Good Architecture Deletes the Signals Your Agent Depends On

Stop Giving Your AI Agent a Search Box and Start Giving It Typed Tools, Hard Bounds, and a Gate It Cannot Talk Past

The article explores the effects of removing a search box from an AI agent and instead providing it with typed tools, hard bounds, and a gate that it cannot bypass. It examines how the agent navigates a knowledge graph within strict limits and discusses findings from four models and one incorrect prediction regarding the value of this approach.

Can an Apartment Search Agent Call the Model Fewer Times and Still Find Good Matches?

The article examines whether an apartment search agent can reduce the number of times it calls a predictive model while still identifying suitable matches. The author conducted 2,500 listing checks using Weights & Biases Weave, systematically eliminating unnecessary model computations, and evaluated each iteration against consistent reference answers.

Agentic RAG: Let the Agent Search

A minimal OpenAI Agents SDK implementation where retrieval becomes a search-read-decide loop The post Agentic RAG: Let the Agent Search appeared first on Towards Data Science .

RAG Isn't an Agent — I Built the Layer Between Retrieval and Action

The article explains that Retrieval-Augmented Generation (RAG) is a retrieval system, while agents are responsible for action. The author built a distinct layer that explicitly connects retrieval to action, and tested this setup across nine tasks alongside standalone RAG and agent systems.

The Protocol That Cleaned Up Our Agent Architecture

A detailed look at MCP that turned my scattered tool definitions into a stable, discoverable server The post The Protocol That Cleaned Up Our Agent Architecture appeared first on Towards Data Science .

Open-source DeepResearch – Freeing our search agents