Rethinking Search: Code Generation for Agent Harnesses
TL;DR. A new framework proposes evolving search from monolithic services to programmable primitives, enabling more dynamic and agent-driven information retrieval. - This paradigm shift treats search as code generation, adapting to the demands of modern AI agents. - It moves beyond traditional keyword-based queries to more complex, executable search strategies. - The approach aims to integrate search results directly into the operational logic of AI systems.
- Search is being reimagined as code generation to better serve AI agents.
- This goes beyond conventional search engines, allowing for programmable information gathering.
- The new model integrates search results directly into agent workflows, making them actionable.
Sources
- Rethinking Search as Code Generation — research.perplexity.ai