A shared, structured map that you and your AI agent navigate together. Built from your decisions, pivots, dead ends, and warnings.
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This is the living map of the product you're looking at. Every feature, bug fix, and pivot. 398 nodes, organized and searchable. Names anonymized.
A business major with zero Metal or GPU knowledge hit the hardware ceiling of Apple Silicon by orchestrating an AI agent through 28 optimization probes across 28 stateless sessions.
The tree encoded killed approaches with specific kill conditions. Every future session loaded the graveyard and went straight for what hadn't been tried.
When the agent said it was done, the human said read the tree, find every unresolved node, attack the first one. The next probe converted a 54-second regression into a 30-second speedup.
A flat scroll with no structure or status. The dead end from Week 2 is buried in a thread you'll never reopen. The decision from March contradicts April and neither says which is current.
Documented, but not enforced. Stale warnings sit for months because nothing flags them. Three files contradict each other and nobody knows which is authoritative. The discipline is on you to remember to check.
Remembers facts about you — your name, your stack, your preferences. Doesn't remember why you pivoted, what you ruled out, or which nodes are still unresolved.
Every piece of reasoning state has a place. Status. Warnings. Ruled-out approaches. Links between nodes. Write-time propagation checks that force the agent to ask: what else changes, what else needs updating? The map is a graph with guardrails, not a pile of hope.
You and your agent probe the problem. Most probes fail and that's expected. Every failure gets encoded with a specific kill condition. The cost of a bad idea is zero. The cost of a missed optimization is permanent.
The agent doesn't inventory its skills. It follows the problem. A node links to a sub-agent guide, loaded. A warning says thermal throttling makes it worse, seen before the agent can suggest it. The structure guides the loading, triggered by context, not by the agent's initiative.
Next session is smarter. Antibodies exist. The agent loads the graveyard and skips the dead ends. More usage → more failures encoded → smarter agents → better sessions. The map gets stronger every time something goes wrong. Traditional documentation decays. This grows.
| Instead of this | You get this |
|---|---|
| Chat threads that rot | A navigable tree with status, warnings, and ruled-out paths |
| Markdown files nobody updates | Write-time propagation checks — the agent must think about what else changes |
| Agent memory that stores facts | Agent memory that stores reasoning state: decisions, pivots, dead ends, and why |
| Re-explaining context every session | The agent loads the map JIT — knows what was tried, what died, and what's next |
| Skills in a flat directory | Nodes linked to the problems they solve — loading triggered by context, not search |
398 nodes. Every feature, every pivot, every dead end tracked.