How I Built a Multi-Agent AI Pipeline with Python and Claude

I spent the last few months building a system where 8 AI agents collaborate to turn a topic into a publication-ready LinkedIn post. Not a single prompt — a pipeline where each agent has one job, and they pass work between each other with feedback loops. Here's how it works and what I learned. The Problem I was writing LinkedIn posts manually. Research a topic, write the draft, edit it, find hashtags, create a visual, schedule it. Each post took 45-60 minutes. I wanted to automate the workflow but quickly hit a wall: a single prompt can't do all of this well. Asking one LLM to research, write, validate, and generate visuals produces mediocre results across the board. The fix was splitting the work into specialized agents — each one focused on doing one thing well. The Architecture Topic Research --> Writing --> Validation --> Visual Generation ^ | | v +--- Feedback Loop (if score below threshold) The Orchestrator manages the full pipeline. If a post scores below the quality thr