Agentic data science with the Data Agent Kit
cloud.google.com·7h ago
AI Research
arXiv CS.AI·Aug 28·5 min read
A Contract-Centered Architecture for Scalable and Manageable Agentic Runtimes
TL;DR
A contract-centered architecture for enterprise AI deployment introduces four responsibility objects to enhance scalability and manageability. The key outcome is a falsifiable hypothesis on capability-capacity separability, guiding future AI runtime designs.
✦ Why It Matters
Consider adopting a contract-centered architecture to improve your AI deployment strategy today.
Key Takeaways
- Implement a contract-centered architecture for AI deployment.
- Define clear responsibility objects to enhance team coordination.
- Test capability changes using the proposed randomized crossover experiment.
- Monitor compliance with the falsifiable hypothesis for better outcomes.
How It Works
The architecture introduces four responsibility objects that serve as contracts among teams: Skill for capabilities, Harness for runtime management, Scaffold for execution boundaries, and a data substrate for governance. This structure allows for modular changes in capabilities while maintaining operational integrity, as defined by the hypothesis P1.