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A PM's Guide to AI Agent Architecture


A complete guide to agent architecture, orchestration patterns, trust strategies, and adoption plans for PMs building AI agents.

Each integration makes the agent more useful but also creates more potential failure points - think API rate limits, authentication challenges, and system downtime. Implementation note: Tools like MCP(Model Context Protocol) are making it much easier to build and share skills across different agents, rather than rebuilding capabilities from scratch. We'll also walk through the governance concerns that actually matter in practice - not just theoretical security issues, but the real implementation challenges that can make or break your launch timeline.

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