn’t decide pass/fail. It just gives me the evidence so I don’t have to open the browser myself every time.<p>Open source and completely free.<p>Website: <a href="https://proofshot.argil.io/" rel="nofollow">https://proofshot.argil.io/</a>
Show HN: I took back Video.js after 16 years and we rewrote it to be 88% smaller
What do you do when private equity buys your old company and fires the maintainers of the popular open source project you started over a decade ago? You reboot it, and bring along some new friends to do it.<p>Video.js is used by billions of people every month, on sites like Amazon.com, Linkedin, and Dropbox, and yet it wasn’t in great shape. A skeleton crew of maintainers were doing their best with a dated architecture, but it needed more. So Sam from Plyr, Rahim from Vidstack, and Wes and Christain from Media Chrome jumped in to help me rebuild it better, faster, and smaller.<p>It’s in beta now. Please give it a try and tell us what breaks.
Show HN: I took back Video.js after 16 years and we rewrote it to be 88% smaller
What do you do when private equity buys your old company and fires the maintainers of the popular open source project you started over a decade ago? You reboot it, and bring along some new friends to do it.<p>Video.js is used by billions of people every month, on sites like Amazon.com, Linkedin, and Dropbox, and yet it wasn’t in great shape. A skeleton crew of maintainers were doing their best with a dated architecture, but it needed more. So Sam from Plyr, Rahim from Vidstack, and Wes and Christain from Media Chrome jumped in to help me rebuild it better, faster, and smaller.<p>It’s in beta now. Please give it a try and tell us what breaks.
Show HN: Email.md – Markdown to responsive, email-safe HTML
Show HN: Gemini can now natively embed video, so I built sub-second video search
Gemini Embedding 2 can project raw video directly into a 768-dimensional vector space alongside text. No transcription, no frame captioning, no intermediate text. A query like "green car cutting me off" is directly comparable to a 30-second video clip at the vector level.<p>I used this to build a CLI that indexes hours of footage into ChromaDB, then searches it with natural language and auto-trims the matching clip. Demo video on the GitHub README.
Indexing costs ~$2.50/hr of footage. Still-frame detection skips idle chunks, so security camera / sentry mode footage is much cheaper.
Show HN: Time Keep – Location timezones, timers, alarms, countdowns in one place
I kept running into this: timer on my laptop, alarm on my phone, timezone / discord timestamp conversion app in a separate tab. Switching between them was a hassle and I wanted to be able to set them up and manage really fast anywhere I was.<p>So I built Time Keep, it puts world clocks, timers, alarms, countdowns, a stopwatch, breaks, a sleep planner, Discord timestamps, and more into one always open place.<p>Works without an account or signup. All tools are fully functional immediately. Sign in to save your data across sessions. Pro adds live cross-device sync.<p>Shared countdown links show the correct time in every viewer's timezone. Built with Next.js, Supabase, Clerk, and Vercel.<p><a href="https://www.timekeep.cc" rel="nofollow">https://www.timekeep.cc</a>
Show HN: Littlebird – Screenreading is the missing link in AI
Show HN: Agent Kernel – Three Markdown files that make any AI agent stateful
Show HN: The King Wen Permutation: [52, 10, 2]
I analyzed two orderings of the 64 I Ching hexagrams and found
the permutation cycle decomposition between them is [52, 10, 2]
with zero fixed points. Nobody has done this kind of analysis before
and this cycle type has not been reported in the literature.
You can verify it yourself.
Show HN: The King Wen Permutation: [52, 10, 2]
I analyzed two orderings of the 64 I Ching hexagrams and found
the permutation cycle decomposition between them is [52, 10, 2]
with zero fixed points. Nobody has done this kind of analysis before
and this cycle type has not been reported in the literature.
You can verify it yourself.