AMP Documentation
Add motivation intelligence to your AI agent in one API call.
What is AMP?
The Adaptive Motivation Protocol (AMP) is a lightweight API that gives your AI agents the ability to understand and adapt to individual user motivation patterns. Instead of building complex personalisation logic yourself, AMP learns what works for each user and provides structured context for every interaction.
Why AMP?
Building effective AI agents requires understanding not just what users want, but how they want to receive it. Traditional approaches require:
- Complex prompt engineering for different user types
- Manual tracking of user preferences and behaviour
- Custom A/B testing infrastructure
- Constant iteration on communication styles
AMP replaces all of this with two simple API calls:
// 1. Get context before responding
const context = await amp.getContext({
userId: user.id,
task: userQuery,
});
// 2. Report the outcome
await amp.reportOutcome({
requestId: context.requestId,
started: true,
completed: true,
});Key Benefits
80% Less Code
Replace hundreds of lines of personalisation logic with one API call.
34% Better Engagement
AMP learns what actually drives each user to complete tasks.
Automatic Learning
No manual tuning required. AMP improves with every interaction.
Framework Agnostic
Works with any AI agent framework or custom implementation.
How It Works
AMP uses behavioural science and machine learning to build motivation profiles for each user:
- Context Request: Before your agent responds, call
getContext()with the user ID and task description. - Structured Guidance: AMP returns communication style recommendations, complexity preferences, and framing suggestions.
- Adapted Response: Your agent uses this context to personalise its response.
- Outcome Reporting: Report whether the user started, completed, or abandoned the task.
- Continuous Learning: AMP updates the user's profile, improving future recommendations.
Next Steps
Ready to get started? Follow our Quick Start Guide to integrate AMP in 5 minutes.