01 - Task Decomposition
How agents break complex goals into ordered, dependency-tracked subtasks. Hierarchical decomposition, DAG representation, dynamic replanning, and full Python implementation.
7 docs tagged with "planning"
View all tags02 - Planning with LLMs
Zero-shot, chain-of-thought, Tree of Thoughts, ReWOO, and MCTS-guided planning. When LLM plans fail and how to recover. Full Python implementation of Tree of Thoughts.
03 - Checkpointing and Recovery
How to save agent state mid-run, resume after failures, design idempotent actions, and build production-grade checkpoint systems with SQLite and S3.
04 - Handling Ambiguity and Clarification
How agents detect ambiguous instructions, decide when to ask vs. proceed, design targeted clarification questions, and avoid the overly-cautious anti-pattern.
05 - Interruption and Human-in-the-Loop
When and how agents pause for human judgment. Action classification, async approval workflows, Slack-based HITL, and resuming after interruption.
06 - Evaluation of Long-Horizon Tasks
How to evaluate multi-step agent trajectories. Task completion, path quality, error recovery, efficiency, and LLM-as-judge. Benchmarks and trajectory scorers.
Module 05: Long-Horizon Planning
How agents decompose complex multi-step tasks, plan across long horizons, recover from failures, and know when to ask for help.