AI Agent Squad | Multi-Agent System with Shared Memory by Chetan PathakAI Agent Squad | Multi-Agent System with Shared Memory by Chetan Pathak

AI Agent Squad | Multi-Agent System with Shared Memory

Chetan Pathak

Chetan Pathak

Honestly, most AI agents have a goldfish problem. you brief them, they do the job, next session they’ve forgotten everything. so you explain it all again. every single time
that’s what this project came from. i didn’t want another chatbot you restart every morning. i wanted agents that remember what they’re working on
So i developed a squad. not one agent doing everything badly, but multiple agents with different skills working together, like a small team. each one has its own job, and they share one workspace where all the context lives. when one finishes, the next picks up with the full picture. nobody starts from zero
then the part that makes it usable... you can assign tasks and track progress. you see what’s in progress, what’s done, what’s stuck. managing agents the way you’d manage people, minus the daily check-in
Skills behind it... AI agent development, multi-agent orchestration, bot development, memory and context handling, task tracking
Tools... Claude Code, MCP Servers, OpenAI/LLM APIs, Supabase for the shared workspace
Real talk, it’s not magic. agents still need clear tasks and a person watching the output. what it fixes is the repeating, the re-explaining, the lost context
If you’re tired of briefing your AI from scratch every time, this is the fix
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Posted Nov 1, 2026

Multiple AI agents with different skills, one shared workspace, memory that sticks — assign tasks, track progress, no context lost.