@Akinzoooo · X

@TractLens · X

rolesage · Product Hunt

RoleSage See the person in an avalanche of AI-polished applications

@Wovyr · X

@jozef_x1 · X

🚨 I Vibe Coded F0ur (4) different versions of @coreyganim's "Ai Audit" Funnel, which is your favourite? VERSION #3:

@Val8app · X

u/OGMYT · Reddit

I built LOLM, a lower-cost LLM agent that shows what it actually did — looking for blunt feedback I’m one of the founders/builders behind LOLM. Most AI products show an answer but hide whether the system retrieved anything useful, verified the result, switched models, hit a limit, or simply stopped. LOLM exposes those parts through controller events and run receipts. It includes: - Live agent - CLI - Coding and small app-building workflows - Memory and self-hosting options - Control decis

@VictorLepri · X

solution to organize house search, sharing with people to review and comment, rank and help make a structured decision. Tailored to NYC but works everywhere in USA

@PDFGrid · X

tahazsh · HN

Hi! I’m Taha. In many agentic products that support workflows (including one I worked on), I noticed they either don’t support node-based editors, or use React Flow and go through the difficult work of integrating it into their product to run it and work with their existing logic. So I thought about creating a tool that could help with this by closing the gap between the editor and the runtime. That’s why I created Wayflow. The basic architecture is simple: you just need to create a graph (which is a JSON object) that the runtime knows how to run. The runtime doesn’t care where that graph is coming from, it just needs the right schema. And with the help of the editor, you can create the graph, and then export it or directly save it on your backend in your database. And then when you want to execute it, you just hand it to the runtime. The runtime can either stream the execution (which is useful for the editor), or give you the final result. How you execute the graph is up to you: t

@RasinMuhammedX · X

Declarative Synthetic Data Generation.

u/East_Operation1151 · Reddit

I built pondas: run a team of AI agents like a game to build an app I've been building this for a while and finally want to show it here. Most AI app builders are one model in a black box. You type a prompt, it guesses, and you hope what comes out works. I wanted the opposite: real control over how the AI builds. So in pondas you run a whole team of AI agents, and you control the loop they work in. What it actually does: - You describe an app in plain words and a team goes