Day 0
Vreko installs locally as a background daemon. Code never leaves your machine. The daemon watches the workspace - not your keystrokes, not your file contents, but the shape of what changes: which files move together, how often they change, and when AI tools are involved in those changes.
Days 1–3: Calibrating
Observations accumulate. Vreko is building a behavioral model of your codebase - not a static snapshot, but a living record of co-change relationships, AI tool attribution, and breakage correlation. Which files, when touched by an AI agent under time pressure, tend to need follow-up fixes within 48 hours? By day three, Vreko knows.
Day 4+: Steady state
Your workspace.json is now populated with real fragility scores, co-change relationships, and AI attribution data. Every session adds to this model. When you invoke an AI coding assistant, it can read workspace.json directly. It knows which files are fragile, which patterns have caused regressions before, and what your team considers a safe edit boundary. The agent's behavior becomes calibrated to your codebase's actual risk profile - not a generic one.
Ongoing
Every session makes the intelligence richer. Vreko does not reset between projects or sessions. The behavioral model persists, deepens, and gets shared with every AI tool that reads workspace.json. The memory survives context windows.