I've been working on a search engine project called Slick for over a year now, and I finally have an early access version ready to share.
Slick is a search engine built for speed, privacy, and user control. We never track search queries, location, or user behavior. Since we use our own index and ranking, no tracking slips through proxies.
You just launched on Product Hunt and X is blowing up with replies. Instead of letting that momentum fade, embed your best reactions directly on your landing page while the hype is still fresh.
Turn launch day energy into long-term credibility.
Sign in Fetch & Curate Publish. Withing seconds you'll have options of 1. URL
I've been building ATLAS for 7 months. The idea is simple: instead of charts and opinions, you get the actual probability of making or losing money on any stock.
This is what a simulation looks like: for example Apple, target +5%, 75 days. You can do this for 4,500+ stocks, or get a suggestion of the best stocks with the highest probability for your constraints! The idea is that you can make a more informed decision about your investment ideas!!
We're launching TeamAI today AI employees that get a real Ubuntu desktop, open Chrome, and actually complete tasks for you.
Not just answers. Real work.
The most surprising use case from our early users has been competitive research. They tell the agent "go through these 20 competitor websites and summarize their pricing" and come back in 20 minutes. No copy-paste, no prompt engineering, just done.
One pattern I keep seeing is that logging starts out useful, then gradually becomes inconsistent, noisy, expensive, and harder to trust. Field names drift, context goes missing, dashboards get polluted, and sometimes sensitive data ends up in places it never should have reached.
The deeper problem seems to be that most teams try to fix logging after the data has already entered downstream tools. By then, the cost, risk, and cleanup burden are already there.
I m curious how other teams handle this. What breaks first in practice: naming consistency, missing required context, sensitive fields in logs, alert noise, or ingestion cost? I m building in this area and want to learn where current approaches still fall short.
Hey makers. We re tech founders who saw a massive gap in interior design tools. Designers spend days turning 2D floor plans into 3D. We built Foursite to fix that.
