The hard part of my AI agent wasn't doing the work, it was planning it
8.4 relevance
Score Breakdown
technical depth 9
novelty 8
actionability 9
community 6
strategic 7
personal 10
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Deep dive into AI agent planning architecture, directly matches agent orchestration interest.
Summary
Building an AI agent CLI that executes actions across hundreds of apps revealed that the planning mode was far harder than direct execution. The initial approach of using a single agent for both planning and execution failed because the two modes pull in opposite directions, leading to interference. The solution required a separate planner agent with read-only tools to research actual system state before generating plans, preventing it from fabricating steps based on assumptions.