Designing products for AI agents: A PM’s guide to agent usability

As AI agents increasingly act on users’ behalf across products and systems, software must be designed not only for human interaction but also for reliable machine operation. Unlike people, agents need discoverable capabilities, structured and consistent data, predictable behavior, machine-readable errors with recovery guidance, scoped permissions, and detailed audit trails to execute tasks safely and effectively. Product teams should treat human-facing interfaces and agent-facing APIs, tools, integrations, and workflow endpoints as equally important product surfaces, avoiding common limitations such as UI-only actions, ambiguous schemas, unstable API responses, weak error handling, and inadequate visibility into agent activity. Product requirements documents should include agent-specific user stories, programmatic access requirements, schema and validation standards, recovery criteria, and metrics such as tool-call failures, completion rates, retries, escalations, and automation success. Human judgment and control remain essential, but successful products will increasingly be those that are both easy for people to use and straightforward for them to delegate to agents.

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