A PM's Guide to AI Agent Architecture

What does the PM title even mean at this point? It's a bit surprising to see a deep dive into technical architecture - though there is massive value in understanding what's involved - as a PM responsibility, this is more in TPM (technical program manager) land which is a different job.

In my book they ideally focus on understanding scope, user needs and how to measure success, while implementation details such as orchestration strategies, evaluation and making sure your system delivers the capabilities you want in general, are engineering responsibilities.

This post does not do a deep dive into technical architecture.

The PM's role is to whip devs until the requirements are met. That seems apt here. Even if the requirements make zero sense

When it comes to LLMs and agents, this is the technical architecture: orchestration patterns, memory, context handling, MCP, etc.