Google Backs New Spec to Standardize How AI Agents Discover Tools and APIs

Google and industry partners have announced an Agentic Resource Discovery Specification aimed at standardizing how AI agents find and interact with tools, APIs, and data sources. The initiative addresses a key bottleneck in agent orchestration, where agents often struggle to identify external resources without explicit manual programming. By establishing a common framework, the spec seeks to enable interoperability across agent platforms and foster a broader ecosystem for agent development. Separately, a practical guide published on DEV Community demonstrates how to implement Retrieval Augmented Generation (RAG) in a Laravel application using embeddings and pgvector, extending RAG beyond Python-centric frameworks. The Laravel approach stores document embeddings in PostgreSQL and performs similarity searches to supply relevant context to large language models, reducing hallucinations in domain-specific chatbots.