Ray
I've been using this daily for 4 months and figured others might find it useful. This is my first open source project so would love any feedback. Ray connects to your bank via Plaid, stores everything in an encrypted local SQLite database, and lets you ask questions about your finances in natural language. No cloud, no account, your data is stored on your machine. Before anything reaches the LLM, all PII is stripped — your name, companies, transaction details are redacted and replaced with tokens, then rehydrated locally in the response. The AI never sees who you are.
Artemis.fyi
There are plenty of Artemis II trackers out there. I looked at a bunch and kept running into the same issues - some had data that didn't look right, it was hard to use on smaller screen, others felt overly complicated for what I actually wanted to know: what's the crew doing, where is Orion, how fast is it going. The best one I found was issinfo.net/artemis, which inspired a lot of the design. So I built my own. The part that was genuinely interesting to me was the data. Turns out anyone can query JPL's Horizons API for full ephemeris data on the Orion spacecraft - position, velocity, range - for free. I had no idea this existed. Even better: NASA's Deep Space Network publishes a live XML feed (eyes.nasa.gov/dsn/data/dsn.xml) that updates every 5 seconds showing exactly which ground antennas are talking to which spacecraft. Right now two dishes in Canberra are locked onto Orion - one sending commands, both receiving 6 Mbps of S-band telemetry at 296,000 km. You can see Juno at Jupiter, JWST, Mars Odyssey, all in the same feed. It's pretty amazing what's just sitting there in the open. The app fetches trajectory from Horizons, crew activities from NASA's published flight plan, and live ground station status from DSN. I'll be honest - it's mostly vibe-coded with supervision. The data pipeline is the part that was more manual: figuring out what's publicly available, how to compute relative positions from raw vectors, how to cache and backfill. That was the fun part. Code is open on GitHub. I built it for myself and as a fun exercise, but happy for any feedback - especially around data correctness and what other public data sources are out there that I might be missing. Source: https://github.com/dmarchuk/artemis.fyi
Contrapunk
Show HN: Contrapunk – Real-time counterpoint harmony from guitar input, in Rust
Cabinet
Hi HN, for quite some time I've been thinking how LLMs are missing the knowledge base, where I can dump CSVs, PDFs, and most important, inline web app. running on Claude Code (bring your own agent) with agents with heartbeats and jobs https://runcabinet.com It runs locally and is installable via npm. GitHub (open source): https://github.com/hilash/cabinet This is still very early. I put the first version together quickly after seeing a post by Andrej Karpathy about LLM knowledge bases, which matched closely with what I’d been building. Some people have already started trying it and opening PRs, which has been encouraging (got 374 stars in 2 days :] ) If useful: Waitlist for a hosted version: https://runcabinet.com/waitlist Discord (small, but growing): https://discord.gg/rxd8BYnN Would really appreciate feedback: does this “KB + agents” model make sense? what would you expect from a system like this? where does this fall apart? Happy to answer anything. Hila
Enter an Instagram/TikTok handle, get a data-backed price for collab
I had no clue what to offer IG/Tiktok creators for collabs and their offers were too high. That's why built a thing that turns IG profile name into suggested pricing with key metrics and suggestions, looking forward to hearing your feedback!
YouTube search barely works, I made a search form with advanced filters
Show HN: YouTube search barely works, I made a search form with advanced filters
I Built Paul Graham's Intellectual Captcha Idea
PG has posted about improving social networks using something like an "intellectual CAPTCHA" many times [1][2][3][4] - "Make users pass a test on basic concepts like the distinction between necessary and sufficient conditions before they can tweet." I felt the same way. So I built one using a mix of simple math, logic, and Twitter/X Community Noted posts. Try sample questions here - https://mentwire.com/sample - without signing up. - Invites are temporarily open to HN users. - Onboarding test + one daily question before accessing feed, post or reply. - Posts authors are anonymous until upvoted or downvoted, forcing evaluation of content on merit. - Face ID (on-device only) to post/reply, pangram checks for AI text. Sourcing good questions turned out to be much harder than I thought. If you have suggestions to scale this, I would love to hear. Eventually, could be gated across disciplines/topics to get a competence × interest graph instead of the pure interest graph of today's social networks. [1] https://x.com/paulg/status/1235949761359904768 [2] https://x.com/paulg/status/1576517990182359040 [3] https://x.com/paulg/status/1514979883948126209 [4] https://x.com/paulg/status/1505842647319126016 Repost from https://news.ycombinator.com/item?id=47577829. This link contains a full quiz and linked directly to sample to try without signing up.
GovAuctions lets you browse government auctions at once
I've long been into finding deals on government auction sites (seizures, surplus sales etc.) - right now for example San Diego DHS is selling 26 tons of lead shot, with bidding starting at $1,000 ¯\_(ツ)_/¯ It has historically been extremely tedious though: scanning dozens of janky sites which have interminable page loading times; back buttons take you all the way back to the homepage etc. The site I built - GovAuctions - lets you search every government surplus auction at once. You can filter by location, category, and price, save items to a watchlist, and get alerts when new auctions match what you're looking for. Let me know what you think, if you have any suggestions, and if you find any deals in your area!
I made a crossword app for language learners
Hi HN! In the last couple of weeks I've been working on Cranki: Cranki = Crosswords + Anki. (It's a stupid name tbh, haha) I like doing crosswords in Spanish (to learn vocab) but none of the apps out there allowed me to use my own list of words that I come across. So I built one instead. It's entirely client-side. No server, no database, no accounts, etc. Your words and stats are stored in local storage. I built this for myself but let me know if you like it!
I built a 2-min quiz that shows you how bad you are at estimating
I've gotten to the point in my career where I now make strategic decisions often (hiring, firing, choosing what equipment to go with, etc.), as well as in my personal life where I need to strongly weigh my options for a big purchase or investment. I found a not-so-surprising parallel between the two as these decisions "resolved." Am I making good decisions or am I getting lucky? Did some research, read some books, and realized I should get in the habit of tracking my decision process. That quickly turned into the idea that formed Convexly. The landing page is a 10-question calibration quiz where you assign a confidence level to statements drawn from a rotating pool of 100 (working on making the pool larger) and you get a Brier score back instantly. No signup required, and you can share your scores right away. If you find it interesting, you can create a free account where you can track your decisions with probability estimates, resolve them over time, and get calibration curves that show if you are over/underconfident. From what I've seen so far, users are overconfident when they say they're between 70-90% sure about something. For the math: Beta-PERT distributions for the payoff modeling, Kelly criterion for the position sizing, signal detection theory for separating skill from randomness. On the coding side: FastAPI with NumPy/SciPy, frontend in Next.js and Supabase. So far this has been a solo project of mine. If you want to see all the features use code SHOWHN for 30 days of full access, no credit card required. Curious if anything about your score surprised you after taking the quiz.
Freestyle
We’re Ben and Jacob, cofounders of Freestyle (https://freestyle.sh). We’re building a cloud for Coding Agents. For the first generation of agents it looked like workflows with minimal tools. 2 years ago we published a package to let AI work in SQL, at that time GPT-4 could write simple scripts. Soon after the first AI App Builders started using AI to make whole websites; we supported that with a serverless deploy system. But the current generation is going much further, instead of minimal tools and basic serverless apps AI can utilize the full power of a computer (“sandbox”). We’re building sandboxes that are interchangeable with EC2s from your agents perspective, with bonus features: 1. We’ve figured out how to fork a sandbox horizontally without more than a 400ms pause in it. That's not forking the filesystem, we mean forking the whole memory of it. If you’re half way down a browser page with animations running, they’ll be in the same place in all the forks. If you’re running a minecraft server every block and player will be in the same place on the forks. If you’re running a local environment and an error comes up in process that error will be there in all the forks. This works for snapshotting as well, you can save your place and come back weeks later. 2. Our sandboxes start in ~500ms. Demo: https://www.loom.com/share/8b3d294d515442f296aecde1f42f5524 Compared with other sandboxes, our goal is to be the most powerful. We support full Linux + hardware-virtualization, eBPF, Fuse, etc. We run full Debian with multiple users and we use a systemd init instead of runc. Whatever your AI expects to work on debian should work on these vms, and if it doesn’t send a bug report. In order to make this possible, we’ve moved to our own bare metal racks. Early in our testing we realized that moving VMs across cloud nodes would not have acceptable performance properties. We asked Google Cloud and AWS for a quote on their bare metal nodes and found that the monthly cost was equivalent to the total cost of the hardware so we did that. Our goal is to build the necessary infrastructure to replicate the human devloop on the massively multi-tenant scale of AI, so these VMs should be as powerful as the ones you’re used to, while also being available to provision in seconds.
Per-user isolated environments for AI agents
Show HN: Per-user isolated environments for AI agents