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technologyreview.com·3h ago
AI Research
arXiv CS.AI·Jun 12·5 min read
Fantastic Scientific Agents and How to Build Them: AgentBuild for Rietveld Refinement
TL;DR
As scientific workflows transition to using large language model (LLM)-based agents, traditional methods can overshadow scientists' expertise. AgentBuild was developed to create scientific agents based on a contract authored by the scientist, which includes a rubric and external knowledge.
✦ Why It Matters
Engineers can leverage AgentBuild to create adaptable scientific agents that maintain alignment with researchers' goals.
Key Takeaways
- Utilize AgentBuild to define contracts for agent construction.
- Implement structured rubrics to enhance reproducibility in research.
- Leverage meta-optimizers for efficient agent editing within boundaries.
- Adapt existing agents easily as foundational models evolve.
How It Works
AgentBuild allows scientists to create agents by defining a contract that includes a rubric for evaluation, a curriculum for difficulty grading, and a curated knowledge base. This structured approach enables a meta-optimizer to edit the agent's code within specified limits, ensuring that the agent's development is guided by the scientist's criteria rather than solely by automated processes.