Ho creato un flusso di lavoro di intelligenza artificiale multi-agente con Claude Code + Java/Spring Boot (esperimento reale).
I’ve been experimenting with Claude Code to go beyond “AI as a copilot” and instead simulate a small team of AI agents working on software development tasks.
The idea was simple: Instead of asking Claude to help with isolated snippets, I structured it into a workflow where different “agents” handle:
\-code generation
\-review & validation
\-architecture decisions
\-cost/governance constraints
All orchestrated through a Java / Spring Boot backend.
What I found interesting is that the real challenge wasn’t generating code, it was coordination, governance, and control over the system behavior.
In practice, the hard problems became:
\-preventing agents from diverging in logic
\-maintaining consistency across outputs
\-controlling cost and iteration loops
\-introducing human decision points at the right time
I documented the full setup, architecture, and lessons learned here:
https://www.rheorix.com/en/2026/05/19/how-i-built-a-team-of-ai-agents-with-claude-code/
Curious if anyone else is experimenting with similar multi-agent setups, especially in production or near-production environments.
What patterns are you using for orchestration and governance?