I'm a solo founder, and I just shipped something I've been thinking about for years.
The problem: senior architects and staff engineers at scaling startups spend days drawing diagrams in Lucidchart or Visio, debating system boundaries, only to ship something that breaks under load. The diagrams are manual, static, and disconnected from actual reality. Tools like draw.io don't validate anything they're just boxes and arrows.
So I built Archivolt. You describe your system in plain English. Tell it your tech stack and expected scale. It analyzes your design for failure modes, load bottlenecks, single points of failure, anti-patterns the stuff that actually breaks production systems. Then it generates a validated blueprint and production-ready scaffolds in 60 seconds.
Not a diagram generator. Not another AI that hallucinates. A validation engine that tells you what will actually break before you build it.
You know that moment. You've been reading for weeks. Your notes are a mess. Half-formed ideas, highlighted passages, questions that keep circling back. You know there's something there, but you can't articulate it cleanly enough to search for it.
So you open Google Scholar. Type something close. Get 2,000 results. Spend three hours filtering. Realize your search terms were wrong. Start over.
This is the hidden tax on research. Not the reading. Not the analysis. The orientation figuring out what you should even be looking at. It burns weeks.
We built Cognir because we got sick of paying that tax.
My name is Marta, and I m working on a startup idea that I genuinely believe could become something big and I want you to give me harsh and frank rather than nice and polite feedback.
Most AI agent frameworks are slow and expensive because they constantly shuffle massive JSON payloads and duplicate data between components.
Gliding Horse changes the game. We built an open-source AI Agent Operating System that treats your agents' memory with the extreme efficiency of a computer's hardware. Instead of passing heavy text blobs, Gliding Horse uses a unified data bus to pass lightweight pointers, making your multi-agent systems faster, cheaper, and infinitely more scalable.
Why developers love Gliding Horse:
Smart Memory Management (The "MMU" Engine) Inspired by CPU architecture, our system only loads the exact information your agent needs at any given moment. If data isn't active, it stays in deep storage until triggered just like a page fault. This slashes token costs and completely prevents context window overload.
Simple idea, tabs out of control? Close duplicates, group tabs by domain or category, create your own groups by domain, search for open tabs, export your open tabs to csv.
It s TabHawk - might it change your life? Give you back some control? My first extension but I m open to improvements, bug fixes and even new extension ideas. https://chromewebstore.google.co...
I'm Fares, indie iOS dev based in France. I built Dois-Je Signer after watching too many friends sign gym subscriptions, telecom plans, and freelance contracts they didn't fully read, then getting stuck with hidden tacit renewal clauses or 24-month commitments.
The app does one thing: you drop a French contract (PDF, photo, or pasted text), and an AI trained on French law (Code de la consommation, Code civil, current case law) analyzes every clause in around 30 seconds. You get:
