I just uploaded a new YouTube video for the community. In this demo, I show how the SaaS Roast Agent reviews a real SaaS codebase using 6 AI agents. One agent scans the project. Five specialist agents review it in parallel: authentication tenant isolation security database performance architecture Then a final synthesis agent combines everything into one Launch Readiness Report. The report gives: → launch score out of 100 → category-level scores → critical issues → security risks → database and architecture problems → practical 7-day fix plan The idea is simple: Founders, indie hackers, and vibe coders are building faster than ever. But fast shipping without review can create dangerous production bugs. This agent helps you move fast without blindly launching risky SaaS code. Built with Python, FastAPI, and the official Claude SDK. Just Claude SDK, structured prompts, tools, and a practical multi-agent workflow. Watch here https://youtu.be/fsE-XLm1yxI After watching, tell me this: Would you use an AI agent like this before launching your own SaaS project?

We just wrapped the first live community session. What we covered: 1. Why this community exists, and how Sundays will run from here 2. The 3 Levels of AI Agents: Chatbot (talks), Tool-Using (acts), Workflow (ships a full process) 3. The beginner trap: most people jump straight to Level 3 and stall. Build a small Level 2 first. 4. How to actually start: pick one boring agent that solves one real problem you have this week. Your challenge this week Before next Sunday, post one AI agent idea in the community using this format: 1. Agent name 2. Problem it solves 3. Who it helps 4. Tools it needs 5. What the first version should do I will review selected ideas live next Sunday and help you sharpen them. Recording is pinned in Youtube Resources. If you missed it, drop your question below and I will answer every one in the next 48 hours. What is the first agent you want to build?

Day 30 of my email sorter. now also drafts replies for the 'can wait' bucket. team is using the drafts as starter text. saved each person ~20 min/day they say. wild that the simplest agent in my system is the one that's actually useful.

Been reading a lot over the past few days, especially the failure-story posts (Priya's CrewAI typo, the overbuilt summarizer post). Honestly easier to learn from those than from happy-path tutorials. Anyone else find the failure stories more useful than the polished wins?

Spent the weekend rewriting one of my agents from CrewAI to a single OpenAI SDK call. Same outcome. 1/3 the latency. 1/4 the cost. Multi-agent is fun but it's expensive theater for most jobs.