Task Management protocol utilizing biometric feedback to optimize developer state.
Deep Focus treats attention as the scarcest resource in software engineering. It pairs a deliberately minimal task protocol with passive biometric signals — heart-rate variability, session cadence, typing rhythm — to learn when you are actually in flow and when you are merely at the keyboard.
The output is not another productivity graph. It is a protective layer: notifications held, tasks sequenced to match your cognitive state, and honest data about the conditions under which your best work happens.
Orders the day's tasks against your measured focus curve — deep work when you are sharp, chores when you are not.
Detects fragmentation early and quietly defers non-urgent interruptions until a natural break.
All biometric processing happens locally. Raw signals never leave the machine.
Anything HealthKit exposes — Apple Watch primarily. Desktop signals (typing cadence, app focus) work without any wearable.
Development updates shared through the journal.
Expense Tracking engine with zero-shot categorization using localized LLMs.