Agentic Behavior Engineering: A Design-by-Contract Methodology for Enterprise AI Agents
Story 15, from arXiv
This paper introduces ABE, a methodology for managing AI agent behavior in enterprise settings by treating observable behavior as the primary engineering artifact, rather than the model or prompt.
Key points
- ABE addresses the challenge of maintaining AI agents by focusing on observable behavior rather than model or prompt changes.
- It adapts Design by Contract to non-deterministic systems, using stable rule identifiers to define what agents must and must not do.
- A lightweight scenario library turns each rule into concrete situations for testing and verification.
- Engineering artifacts like tests and policies reference the contract in one direction, allowing independent evolution of specification and implementation.
- The method organizes work into five responsibilities: Specify, Ground, Control, Verify, and Observe.
- ABE gates releases on per-scenario reliability rather than aggregate accuracy and routes findings to the correct asset for change.
Why it matters
Software engineers working with AI agents face challenges in maintaining and verifying behavior due to non-determinism and external changes. ABE offers a structured approach to manage these complexities, improving reliability and traceability in enterprise AI systems.
Counterpoint
The methodology is theoretical and requires implementation in real-world systems to validate its effectiveness in practice.
Sources
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