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This article serves as a non-technical PM's guide to orchestrators, context optimization, and evals for AI agents. Jake McCGwire shares practical lessons learned from building AI agents, demystifying technical concepts for product managers who need to understand agent architecture without deep engineering knowledge.
The piece covers key concepts PMs encounter when working with AI agents, including orchestration patterns, how context impacts agent performance, and evaluation methodologies. It's designed to help product managers have informed conversations with engineering teams and make better product decisions around agent-based systems.
This resource is ideal for PMs just starting their AI journey. It provides foundational knowledge in technical skills that will help you build a solid understanding of how AI impacts product management.
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Go to The Release NotesThis free short course from DeepLearning.AI teaches how to use large language models through the OpenAI API. Taught by Isa Fulford (OpenAI) and Andrew...
This ProductTapas newsletter article advocates for Claude Code as an essential PM productivity tool. The author claims to have saved over 200 hours in...
This guide teaches practitioners how to build effective AI prototypes through a structured, 12-step execution pipeline. Rather than creating impressiv...