# How to Build Your AI Agent Team With Claude Opus 5.5

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How to Build Your AI Agent Team With Claude Opus 5.5

Build an orchestrator, narrow specialists, and a critic, then add the permission boundaries, spending caps, time limits, evaluation tests, and stop conditions required to run the team responsibly.

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Oct 1

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Everyone is talking about AI agents. The quiet problem is that most “teams” are five vague agents with broad permissions, weak handoffs, and no spending ceiling. They produce more activity, not necessarily better work.

Claude Opus 5.5 makes coordinated work more practical. Anthropic built the model for long-running agentic coding and knowledge work, priced it at $4 per million input tokens and $20 per million output tokens, and made effort the main control for reasoning depth, latency, and cost. But a stronger model cannot rescue a weak architecture.

The useful question is not how many agents you can run. It is whether each new agent creates a measurable advantage over one well-designed agent.

This guide starts with a single-agent baseline. Then it adds one orchestrator, narrow specialists, and a critic only where parallel work, context isolation, specialized instructions, or tighter permissions justify the complexity.

You will finish with a documented implementation, hard runtime limits, a reproducible comparison test, and a release scorecard that tells you whether the team is actually faster, safer, cheaper, or better...

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