AI Brain Starter

AI Brain Starter

A verification harness around your AI agent. So memory compounds instead of corrupts.

You have a smart assistant that forgets you every morning. This is the harness that gives it a memory: notes on your disk that the assistant reads before answering you, deterministic guards that block bad edits before they land, and a session-end ritual that files what mattered. Whether you write, run a company, or just want context to stop disappearing between conversations, the same surface works.

Microsoft DELEGATE-52 (arxiv.org/abs/2604.15597, April 2026) measured what most operators already feel: frontier LLMs corrupt 25% of professional content over 20 edit interactions. Document size amplifies the failure 5×. The paper concludes the only reliable mitigation is a domain-specific verification harness around the model.

This is one.

Four moving parts.

- Vault as ground truth. Markdown on disk. Decisions, patterns, context. The model reads from the vault, not from chat history.
- Hooks as deterministic guards. Pre-write hooks block bad edits before they land. Em dashes in external prose. Frontmatter without required fields. Calendar events without timezone offsets. Raw git add -A on a 60K-file vault.
- Bi-temporal rule lineage. Every codified rule carries two clocks: when it was written, and when it was last verified. The resolver detects conflicts. Drift detection scans high-edit files weekly for cumulative semantic shift. The closed loop promotes hardened patterns into procedural memory and demotes stale ones.
- Session lifecycle. Each session start loads context. Each session end cascades decisions, insights, and to-dos to the right files. Nothing stays trapped in a chat transcript.

Free to install. Free to run. Your Claude subscription is the inference.…