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A discussion about designing AI agent systems in heavily regulated environments, focusing on the challenge of false positives and how to present model confidence to users without adding cognitive load.
The author shares their experience building an autonomous AI research agent for pre-meeting paraplanning tasks using Claude Opus 4, but faces challenges extending it to post-meeting document generation due to compliance and template issues. They seek advice on whether the two phases should remain separate and how to bridge them in regulated environments.