How 9 AI Agents Collaborate to Code, Test, and Deploy Automatically

A developer created Agent Swarm, a pipeline where nine specialized AI agents collaborate to code, test, and deploy software automatically. The system includes agents for orchestration, search, planning, contracts, frontend, backend, testing, reviewing, and writing, with the orchestrator using mandatory pre-search to determine task complexity. The project is available on GitHub for cloning and configuration.

Modern software development is fractal. Every feature touches 5-10 contexts simultaneously. A single LLM struggles to maintain multi-domain coherence. This is the problem Agent Swarm solves. Unlike single-agent tools, Swarm is a pipeline where 9 specialized AI agents collaborate automatically, each with a precise role and strict constraints: Orchestrator, Search, Planner, Contract, Front, Back, Tester, Reviewer, Writer. The Orchestrator uses mandatory pre-search: extracts technical terms, runs parallel grep on the codebase, and counts distinct files touched. No LLM guessing its own difficulty. Routes: DIRECT → SIMPLE → ADAPT → MEDIUM → FULL. "Add a Recent Updates section to the homepage" → 8 files touched → MEDIUM. Planner designs 5-step plan. Front+Back implement in parallel. Tester ensures 80% coverage. Reviewer audits security =1.0, quality =0.85 . Merge automatic. git clone https://github.com/JohTandou/agent-swarm.git https://github.com/JohTandou/agent-swarm.git cp -r agent-swarm/.opencode/ ~/.opencode/ cp agent-swarm/opencode.json ~/.config/opencode/opencode.json