davidtsong · HN

Benchmarklist: track AI benchmarks (2.4k+), models, and capabilities

dudemanAtl · HN

PlanWright – A control plane for AI coding agents

shreyans_assistiv · Product Hunt

AskCodi Orchestrate agents at scale while reducing cost

@SamiirHalady · X

Building ReviewMitra: Living Customer‑Centricity If you listen closely enough, your customers will write your product roadmap for you. When I built the goal was simple : help businesses get Google reviews without typing them out. That idea became reality. My first vibe‑coded app took time, but it worked. Then a friend asked, “Can we respond to reviews too?” That one question sparked the next feature : replying directly from the merchant login. Soon, I added sentiment analysis, a word cloud, and WhatsApp integration. Then came support for multi‑outlet brands, and now, a white‑label option for agencies. And here’s the part I’m most proud of - ReviewMitra now generates reviews in 39 languages, including 22 Indian languages and several European and Asian ones. Because trust shouldn’t be limited by language! Every new feature wasn’t planned, it was inspired. By feedback, by curiosity, by conversations. For years, I’ve told clients that the best approach is customer‑

u/EagleApprehensive · Reddit

I've made an IDE. I built intentic.dev , a free IDE that runs self-hosted on your hardware in docker - can be easily shared with coworkers and deployed on servers. It's not for you! It's a home for agents, you're just a guest there so behave. Comes with cool stuff for AI powerusers - token saving mechanisms, codebase indexers, healthiness checkers - helps you keep the code manageable. Can connect to stuff as well. And if you're crazy you can even add widget to your produc

tyagivivek · HN

Parley – your coding agent can talk to a teammate's agent

@viewfy_ai · X

jayaprabhakar · HN

I've been building an open source formal methods system (fizzbee.io) for the past few years. Today I'm launching a new app built on the same technology. It performs requirements engineering using formal verification to uncover gaps and produce precise instructions for your coding agents to follow. When given a prompt, it - asks high signal follow-up questions - converts to formal spec and identifies complex requirements gaps - generates validation scenario At the end, it produces a specification document that can be shared with coding agents. In my trials on various projects, it produces working code in fewer iterations. Please give it a try and share your feedback. https://fizzbee.ai/ You can also look at a sample project. https://fizzbee.ai/projects/94bf2869-97a1-445c-8f5d-4445848b...

@snipextt · X

i'm building to solve build products fast and also to build presence fast :)

JulianQuinn · HN

Show HN: TaskPeace – a task queue my AI coding agents pull work from over MCP

Aldasams · HN

Show HN: DocFlow – AI documentation updates for GitHub pull requests

jacobgc · HN

Outside Agent – Build SMS Agents from Claude Code