Iterative Planner

Iterative Planner

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**A [Claude Code](https://docs.anthropic.com/en/docs/claude-code) skill that stops an agent from losing the plot halfway through a hard task.**

Turn an agent loose on something big and a familiar failure shows up. It plans once, starts strong, then hits a wall. It patches the wall. The patch breaks something else, so it patches that. A few turns later it has forgotten which fixes it already tried, the codebase is a thicket of half-reverted experiments, and nobody — human or model — can say what state anything is in.

The root cause is not intelligence. It is memory. **The context window is RAM: fast, volatile, and it rots mid-task.** Push enough tokens through it and the early decisions blur, the failed approaches fade, and the agent starts relitigating settled ground.

Iterative Planner gives the agent a disk. Every finding, decision, pivot, and dead end is written to the filesystem the moment it happens — structured, indexed, and re-read on a schedule. The work is driven by a six-state machine: **Explore → Plan → Execute → Reflect → Pivot → Close**. The context window can forget. The plan directory does not.

The context window is RAM. The filesystem is disk. Truth lives on disk.

And here is the part that sneaks up on you. Those files are not just scratch space for one task — they are a record the *next* task inherits. Every plan leaves behind findings, decisions, hard-won lessons, and a living map of the system it worked on. So the agent stops starting cold. It begins each new job already knowing the terrain, and that knowledge compounds: the tenth plan is sharpe