Momentum is an agentic learning companion designed to help self-directed developers resume progress when motivation drops or learning is postponed.
The system is intentionally simple and bounded.
Momentum does not generate curriculum, plans, or long-term goals.
Instead, it:
- operates on a fixed learning path defined by the developer
- uses deterministic rules to detect inactivity or repeated postponement
- delegates the choice of the next small action to an AI agent
The purpose of the AI is to make continuation easier than quitting.
The AI agent:
- does not decide what to learn
- does not generate new learning steps
- does not optimize for speed or completion
The AI only:
- selects one task from a bounded task template library
- adapts its scope based on user behavior
- phrases the task in a low-pressure, human-friendly way
All curriculum structure, rules, and constraints are deterministic.
- The user follows a predefined learning path (e.g., Android / Jetpack Compose)
- The system tracks completion, postponement, and inactivity
- Rule-based logic selects an intervention strategy
- The AI agent selects and instantiates one minimal next action
- The user either completes or postpones the action
Only one task is presented at any time.
- Small steps beat perfect plans
- Restarting matters more than speed
- Scope reduction is preferable to pressure
- AI judgment is bounded and explainable
Momentum does not aim to:
- replace structured courses
- act as a general productivity tool
- monitor external activity (e.g., GitHub)
- provide motivational coaching or reminders
The project is evaluated using Comet’s Opik, focusing on:
- appropriateness of selected tasks
- quality of scope adaptation
- alignment between strategy and action
Completion rates are not the primary success metric.
This README is intentionally concise to serve as ground truth for both developers and AI-assisted tools.