Multi-agent is the new microservices

Multi-agent AI systems are being over-adopted in the same way microservices were — applied broadly before teams have problems that actually warrant the complexity. Anthropic, OpenAI, Microsoft, and Google all advise starting with the simplest solution: a single optimized LLM call, then retrieval, then tools, then a single agent loop. Only add a second agent when you can clearly identify parallelizable tasks, context pollution, or specialization needs. Multi-agent architectures cost significantly more in tokens, observability, error handling, and maintenance. Most enterprise teams don't yet have problems worth decomposing across agents, and adding agents won't fix weak retrieval, vague tools, or poor documentation — it will amplify those problems.