In Agent design, PRD is not just a document, but a "code", a context, and the function itself.

There is a huge difference between traditional software development and AI Agent development paradigms, which can be reflected in the role of PRD (Product Requirements Document).

PRD (Product Requirements Document), describes business goals, user requirements, functional specifications, non-functional requirements, etc. It is the product manager's statement of the product's intentions.

Traditional software has static, fixed functions and clear boundaries. A change in requirements usually means code modification, testing, and redeployment. Product managers have to spend a lot of effort to ensure that product implementation reflects the design requirements of the PRD.

In Agent design, PRD is almost equivalent to System Prompt. As part of the context, PRD directly affects the function performance and is even part of the function.

In PRD, descriptions of the agent's role responsibilities, functional capabilities, core problems to be solved, expected behavior patterns, thinking and reasoning processes, boundary restrictions, etc. are the system prompts for the agent.

Whether it is PRD or system prompts, these are carefully designed natural language instructions.

In the debugging of agent software, many tasks do not require explicit code. Once the system prompts you have written are input into the agent framework (including tools, memory, planning and other mechanisms), the agent can show the prototype of the expected functions. LLM naturally understands and responds to these contexts.

For Agent product managers, the product requirement description (PRD) is part of the product functionality.

The AI ​​Agent product manager is not only a product designer, but also a debugger and a direct developer.