Agentic RAG: Let the Agent Search

Agentic Search. More accurate and efficient results from your AI systems.

The retrieval layer that helps AI systems navigate, read, and verify information inside even the most complex documents

Agentic Resource Discovery: Let agents search

The next evolution of the Agents SDK

OpenAI updates the Agents SDK with native sandbox execution and a model-native harness, helping developers build secure, long-running agents across files and tools.

Using Agents as Tools

Building manager–specialist workflows with the OpenAI Agents SDK The post Using Agents as Tools appeared first on Towards Data Science .

BrowseComp: a benchmark for browsing agents

BrowseComp: a benchmark for browsing agents.

EMBL AI Librarian: Life-Sciences Knowledge Layer for AI Agents

arXiv:2607. 28229v1 Announce Type: cross Abstract: The web is increasingly accessed by AI agents rather than humans.

Research acceleration: The view inside OpenAI

The article discusses how coding agents are transforming AI research within OpenAI. It presents early data on agent usage, experiment velocity, task complexity, and the resulting acceleration of research. The piece highlights the growing role of these agents in speeding up development and experimentation.

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.

Search, Inspect, Fetch: Exploiting Boolean Retrieval for Deep-Research Agents

arXiv:2608. 02751v1 Announce Type: cross Abstract: Existing deep-research agents use a search-visit workflow that retrieves and reads whole pages, without considering the addressable structure that web sources expose through titles, headings, sections, and metadata.

Search, Inspect, Fetch: Exploiting Structure-Aware Boolean Retrieval for Deep-Research Agents

arXiv:2608. 02751v2 Announce Type: replace-cross Abstract: Existing deep-research agents use a Search--Visit workflow that retrieves whole webpages without considering the structure they expose through titles, headings, sections, and metadata.

Turning contracts into searchable data at OpenAI

OpenAI built a system to extract contract data quickly, cutting turnaround times and making it easier for teams to access the details they need.

From Local LLM to Tool-Using Agent

Using Gemma 4, Ollama, OpenAI Agents SDK, and Tavily MCP to build a lightweight research agent The post From Local LLM to Tool-Using Agent appeared first on Towards Data Science .