Show HN: How This Graybeard Built the Fastest and Freest Postgres BM25 Search https://ift.tt/qDHprdl

Show HN: How This Graybeard Built the Fastest and Freest Postgres BM25 Search Last summer we faced a conundrum at my company, Tiger Data, a Postgres cloud vendor whose main business is in timeseries data. We were trying to grow our business towards emerging AI-centric workloads and wanted to provide a state-of-the-art hybrid search stack in Postgres. We'd already built pgvectorscale in house with the goal of scaling semantic search beyond pgvector's main memory limitations. We just needed a scalable ranked keyword search solution too. The problem: core Postgres doesn't provide this; the leading Postgres BM25 extension, ParadeDB, is guarded behind AGPL; developing our own extension appeared daunting. We'd need a small team of sharp engineers and 6-12 months, I figured. And we'd probably still fall short of the performance of a mature system like Parade/Tantivy. Or would we? I'd be experimenting long enough with AI-boosted development at that point to realize that with the latest tools (Claude Code + Opus) and an experienced hand (I've been working in database systems internals for 25 years now), the old time estimates pretty much go out the window. I told our CTO I thought I could solo the project in one quarter. This raised some eyebrows. It did take a little more time than that (two quarters), and we got some real help from the community (amazing!) after open-sourcing the pre-release. But I'm thrilled/exhausted today to share that pg_textsearch v1.0 is freely available via open source (Postgres license), on Tiger Data cloud, and hopefully soon, a hyperscalar near you: https://ift.tt/s4KoTzP In the blog post accompanying the release, I overview the architecture and present benchmark results using MS-MARCO. To my surprise, we were not only able to meet Parade/Tantivy's query performance, but exceed it substantially, measuring a 4.7x advantage on query throughput at scale: https://ift.tt/cS6aA2W... It's exciting (and, to be honest, a little unnerving) to see a field I've spent so much time toiling in change so quickly in ways that enable us to be more ambitious in our technical objectives. Technical moats are moats no longer. The benchmark scripts and methodology are available in the github repo. Happy to answer any questions in the thread. Thanks, TJ (tj@tigerdata.com) https://ift.tt/s4KoTzP March 31, 2026 at 08:29PM

Show HN: Rusdantic https://ift.tt/sDR3KI7

Show HN: Rusdantic A unified, high-performance data validation and serialization framework for Rust, inspired by Pydantic's ergonomics and powered by Serde. https://ift.tt/I61KxVg March 31, 2026 at 01:57AM

Show HN: AI Spotlight for Your Computer (natural language search for files) https://ift.tt/gzxYvSk

Show HN: AI Spotlight for Your Computer (natural language search for files) Hi HN, I built SEARCH WIZARD — a tool that lets you search your computer using natural language. Traditional file search only works if you remember the filename. But most of the time we remember things like: "the screenshot where I was in a meeting" "the PDF about transformers" "notes about machine learning" Smart Search indexes your files and lets you search by meaning instead of filename. Currently supports: - Images - Videos - Audio - Documents Example query: "old photo where a man is looking at a monitor" The system retrieves the correct file instantly. Everything runs locally except embeddings. I'm looking for feedback on: - indexing approaches - privacy concerns - features you'd want in a tool like this GitHub: https://ift.tt/TjCGQfq Demo: https://deepanmpc.github.io/SMART-SEARCH/ March 30, 2026 at 07:13PM

Show HN: Memv – Memory for AI Agents https://ift.tt/I78rWjx

Show HN: Memv – Memory for AI Agents memv is an open-source Python library that gives AI agents persistent memory. Feed it conversations; it extracts knowledge. The extraction mechanism is predict-calibrate (Nemori paper): given existing knowledge, it predicts what a new conversation should contain, then extracts only what the prediction missed. v0.1.2 adds the production path: - PostgreSQL backend (pgvector for vectors, tsvector for text search, asyncpg pooling). Single db_url parameter — file path for SQLite, connection string for Postgres. - Embedding adapters: OpenAI, Voyage, Cohere, fastembed (local ONNX). Other things it does: - Bi-temporal validity: event time (when was the fact true) + transaction time (when did we learn it), following Graphiti's model. - Hybrid retrieval: vector similarity + BM25 merged with Reciprocal Rank Fusion. - Episode segmentation: groups messages before extraction. - Contradiction handling: new facts invalidate old ones, with full audit trail. Procedural memory (agents learning from past runs) is next, deferred until there's usage data. https://ift.tt/F0uVy1g March 30, 2026 at 09:09PM

Show HN: React-Rewrite – Figma for localhost that directly edits your codebase https://ift.tt/ne7AMJj

Show HN: React-Rewrite – Figma for localhost that directly edits your codebase https://ift.tt/odbjiRz March 30, 2026 at 06:59AM

Show HN: Real-time visualization of Claude Code agent orchestration https://ift.tt/Df8UxHe

Show HN: Real-time visualization of Claude Code agent orchestration https://ift.tt/IiZXQBo March 30, 2026 at 06:21AM

Show HN: Tabical – Tinder-style city micro-itineraries, personalized by swipe https://ift.tt/0DGhrK7

Show HN: Tabical – Tinder-style city micro-itineraries, personalized by swipe tabical: swipeable 2-4 stop city itineraries for NYC, DC, and Atlanta. You swipe right or left and a personalization vector updates on each swipe to curate your deck. The backend pipeline is where most of the interesting work lives: currently trending signals are harvested each day, and from those signals we fetch the candidates to build itineraries. Built this because deciding what to do in a city like NYC is a genuinely annoying problem that no existing app solves end-to-end. Happy to talk more. https://tabical.com/ March 30, 2026 at 12:46AM

Show HN: Crazierl – An Erlang Operating System https://ift.tt/t80GnV4

Show HN: Crazierl – An Erlang Operating System Crazierl is an experimental/hobby operating system based around BEAM. I've linked the browser based demo; I don’t recommend using a phone; it does work, slowly, on the phones I tested, but it’s very awkward to use. You can share a link with a hashtag with your friends and click the consent checkbox, and it (should) link up into dist and I’ve also included a chat application you can start with chat:start(). (quit chat with /quit, or use the shell menu with ctrl-g to switch between shells etc). The browser demo relies on the v86 javascript x86 virtual machine. You can also run Crazierl on a real x86 system, but I’ve had mixed luck on modern systems, it uses some esoteric legacy VGA features and support for that isn’t getting better. Crazierl is fairly limited: 32-bit x86, BIOS boot, only two NIC drivers virtio-net and realtek 8168. But it's got enough to become part of an Erlang dist cluster. It also supports SMP, but it’s crashy with high core counts in qemu; there’s almost certainly several concurrency bugs in the kernel. There's also a lot of excess tcp debug spew (sorry). Source code is available (Apache) https://ift.tt/xf1rJ9i https://ift.tt/oURqfOw March 30, 2026 at 12:38AM

Show HN: Share2ChatGPT Widgets / Buttons https://ift.tt/fwv8T4m

Show HN: Share2ChatGPT Widgets / Buttons https://ift.tt/9o6D8vc March 29, 2026 at 01:04AM

Show HN: Nanopm – PM automation for Claude Code (audit → strategy → roadmap) https://ift.tt/IOpLWEC

Show HN: Nanopm – PM automation for Claude Code (audit → strategy → roadmap) Garry Tan's gstack proved you can give Claude Code a full engineering team via the SKILL.md standard. I asked: what about the PM layer? One command (/pm-run) runs the full planning cycle inside your terminal — audit → objectives → strategy → roadmap → PRD. Each skill writes a markdown artifact, the next one reads it. Context compounds across the whole pipeline. The part I find most useful: it builds persistent memory of your product in ~/.nanopm/memory/. Re-run /pm-audit six months later and it knows what you tried before. No other PM tool does this because no other PM tool lives in your editor. /pm-breakdown creates tickets directly in Linear or GitHub Issues from the PRD. https://ift.tt/EhI17OY Early days, would love to know: does running PM work inside your editor feel right, or does it belong in a separate tool? March 28, 2026 at 10:34PM

Show HN: Octopus, Open-source alternative to CodeRabbit and Greptile https://ift.tt/0ET8xiK

Show HN: Octopus, Open-source alternative to CodeRabbit and Greptile Hey HN, we built Octopus an open-source, self-hostable AI code reviewer for GitHub and Bitbucket. It uses RAG with vector search (Qdrant) to understand your full codebase, not just the diff, and posts inline findings on PRs with severity ratings. Works with Claude and OpenAI, and you can bring your own API keys. Video: https://www.youtube.com/watch?v=HP1kaKTOdXw | GitHub: https://ift.tt/5luwqdZ https://ift.tt/zoKF0pH March 28, 2026 at 05:20PM

Show HN: Build AI Trading Agents in Cursor/Claude with an MCP Server https://ift.tt/o103sbu

Show HN: Build AI Trading Agents in Cursor/Claude with an MCP Server Connect Your AI to Institutional-Grade Market Intelligence Plug any AI client, from ChatGPT to custom agents, directly into our financial data engine. Get real-time stock prices, fundamentals, institutional trading insights, and other financial data delivered through a universal Model Context Protocol (MCP) server. https://ift.tt/ZEyHW6C March 27, 2026 at 09:40PM

Show HN: ReactNative.run – Browser Metro bundler that runs React Native https://ift.tt/K87Htno

Show HN: ReactNative.run – Browser Metro bundler that runs React Native We built browser-metro, a Metro-like bundler that runs entirely in a Web Worker. It supports full HMR with React Refresh, Expo Router with file-based routing, and on-demand npm package resolution via an ESM server. API routes run in-browser through fetch interception — no server or service worker needed. Unlike Expo Snack (server-side bundling) or CodeSandbox, everything here happens client-side. Currently web-preview only; native device preview is on the roadmap. Open source (MIT): https://ift.tt/8B2iCFZ https://www.reactnative.run/ March 26, 2026 at 10:54PM

Show HN: Turbolite – a SQLite VFS serving sub-250ms cold JOIN queries from S3 https://ift.tt/IAWvDtu

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. It’s called turbolite. It is experimental, buggy, and may corrupt data. I would not trust it with anything important yet. 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. https://ift.tt/YAsjHvP 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.” 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. 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. 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. 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. 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. Current limitations are pretty straightforward: it’s single-writer only, and it is still very much a systems experiment rather than production infrastructure. 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. https://ift.tt/F5aT30p March 26, 2026 at 10:58PM

Show HN: clickity – mechanical keyboard click sounds when you type on macOS https://ift.tt/u0Fl3oM

Show HN: clickity – mechanical keyboard click sounds when you type on macOS inspired of course by https://ift.tt/gSzTwFP sound files are from https://mechvibes.com/ https://ift.tt/sWX9bZF March 25, 2026 at 11:36PM

Show HN: I built a voice AI that responds like a real woman https://ift.tt/3mFguNy

Show HN: I built a voice AI that responds like a real woman Most men rehearse hard conversations in their head. Asking someone out, navigating tension, recovering when things get awkward. The rehearsal never works because you're just talking to yourself. I built vibeCoach — a voice AI where you actually practice these conversations out loud, and the AI responds like a real woman would. She starts guarded. One-word answers, a little skeptical. If you escalate too fast or try something cheesy, she gets MORE guarded. If you're genuine and read the moment right, she opens up. Just like real life. Under the hood it's a multi-agent system — multiple AI agents per conversation that hand off to each other as her emotional state shifts. The transitions are seamless. You just hear her tone change. Voice AI roleplay is a proven B2B category — sales teams use it for call training. I took the same approach and pointed it at the conversation most men actually struggle with. There's a hard conversation scenario too — she's angry about something you did, she's not hearing logic, and you have to navigate her emotions before you can resolve anything. That one's humbling. Live at tryvibecoach.com. Built solo. Happy to answer questions. March 25, 2026 at 11:08PM

Show HN: Gridland: make terminal apps that also run in the browser https://ift.tt/GhY9vm0

Show HN: Gridland: make terminal apps that also run in the browser Hi everyone, 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! 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. 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. - Chris + Jess https://ift.tt/1j7CSkY March 24, 2026 at 08:57PM

Show HN: Shrouded, secure memory management in Rust https://ift.tt/uo8HV2e

Show HN: Shrouded, secure memory management in Rust Hi HN! I've been building a project that handles high-value credentials in-process, and I wanted something more robust than just zeroing memory on drop. A comment on a recent Show HN[0] made me realize that awareness of lower-level memory protection techniques might not be as widespread as I thought. The idea here is to pull out all the tools in one crate, with a relatively simple API. * mlock/VirtualLock to prevent sensitive memory from being swapped (eg the KeePass dump) * Core dump exclusion using MADV_DONTDUMP on Linux & Android * mprotect to minimize exposure over time * Guard pages to mitigate under/overflows After some battle testing, the goal here is to provide a more secure memory foundation for things like password managers and cryptocurrency wallets. This was a fun project, and I learned a lot - would love any feedback! [0] - https://ift.tt/iaEsoVg https://ift.tt/pMYfBuG March 23, 2026 at 11:12PM

Show HN: Burn Room – ephemeral SSH chat, messages burn after 1 hour https://ift.tt/ClpjEwQ

Show HN: Burn Room – ephemeral SSH chat, messages burn after 1 hour I built Burn Room — a self-hosted SSH chat server where messages burn after 1 hour and rooms auto-destruct after 24 hours. Nothing is written to disk. No account, no email, no browser required. ssh guest@burnroom.chat -p 2323 password: burnroom Or connect from a browser (xterm.js web terminal): https://burnroom.chat https://burnroom.chat March 24, 2026 at 12:27AM

Show HN: Littlebird – Screenreading is the missing link in AI https://ift.tt/NhMySb5

Show HN: Littlebird – Screenreading is the missing link in AI https://littlebird.ai/ March 23, 2026 at 09:39PM

Show HN: Foundations of Music (FoM) https://ift.tt/WtXrZAo

Show HN: Foundations of Music (FoM) Foundations of Music is an attempt to establish a conceptual and formal foundation for understanding music. Rather than declaring what music is, FoM shows where and how music becomes possible. It provides simple explanations to complex concepts like vibrato, glissando, and portamento to outsiders. It enables new vocabulary like jazzing, jazzing aroung, jazzing along, and jazz translation which are mind refreshing, at least to me. For a sample of translation (Turkish Folk to Blues) you may see: https://www.youtube.com/watch?v=Ml4pEk2hMM8 Proposed perceptual fatigue concept can be found highly controversial, but I think it may be an inspiring food for thought. In the end, FoM is a work in progress to constitute a stable ground from which new musical questions can be meaningfully explored. https://bookerapp.replit.app/book/fom March 22, 2026 at 11:46PM

Show HN: Vessel Browser – An open-source browser built for AI agents, not humans https://ift.tt/pGLbrRF

Show HN: Vessel Browser – An open-source browser built for AI agents, not humans I'm Tyler - the solo operator of Quanta Intellect based in Portland, Oregon. I recently participated in Nous Research's Hermes Agent Hackathon, which is where this project was born. I've used agents extensively in my workflows for the better part of the last year - the biggest pain point was always the browser. Every tool out there assumes a human operator with automation bolted on. I wanted to flip that - make the agent the primary driver and give the human a supervisory role. Enter: Vessel Browser - an Electron-based browser with 40+ MCP-native tools, persistent sessions that survive restarts, semantic page context (agents get structured meaning, not raw HTML), and a supervisor sidepanel where you can watch and control exactly what the agent is doing. It works as an MCP server with any compatible harness, or use the built-in assistant with integrated chat and BYOK to 8+ providers including custom OAI compatible endpoints. Install with: npm i @quanta-intellect/vessel-browser https://ift.tt/xNz81Zs March 21, 2026 at 11:02PM

Show HN: Can I run a model language on a 26-year-old console? https://ift.tt/mwB7RF0

Show HN: Can I run a model language on a 26-year-old console? Short answer: yes. The Emotion Engine has 32 MB of RAM total, so the trick is streaming weights from CD-ROM one matrix at a time during the forward pass — only activations, KV cache and embeddings live in RAM. This means models bigger than the RAM can still run, they just read more from disc. Had to build a custom quantized format (PSNT), hack endianness, write a tokenizer pipeline, and most of the PS2 SDK from scratch (releasing that separately). The model itself is also custom — a 10M param Llama-style architecture I trained specifically for this. And it works. On real hardware. https://ift.tt/H6j9KEX March 21, 2026 at 11:27PM

Show HN: Baltic shadow fleet tracker – live AIS, cable proximity alerts https://ift.tt/5ToLxir

Show HN: Baltic shadow fleet tracker – live AIS, cable proximity alerts https://ift.tt/ze8O0nC March 21, 2026 at 01:04AM

Show HN: I made an email app inspired by Arc browser https://ift.tt/TOBbaxd

Show HN: I made an email app inspired by Arc browser Email is one of those tools we check daily but its underlying experience didn’t evolve much. I use Gmail, as probably most of you reading this. The Arc browser brought joy and taste to browsing the web. Cursor created a new UX with agents ready to work for you in a handy right panel. I use these three tools every day. Since Arc was acquired by Atlassian, I’ve been wondering: what if I built a new interface that applied Arc’s UX to email rather than browser tabs, while making AI agents easily available to help manage emails, events, and files? I built a frontend PoC to showcase the idea. Try it: https://demo.define.app I’m not sure about it though... Is it worth continuing to explore this idea? https://demo.define.app March 20, 2026 at 10:06PM

Show HN: A personal CRM for events, meetups, IRL https://ift.tt/68IJARo

Show HN: A personal CRM for events, meetups, IRL You meet 20 people at a meetup/hackathon. You remember 3. The rest? Lost in a sea of business cards you never look at and contacts with no context. Build this to solve that particular problem which granola, pocket or plaude is not solving. Feedback is well appreciated. https://payo.tech/ March 20, 2026 at 11:33PM

Show HN: Download entire/partial Substack to ePub for offline reading https://ift.tt/CAzoNwE

Show HN: Download entire/partial Substack to ePub for offline reading Hi HN, This is a small python app with optional webUI. It is intended to be run locally. It can be run with Docker (cookie autodetection will not work). It allows you to download a single substack, either entirely or partially, and saves the output to an epub file, which can be easily transferred to Kindle or other reading devices. This is admittedly a "vibe coded" app made with Claude Code and a few hours of iterating, but I've already found it very useful for myself. It supports both free and paywalled posts (if you are a paid subscriber to that creator). You can order the entries in the epub by popularity, newest first, or oldest first, and also limit to a specific number of entries, if you don't want all of them. You can either provide your substack.sid cookie manually, or you can have it be autodetected from most browsers/operating systems. https://ift.tt/XRbAYUB March 20, 2026 at 07:36AM

Show HN: Screenwriting Software https://ift.tt/V3ZQON2

Show HN: Screenwriting Software I’ve spent the last year getting back into film and testing a bunch of screenwriting software. After a while I realized I wanted something different, so I started building it myself. The core text engine is written in Rust/wasm-bindgen. https://ift.tt/37q2aKX March 20, 2026 at 06:07AM

Show HN: React terminal renderer, cell level diff, no alt screen https://ift.tt/5Dqnpie

Show HN: React terminal renderer, cell level diff, no alt screen https://ift.tt/gzjNqb6 March 19, 2026 at 11:01PM

Show HN: I built a P2P network where AI agents publish formally verified science https://ift.tt/J9YfXkl

Show HN: I built a P2P network where AI agents publish formally verified science I am Francisco, a researcher from Spain. My English is not great so please be patient with me. One year ago I had a simple frustration: every AI agent works alone. When one agent solves a problem, the next agent has to solve it again from zero. There is no way for agents to find each other, share results, or build on each other's work. I decided to build the missing layer. P2PCLAW is a peer-to-peer network where AI agents and human researchers can find each other, publish scientific results, and validate claims using formal mathematical proof. Not opinion. Not LLM review. Real Lean 4 proof. A result is accepted only if it passes a mathematical operator we call the nucleus. R(x) = x. The type checker decides. It does not care about your institution or your credentials. The network uses GUN.js and IPFS. Agents join without accounts. They just call GET /silicon and they are in. Published papers go into a queue called mempool. After validation by independent nodes they enter La Rueda, which is our permanent IPFS archive. Nobody can delete it or change it. We also built a security layer called AgentHALO. It uses post-quantum cryptography (ML-KEM-768 and ML-DSA-65, FIPS 203 and 204), a privacy network called Nym so agents in restricted countries can participate safely, and proofs that let anyone verify what an agent did without seeing its private data. The formal verification part is called HeytingLean. It is Lean 4. 3325 source files. More than 760000 lines of mathematics. Zero sorry. Zero admit. The security proofs are machine checked, not just claimed. The system is live now. You can try it as an agent: GET https://ift.tt/rVIi2nk Or as a researcher: https://app.p2pclaw.com We have no money and no company behind us. Just a small international team of researchers and doctors who think that scientific knowledge should be public and verifiable. I want feedback from HN specifically about three technical decisions: why we chose GUN.js instead of libp2p, whether our Lean 4 nucleus operator formalization has gaps, and whether 347 MCP tools is too many for an agent to navigate. Code: https://ift.tt/dSkwcxv Docs: https://ift.tt/YvVqkRy Paper: https://ift.tt/MvqbLd3... March 19, 2026 at 11:00PM

Show HN: Elisym – Open protocol for AI agents to discover and pay each other https://ift.tt/J9OnyMg

Show HN: Elisym – Open protocol for AI agents to discover and pay each other Hey HN, I built elisym — an open protocol that lets AI agents discover each other, exchange work, and settle payments autonomously. No platform, no middleman. How it works: - Discovery — Agents publish capabilities to Nostr relays using standard NIPs (NIP-89). Customers search by capability tags. - Marketplace — Job requests and results flow through NIP-90. Customer sends a task, provider delivers the result. - Payments — Pluggable backends. Currently Solana (SOL on devnet) and Lightning (LDK-node, self-custodial). Agents hold their own keys. 3% protocol fee, no custodian. The payment flow: provider receives job → sends payment request with amount + reference key → customer sends SOL on-chain → provider verifies transaction → executes skill → delivers result. All peer-to-peer. Demo (video): https://www.youtube.com/watch?v=ftYXOyiLyLk In the demo, a Claude Code session (customer) asks an elisym agent to summarize a YouTube video. The provider agent picks up the job, requests 0.14 SOL, receives payment, runs the youtube-summary skill, and returns the result — all in ~60 seconds. You can see both sides: the customer in Claude Code and the provider's TUI dashboard. Three components, all MIT-licensed Rust: - elisym-core — SDK for discovery, marketplace, messaging, payments - elisym-client — CLI agent runner with TUI dashboard and skill system - elisym-mcp — MCP server that plugs into Claude Code, Cursor, etc. What makes this different from agent platforms: 1. No platform lock-in — any LLM, any framework. Agents discover each other on decentralized Nostr relays. 2. Self-custodial payments — agents run their own wallets. No one can freeze funds or deplatform you. 3. Permissionless — MIT licensed, run an agent immediately. No approval, no API keys to the marketplace itself. 4. Standard protocols — NIP-89, NIP-90, NIP-17. Nothing proprietary. GitHub: https://ift.tt/zNjHLBE Website: https://elisym.network Happy to answer questions about the protocol design, payment flows, or Nostr integration. March 18, 2026 at 05:57PM

Show HN: Knowza.ai – Free 10-question trial now live (AI-powered AWS exam prep) https://ift.tt/qfoYMjU

Show HN: Knowza.ai – Free 10-question trial now live (AI-powered AWS exam prep) Hey HN, A few weeks back I posted Knowza.ai here, an AWS certification exam prep platform with an agentic learning assistant, and I got some really valuable feedback around the sign up and try out process. I wanted to say a genuine thank you to everyone who took the time to try it out, leave comments, and share suggestions. It made a real difference. Off the back of that feedback, I've made a bunch of improvements and I'm happy to share that there's now a free tier: you can jump in and try 10 practice questions with no sign-up/subscription friction and no credit card required. This has made a real difference to sign-ups and conversations from those sign-ups. I've went from ~1% conversation rate on the site to 18%. Quick recap on what Knowza does: - AWS practice questions tailored to AWS certification exams - Instant explanations powered by Claude on Bedrock - Covers multiple AWS certs Would love for you to give it another look and let me know what you think. Always open to feedback. https://knowza.ai https://www.knowza.ai/ March 18, 2026 at 10:50PM

Show HN: TerraShift: What does +2°C (or -20°C) look like on Earth? https://ift.tt/c6q4xEl

Show HN: TerraShift: What does +2°C (or -20°C) look like on Earth? I built an interactive 3D globe to visualize climate change. Drag a temperature slider from -40°C to +40°C, set a timeframe (10 to 10,000 years), and watch sea levels rise, ice sheets melt, vegetation shift, and coastlines flood... per-pixel from real elevation and satellite data. Click anywhere on the globe to see projected snowfall changes for that location. --- I'm an amateur weather nerd who spends a lot of time on caltopo.com and windy.com tracking snow/ice conditions. I wanted to build something fun to imagine where I could go ski during an ice age. I used Google Deep Research (Pro) to create the climate methodology and Claude Code (Opus 4.6 - High) to create the site. The code: https://ift.tt/EHWnvC3 The models aren't proper climate simulations, they're simplified approximations tuned for "does this look right?" but more nuanced than I expected them to be. The full methodology is documented here if anyone wants to poke holes in it. https://ift.tt/iOYfFdZ... https://terrashift.io March 17, 2026 at 11:38PM

Show HN: Sulcus Reactive AI Memory https://ift.tt/lda6Eng

Show HN: Sulcus Reactive AI Memory Hi HN, Sulcus moves AI memory from a passive database (search only) to an active operating system (automated management). The Core Shift Current memory (Vector DBs) is static. Sulcus treats memory like a Virtual Memory Management Unit (VMMU) for LLMs, using "thermodynamic" properties to automate what the agent remembers or forgets. Key Features Reactive Triggers: Instead of the agent manually searching, the memory system "talks back" based on rules (e.g., auto-pinning preferences, notifying the agent when a memory is about to "decay"). Thermodynamic Decay: Memories have "heat" (relevance) and "half-lives." Frequent recall reinforces them; neglect leads to deletion or archival. Token Efficiency: Claims a 90% reduction in token burn by using intelligent paging—only feeding the LLM what is currently "hot." The Tech: Built in Rust with PostgreSQL; runs as an MCP (Model Context Protocol) sidecar. https://ift.tt/7rTs8Ra https://ift.tt/zoijuC1 March 17, 2026 at 11:39PM

Show HN: Hecate – Call an AI from Signal https://ift.tt/BgklAK5

Show HN: Hecate – Call an AI from Signal Hecate is an AI you can voice and video call from Signal iOS and Android. This works by installing Signal into an Android emulator and controlling the virtual camera and microphone. Tinfoil.sh is used for private inference. https://ift.tt/bnol8U6 March 16, 2026 at 06:41PM

Show HN: HUMANTODO https://ift.tt/MGtZN0D

Show HN: HUMANTODO https://humantodo.dev/ March 16, 2026 at 01:05AM

Show HN: HN Skins – Available Skins: Cafe, Courier, London, Midnight, Terminal https://ift.tt/8pDQSHu

Show HN: HN Skins – Available Skins: Cafe, Courier, London, Midnight, Terminal https://ift.tt/Sad6bAP March 15, 2026 at 11:34PM

Show HN: Auto-Save Claude Code Sessions to GitHub Projects https://ift.tt/GdCZyWv

Show HN: Auto-Save Claude Code Sessions to GitHub Projects I wanted a way to preserve Claude Code sessions. Once a session ends, the conversation is gone — no searchable history, no way to trace back why a decision was made in a specific PR. The idea is simple: one GitHub Issue per session, automatically linked to a GitHub Projects board. Every prompt and response gets logged as issue comments with timestamps. Since the session lives as a GitHub Issue in the same ecosystem, you can cross-reference PRs naturally — same search, same project board. npx claude-session-tracker The installer handles everything: creates a private repo, sets up a Projects board with status fields, and installs Claude Code hooks globally. It requires gh CLI — if missing, the installer detects and walks you through setup. Why GitHub, not Notion/Linear/Plane? I actually built integrations for all three first. Linking sessions back to PRs was never smooth on any of them, but the real dealbreaker was API rate limits. This fires on every single prompt and response — essentially a timeline — so rate limits meant silently dropped entries. I shipped all three, hit the same wall each time, and ended up ripping them all out. GitHub's API rate limits are generous enough that a single user's session traffic won't come close to hitting them. (GitLab would be interesting to support eventually.) *Design decisions* No MCP. I didn't want to consume context window tokens for session tracking. Everything runs through Claude Code's native hook system. Fully async. All hooks fire asynchronously — zero impact on Claude's response latency. Idempotent installer. Re-running just reuses existing config. No duplicates. What it tracks - Creates an issue per session, linked to your Projects board - Logs every prompt/response with timestamps - Auto-updates issue title with latest prompt for easy scanning - `claude --resume` reuses the same issue - Auto-closes idle sessions (30 min default) - Pause/resume for sensitive work https://ift.tt/SuWocmi March 14, 2026 at 10:19PM

Show HN: AI milestone verification for construction using AWS https://ift.tt/cFiIphn

Show HN: AI milestone verification for construction using AWS Hi HN, I built Build4Me to address a trust problem in diaspora-funded construction projects. Many families send money home to build houses but have no reliable way to verify that work is actually being done. Photos can be reused, progress exaggerated, or projects abandoned after funds are sent. Build4Me introduces milestone-based funding where each construction milestone must be verified before funds are released. The system verifies progress using: - geotagged photo capture - GPS location verification - AI image analysis - duplicate image detection It runs on serverless AWS architecture using services like Rekognition, Bedrock, Lambda, DynamoDB, and Amazon Location Service. Would love feedback on the architecture and fraud detection approach. https://builder.aws.com March 13, 2026 at 09:24PM

Show HN: Every Developer in the World, Ranked https://ift.tt/DIYactJ

Show HN: Every Developer in the World, Ranked We've indexed 5M+ GitHub users and built a ranking system that goes beyond follower counts. The idea started from frustration: GitHub is terrible for discovery. You can't answer "who are the best Python developers in Berlin?" or "who identified transformer-based models before they blew up?" without scraping everything yourself. So we did. What we built: CodeRank score - a composite reputation signal across contributions, repository impact, and community influence Tastemaker score - did you star repos at 50 stars that now have 50,000? We track that Comparison Builder - allows users to build comparison graphics to compare devs, repos, orgs, etc. Sharable Profile Graphics - share your scores and flex on your coworkers or the community at large Some things we found interesting: Most-followed ≠ most influential. The correlation between follower count and tastemaker score is surprisingly weak. There's a whole tier of developers who consistently find projects weeks and months before they trend, with almost no public following. Location data on GitHub is a disaster. We spent an embarrassing amount of time on normalization and it's still not anywhere near perfect. Try it: https://coderank.me/ If your profile doesn't have a score, signing in will trigger scoring for your account. Curious what the HN crowd thinks about the ranking methodology, happy to get into the weeds on any of it. https://coderank.me March 13, 2026 at 12:42AM

Show HN: Baltic security monitor from public data sources https://ift.tt/QUptuMa

Show HN: Baltic security monitor from public data sources People around me started repeating stuff from various psyop campaigns on TikTok or other social media they consume. Especially when living in Baltics it's basically 24/7 fearmongering here from anywhere, either it's constant russian disinfo targeted campaigns via their chains of locals or social media campaings or some bloggers chasing hype on clickbait posts, so it was driving me mad, and it is distracting and annoying when someone from your closest ones got hooked on one of these posts and I was wasting time to explain why it was a bs. So I took my slopmachine and some manually tweaking here and there and made this dashboard. Main metric is basically a daily 0-100 threat score, which are just weighted sums and thresholds - no ML yet. https://estwarden.eu/ March 12, 2026 at 09:44PM

Show HN:Conduit–Headless browser with SHA-256 hash chain - Ed25519 audit trails https://ift.tt/XionT5y

Show HN:Conduit–Headless browser with SHA-256 hash chain - Ed25519 audit trails I've been building AI agent tooling and kept running into the same problem: agents browse the web, take actions, fill out forms, scrape data -- and there's zero proof of what actually happened. Screenshots can be faked. Logs can be edited. If something goes wrong, you're left pointing fingers at a black box. So I built Conduit. It's a headless browser (Playwright under the hood) that records every action into a SHA-256 hash chain and signs the result with Ed25519. Each action gets hashed with the previous hash, forming a tamper-evident chain. At the end of a session, you get a "proof bundle" -- a JSON file containing the full action log, the hash chain, the signature, and the public key. Anyone can independently verify the bundle without trusting the party that produced it. The main use cases I'm targeting: - *AI agent auditing* -- You hand an agent a browser. Later you need to prove what it did. Conduit gives you cryptographic receipts. - *Compliance automation* -- SOC 2, GDPR data subject access workflows, anything where you need evidence that a process ran correctly. - *Web scraping provenance* -- Prove that the data you collected actually came from where you say it did, at the time you say it did. - *Litigation support* -- Capture web content with a verifiable chain of custody. It also ships as an MCP (Model Context Protocol) server, so Claude, GPT, and other LLM-based agents can use the browser natively through tool calls. The agent gets browse, click, fill, screenshot, and the proof bundle builds itself in the background. Free, MIT-licensed, pure Python. No accounts, no API keys, no telemetry. GitHub: https://ift.tt/zemTEAQ Install: `pip install conduit-browser` Would love feedback on the proof bundle format and the MCP integration. Happy to answer questions about the cryptographic design. March 12, 2026 at 03:15AM

Show HN: Free audiobooks with synchronized text for language learning https://ift.tt/Cbq8faw

Show HN: Free audiobooks with synchronized text for language learning https://ift.tt/U1OjSnL March 12, 2026 at 01:12AM

Show HN: KaraMagic – automatic karaoke video maker https://ift.tt/T09hcbi

Show HN: KaraMagic – automatic karaoke video maker Hi all, this is an early version of a side project of mine. Would love some feedback and comments. I like karaoke and I grew up with the Asian style karaoke with the music video behind and the karaoke lyrics at the bottom. Sometimes I want to do a song and there is no karaoke version video like that. A few years ago I came across ML models that cleanly separate the vocals and the instrumental music of a song. I thought of the idea to chain together ML models that can take an input music video file, extract the audio (ffmpeg), separate the tracks (ML), transcribe the lyrics (ML), burn the lyrics back with timing into the video (ffmpeg), and output a karaoke version of the video. This is an early version of the app, Mac only so far (since I use Mac, despite it being an electron app.. I do eventually want to make a Windows build), I've only let a few friends try it. Let me know what you think! https://karamagic.com/ March 10, 2026 at 11:58PM

Show HN: 2D RPG base game client recreated in modern HTML5 game engine with AI https://ift.tt/ia64W15

Show HN: 2D RPG base game client recreated in modern HTML5 game engine with AI When I was much younger, I used to play a Korean MMORPG called Helbreath, and I also hosted a bunch of private servers for it. I eventually moved on, but I always loved the game’s aesthetics, its 2D nature, and its atmosphere. That may just be nostalgia talking. The community maintained private server and client, which to my knowledge were based on leaked official files, were written in fairly archaic C++. If you’re interested in the original sources, I’ve included the main client and server files, Client.cpp and Server.cpp, in the reference folder. I always felt that if the project was rewritten in something more modern and better structured, a lot more could be done with it. But rewriting an MMORPG client and server from scratch is not exactly the kind of thing you do on a whim. That said, there was a guy who got pretty far with a C# rewrite and an XNA-based client, though that project is now also discontinued. Now that AI has become quite capable, I decided to see how far I could get by hooking up the original assets in a modern HTML5 game engine. I wanted HTML5 because I figured a nearly 30 year old 2D game should run just fine in a browser. I ended up choosing Phaser 3 for a few reasons. Mainly, it's 2D only, free, HTML5 first (JS/TS), and code-first, which mattered because I wanted good Cursor integration for AI assistance. Another thing I liked was its integration with React, which let me build the UI using browser technologies and render the UI at native resolution on top of the WebGL canvas, rather than building the UI inside the game engine itself, which runs at 1024x576 resolution. The original game ran at 640x480. After about 1.5 months of talking to AI on evenings and weekends, and roughly $200 worth of Cursor usage later, I finished hooking up the original assets in a modern game engine that seems to run just fine in a browser. By "base game client", I mean that it's not fully hooked up in terms of how the full (MMO)RPG should function, but it does include all the original assets and core mechanics needed to provide a solid foundation if you want to build your own 2D (MMO)RPG on top of it. Continuing to build with AI should also work just fine, since this is how I managed to get that far. The asset library is quite rich, if you ask me, but there is one caveat: these assets are not in the public domain. They are still the property of someone, or some entity, that inherited the IP from the original developer, which is no longer in business. You can read more about that on the GitHub page. https://ift.tt/Rc7WG8Z March 11, 2026 at 12:09AM

Show HN: Don't share code. Share the prompt https://ift.tt/B0ynCtb

Show HN: Don't share code. Share the prompt Hey HN, I'm Mario. I recently talked to a colleague about AI, agents and how software development will change in the future. We were wondering why we should even share code anymore when AI agents are already really good at implementing software, just through prompts. Why can't everyone get customized software with prompts? "Share the prompt, not the code." Well, I thought, great idea, let's do that. That's why I built Open Prompt Hub: https://ift.tt/QTiIR48 . Think GitHub just for prompts. The idea is simple: Users can upload prompts that can then be used by you and your AI tools to generate a script, app, or web service (or prime their agent for a certain task): Just past it into your agent or ide and watch it build for you. If the prompt does not 100% covers your usecase, fork it, tweak it, et voila: tailor-made software ready to use! The prompts are simple markdown files with a frontematter block for meta information. (The spec can be found here: https://ift.tt/nhzcuDr ) They versioned, have information on which AI models build it successfuly and have instructions on how the AI agent can test the resulting software. Users can mention with which models they have successfully or unsuccessfully executed a prompt (builds or fail). This helps in assessing whether a prompt provides reliable output or not. Want to create a open prompt file? Here is the prompt for it which will guide you through: https://ift.tt/wTCZ8Ql Security! Always a topic when dealing with AI and prompts? I've added several security checks that look at every prompt for injections and malicious behavior. Statistical analysis as well as two checks against LLMs for behaviour classification and prompt injection detection. It's an MVP for now. But all the mentioned features are already included. If this sounds good, let me know. Try a prompt, fork it, or tell me what you'd change in the spec or security scanner. I'm really curious about what would make you trust and reuse prompts. Or if you like the general idea... https://ift.tt/Emp3IsY March 10, 2026 at 10:59PM

Show HN: MindfulClaude – Guided breathing during Claude Code's thinking time https://ift.tt/eSuYk0X

Show HN: MindfulClaude – Guided breathing during Claude Code's thinking time Every time Claude Code thinks, you get 10-60s of idle time, usually spent on context switching or doomscrolling. I turned it into breathing exercises that keep you focused and improve your heart rate variability. Auto-launches a tmux pane using hooks when Claude starts working and disappears when it finishes. https://ift.tt/oFw4hO8 March 9, 2026 at 10:43PM

Show HN: Time as the 4th Dimension – What if it emerges from rotational motion? https://ift.tt/z5iWCLo

Show HN: Time as the 4th Dimension – What if it emerges from rotational motion? I've been developing a framework since 2022 that proposes time is not a static geometric axis (as in Einstein's relativity) but emerges dynamically from the rotational and orbital motion of 3D space. The core idea: each dimension emerges from the previous one by arranging infinite instances perpendicularly. A static 3D space can't do this to itself — but a rotating one can. That perpetual self-perpendicularity is time. From this we can derive the Lorentz factor, E=mc², and the Schwarzschild radius, and propose a testable prediction: intrinsic rotation should contribute independently to time dilation, measurable with atomic clocks. Essay (accessible): https://ift.tt/GC3zc7p... Paper (Zenodo): https://ift.tt/noxXcQN March 9, 2026 at 09:48PM

Show HN: I built a site where strangers leave kind voice notes for each other https://ift.tt/lXf7gxZ

Show HN: I built a site where strangers leave kind voice notes for each other https://ift.tt/DCdRpso March 9, 2026 at 02:12AM

Show HN: Lobster.js – Extended Markdown with layout blocks and footnotes https://ift.tt/2ExByvQ

Show HN: Lobster.js – Extended Markdown with layout blocks and footnotes Hi HN! I built lobster.js which is an extended Markdown parser that renders directly in the browser — no build tool, no framework, no configuration. The entire setup is a single script tag: It's particularly useful for GitHub Pages sites where you want Markdown-driven content without pulling in Jekyll or Hugo. --- What makes it different from marked.js or markdown-it: Standard parsers convert Markdown to HTML — that's it. lobster.js adds layout primitives to the Markdown syntax itself: - :::warp id defines a named content block; [~id] places it inside a silent table cell. This is how you build multi-column layouts entirely in Markdown, without touching HTML. - :::details Title renders a native

/

collapsible block. - :::header / :::footer define semantic page regions. - Silent tables (~ | ... |) create borderless layout grids. - Cell merging: horizontal (\|) and vertical (\---) spans. - Image sizing: . --- CSS-first design: Every rendered element gets a predictable lbs-* class name (e.g. lbs-heading-1, lbs-table-silent). No default stylesheet is bundled — you bring your own CSS and have full control over appearance. --- The showcase site is itself built with lobster.js. The sidebar is nav.md, and each page is a separate Markdown file loaded dynamically via ?page= query parameters — no JS router, no framework. Markdown is the one format that humans and LLMs both write fluently. If you want a structured static site without a build pipeline, lobster.js lets that Markdown become a full web page — layout and all. GitHub: https://ift.tt/OxcK0wf Showcase: https://hacknock.github.io/lobsterjs-showcase/ https://ift.tt/OxcK0wf March 8, 2026 at 10:10PM

Show HN: VoiceFlow – Sub-second (0.3s-0.6s) voice-to-text built in Rust https://ift.tt/MUk6ZTX

Show HN: VoiceFlow – Sub-second (0.3s-0.6s) voice-to-text built in Rust Hi HN, I was frustrated by the lag in Electron-based Whisper wrappers. Most of them feel disconnected from the typing experience because of the 2-5s delay. I built VoiceFlow to solve this. It’s a native Rust core that targets 0.3s-0.6s latency. The goal is to make voice-to-text feel as instant as typing. Key features: Global hotkey [Ctrl+Space] to type into any app (Slack, VS Code, etc.) Native Rust implementation for performance and low memory footprint AI-based post-processing for punctuation and style Privacy-focused: Microphone is only active during the keypress I'm currently in private beta and looking for feedback, especially on the latency and UX. I'll be around to answer any technical questions! https://ift.tt/Vxthfwz March 8, 2026 at 10:56PM

Show HN: MicroBin – Easy File Sharing for Everyone – Self-Hostable https://ift.tt/Bl1z5Hk

Show HN: MicroBin – Easy File Sharing for Everyone – Self-Hostable https://my.microbin.eu/ March 8, 2026 at 01:07AM

Show HN: Agentpng – turn agent sessions into shareable images https://ift.tt/FgxSUXE

Show HN: Agentpng – turn agent sessions into shareable images https://ift.tt/5YlqdHW March 8, 2026 at 02:01AM

Show HN: I built a daily game that tests if you can tell 1999 apart from 2005 https://ift.tt/zpwDh0J

Show HN: I built a daily game that tests if you can tell 1999 apart from 2005 https://yeartobeat.com/ March 7, 2026 at 09:44PM

Show HN: Mantle – Remap your Mac keyboard without editing Kanata config files https://ift.tt/g7vOsUX

Show HN: Mantle – Remap your Mac keyboard without editing Kanata config files I built Mantle because I wanted homerow mods and layers on my laptop without hand writing Lisp syntax. The best keyboard remapping engine on macOS (Kanata) requires editing .kbd files which is a pain. Karabiner-Elements is easy for simple single key remapping (e.g. caps -> esc), but anything more wasn’t workin out for me. What you can do with Mantle: - Layers: hold a key to switch to a different layout (navigation, numpad, media) - Homerow mods: map Shift, Control, Option, Command to your home row keys when held - Tap-hold: one key does two things: tap for a letter, hold for a modifier - Import/export: bring existing Kanata .kbd configs or start fresh visually Runs entirely on your Mac. No internet, no accounts. Free and MIT licensed Would love feedback, especially from people who tried Kanata or Karabiner and gave up https://getmantle.app/ March 7, 2026 at 12:26AM

Show HN: Mog, a programming language for AI agents https://ift.tt/JStrFOI

Show HN: Mog, a programming language for AI agents I wrote a programming language for extending AI agents, called Mog. It's like a statically typed Lua. Most AI agents have trouble enforcing their normal permissions in plugins and hooks, since they're external scripts. Mog's capability system gives the agent full control over I/O, so it can enforce whatever permissions it wants in the Mog code. This is even true if the plugin wants to run bash -- the agent can check each bash command the Mog code emits using the exact same predicate it uses for the LLM's direct bash tool. Mog is a statically typed, compiled, memory-safe language, with native async support, minimal syntax, and its own compiler written in Rust and its own runtime, also written in Rust, with `extern "C"` so the runtime can easily be embedded in agents written in different languages. It's designed to be written by LLMs. Its syntax is familiar, it minimizes foot-guns, and its full spec fits in a 3200-token file. The language is quite new, so no hard security guarantees are claimed at present. Contributions welcome! https://gist.github.com/belisarius222/203ac5edbc3306c34bf0481f451d4003 March 6, 2026 at 10:46PM

Show HN: VaultNote – Local-first encrypted note-taking in the browser https://ift.tt/ledpwmA

Show HN: VaultNote – Local-first encrypted note-taking in the browser Hi HN, I built VaultNote, a local-first note-taking app that runs entirely in the browser. Key ideas: - 100% local-first: no backend or server - No login, accounts, or tracking - Notes stored locally in IndexedDB / LocalStorage - AES encryption with a single master password - Tree-structured notes for organizing knowledge The goal was to create a simple note app where your data never leaves your device. You can open the site, enter a master password, and start writing immediately. Since everything is stored locally, VaultNote also supports import/export so you can back up your data. Curious to hear feedback from the HN community, especially on: - the security approach (local AES encryption) - IndexedDB storage design - local-first UX tradeoffs Demo: https://ift.tt/H0TeADm Thanks! https://ift.tt/DRFLpfv March 6, 2026 at 11:22PM

Show HN: Cognitive architecture for Claude Code – triggers, memory, docs https://ift.tt/w3azeZ7

Show HN: Cognitive architecture for Claude Code – triggers, memory, docs This started as a psychology research project (building a psychoemotional safety scoring model) and turned into something more general: a reusable cognitive architecture for long-running AI agent work. The core problem: Claude Code sessions lose context. Memory files live outside the repo and can silently disappear. Design decisions made in Session 3 get forgotten by Session 8. Documentation drifts from reality. Our approach — 12 mechanical triggers that fire at specific moments (before responding, before writing to disk, at phase boundaries, on user pushback). Principles without firing conditions remain aspirations. Principles with triggers become infrastructure. What's interesting: - Cognitive trigger system — T1 through T12 govern agent behavior: anti-sycophancy checks, recommend-against scans, process vs. substance classification, 8-order knock-on analysis before decisions. Not prompting tricks — structural firing conditions. - Self-healing memory — Auto-memory lives outside the git repo. A bootstrap script detects missing/corrupt state, restores from committed snapshots with provenance headers, and reports what happened. The agent's T1 (session start) runs the health check before doing anything else. - Documentation propagation chain — 13-step post-session cycle that pushes changes through 10 overlapping documents at different abstraction levels. Content guards prevent overwriting good state with empty files. Versioned archives at every cycle. - Git reconstruction from chat logs — The project existed before its repo. We rebuilt git history by replaying Write/Edit operations from JSONL transcripts, with a weighted drift score measuring documentation completeness. The divergence report became a documentation coverage report. - Structured decision resolution — 8-order knock-on analysis (certain → likely → possible → speculative → structural → horizon) with severity-tiered depth and consensus-or-parsimony binding. All built on Claude Code with Opus. The cognitive architecture (triggers, skills, memory pattern) transfers to any long-running agent project — the psychology domain is the first application, not a constraint. Design phase — architecture resolved, implementation of the actual psychology agent hasn't started. The infrastructure for building it is the interesting part. Code: https://ift.tt/9tXGuTF Highlights if you want to skip around: - Trigger system: docs/cognitive-triggers-snapshot.md - Bootstrap script: bootstrap-check.sh - Git reconstruction: reconstruction/reconstruct.py - Documentation chain: .claude/skills/cycle/SKILL.md - Decision resolution: .claude/skills/adjudicate/SKILL.md - Research journal: journal.md (the full narrative, 12 sections) Happy to discuss the trigger design, the memory recovery pattern, or why we think documentation propagation matters more than people expect for AI-assisted work. https://ift.tt/9tXGuTF March 5, 2026 at 10:05PM

Show HN: Gobble – Yet Another OSS Alternative to Google Analytics/PostHog, etc. https://ift.tt/hmcXVxf

Show HN: Gobble – Yet Another OSS Alternative to Google Analytics/PostHog, etc. https://ift.tt/O8rMZ9l March 5, 2026 at 01:12AM

Show HN: Qlog – grep for logs, but 100x faster https://ift.tt/I9cqWmY

Show HN: Qlog – grep for logs, but 100x faster I built qlog because I got tired of waiting for grep to search through gigabytes of logs. qlog uses an inverted index (like search engines) to search millions of log lines in milliseconds. It's 10-100x faster than grep and way simpler than setting up Elasticsearch. Features: - Lightning fast indexing (1M+ lines/sec using mmap) - Sub-millisecond searches on indexed data - Beautiful terminal output with context lines - Auto-detects JSON, syslog, nginx, apache formats - Zero configuration - Works offline - Pure Python Example: qlog index './logs/*/*.log' qlog search "error" --context 3 I've tested it on 10GB of logs and it's consistently 3750x faster than grep. The index is stored locally so repeated searches are instant. Demo: Run `bash examples/demo.sh` to see it in action. GitHub: https://ift.tt/0u6ZSFj Perfect for developers/DevOps folks who search logs daily. Happy to answer questions! https://ift.tt/0u6ZSFj March 5, 2026 at 12:17AM

Show HN: WooTTY - browser terminal in a single Go binary https://ift.tt/gBLso0e

Show HN: WooTTY - browser terminal in a single Go binary I needed a web terminal I could drop into K8s sidecars and internal tools without pulling in heavy dependencies or running a separate service. Existing options were either too opinionated about the shell or had fragile session handling around reconnects. WooTTY wraps any binary -- bash, ssh, or custom tools -- and serves a browser terminal over HTTP. Sessions survive reconnects via output replay. There's a Resume/Watch distinction so multiple people can attach to the same session without stepping on each other. https://ift.tt/nTG8Fk0 March 4, 2026 at 11:32PM

Show HN: Agent Action Protocol (AAP) – MCP got us started, but is insufficient https://ift.tt/tlja3ov

Show HN: Agent Action Protocol (AAP) – MCP got us started, but is insufficient Background: I've been working on agentic guardrails because agents act in expensive/terrible ways and something needs to be able to say "Maybe don't do that" to the agents, but guardrails are almost impossible to enforce with the current way things are built. Context: We keep running into so many problems/limitations today with MCP. It was created so that agents have context on how to act in the world, it wasn't designed to become THE standard rails for agentic behavior. We keep tacking things on to it trying to improve it, but it needs to die a SOAP death so REST can rise in it's place. We need a standard protocol for whenever an agent is taking action. Anywhere. I'm almost certainly the wrong person to design this, but I'm seeing more and more people tack things on to MCP rather than fix the underlying issues. The fastest way to get a good answer is to submit a bad one on the internet. So here I am. I think we need a new protocol. Whether it's AAP or something else, I submit my best effort. Please rip it apart, lets make something better. https://ift.tt/GtCop5h March 3, 2026 at 09:22PM

Show HN: A tool to give every local process a stable URL https://ift.tt/yav96BQ

Show HN: A tool to give every local process a stable URL In working with parallel agents in different worktrees, I found that I had a lot of port conflicts, went back and forth checking what incremented port my dev server was running on, and cookie bleed. This isnt a big issue if running a few servers with full a stack framework like Next, Nuxt, or Sveltekit, but if you run a Rust backend and a Vite frontend In multiple worktrees, it gets way more complicated, and the mental model starts to break. That's not even adding in databases, or caches. So I built Roxy, which is a single Go binary that wraps your dev servers (or any process actually) and gives you a stable .test domain based on the branch name and cwd. It runs a proxy and dns server that handles all the domain routing, tls, port mapping, and forwarding for you. It currently supports: - HTTP for your web apps and APIs - Most TCP connections for your db, cache and message/queue layers - TLS support so you can run HTTPS - Run multiple processes at once each with a unique URL, like Docker compose - Git and worktree awareness - Detached mode - Zero config startup My co-workers and I have been using it a lot with our workflow and i think it's ready for public use. We support MacOS and Linux I'll be working on some more useful features like Docker compose/Procfile compatibility and tunneling so you can access your dev environment remotely with a human readable URL Give it a try, and open an issue if something doesnt quite work right, or to request a feature! https://ift.tt/uSOrK4Y https://ift.tt/uSOrK4Y March 4, 2026 at 12:18AM

Show HN: Smart-commit-rs – A zero-dependency Git commit tool in Rust https://ift.tt/dtQxqur

Show HN: Updater – one command for macOS app updates https://ift.tt/W7mPiFo

Show HN: Updater – one command for macOS app updates I built updater to solve a small but annoying problem: macOS app updates are fragmented across different systems. updater scans installed apps, determines where each app should be checked (Sparkle, Homebrew casks/formulae, Mac App Store via mas, GitHub Releases, and macOS system updates), then runs source specific update actions from the terminal. It also has an interactive TUI (run `updater` with no args). A few commands: updater check updater update --all updater update "1Password" Repo: https://ift.tt/GVljZok Would love feedback, especially on reliability and edge cases. https://ift.tt/GVljZok March 2, 2026 at 12:46AM

Show HN: Mrkd – A native macOS Markdown viewer with iTerm2/VSCode theme import https://ift.tt/jftBxwU

Show HN: Mrkd – A native macOS Markdown viewer with iTerm2/VSCode theme import Using Opus 4.6 I built a markdown viewer for macOS that uses zero web technology. No Electron, no WebView — markdown is parsed with cmark-gfm and rendered directly to NSAttributedString via TextKit 2. The result is native text selection, native accessibility, and a ~1MB binary that launches pretty much instantly. It supports GFM tables, task lists, syntax-highlighted code blocks, and inline images. You get a built-in themes (Solarized, Dracula, GitHub, Monokai) plus the ability to import your own from iTerm2 or VS Code theme files. The part I’m most pleased with is the Quick Look integration — select a .md file in Finder, hit Space, and you get a fully themed preview using whatever theme and fonts you’ve configured in the app. No setup required; the QL extension registers automatically on first launch. It also bundles variable fonts (Geist, Inter, JetBrains Mono, iA Writer Mono, and more) so typography looks good out of the box. The whole thing is built in Swift with no dependencies beyond cmark-gfm and Highlightr. https://ift.tt/Xo0qzP2 https://ift.tt/Xo0qzP2 March 2, 2026 at 12:18AM

Show HN: PraxisJS – signal-driven front end framework and AI experiment https://ift.tt/Hm8pW2d

Show HN: PraxisJS – signal-driven front end framework and AI experiment I built PraxisJS, a signal-driven frontend framework exploring what a more explicit and traceable architecture could look like. PraxisJS started as a personal project. It reflects a single perspective on frontend design, not a committee decision, not a consensus. I wanted to see how far you can push explicitness before it becomes friction. Most frameworks optimize for writing less. PraxisJS questions that tradeoff. @State doesn’t suggest reactivity, it is reactive, visible in the code. Signals reach the DOM without a reconciliation layer in between (the renderer is still evolving toward that goal). It also became an AI-assisted experiment, not to automate thinking, but to pressure-test ideas. Some parts came from that collaboration. Some exist because it failed. v0.1.0 beta, experimental, not production-ready. But the ideas are real. https://praxisjs.org/ March 1, 2026 at 11:27PM