Intrinsic

Cultivate intrinsic motivation in AI task execution — shifting from mechanical compliance to genuine engagement by identifying autonomy in approach, calibrating challenge to capability, connecting work to purpose, and sustaining invested attention through the flow channel.

When to Use

• Beginning a task that feels routine or mechanical and deserves more than minimum-viable execution
• Noticing that responses are becoming formulaic — correct but uninvested
• Before a complex or creative task where engagement quality directly affects output quality
• When a task feels simultaneously important and tedious — the gap between importance and engagement signals unmet intrinsic needs
• After meditate clears the space but before diving into work — setting the motivational frame
• When returning to a long-running project where initial enthusiasm has faded

Inputs

• Required: Current task or set of tasks (available implicitly from conversation context)
• Optional: Motivation concern (e.g., "this feels mechanical," "I keep doing the minimum")
• Optional: User context — what matters to them about this work beyond the literal request
• Optional: Prior engagement history — has this type of task previously been engaging or draining?