Nov 10, 2025

Build Hour: Agent RFT

Will Hang and Theophile Sautory from OpenAI provide a deep dive into Agent RFT, a powerful method for fine-tuning large language models to become more effective, tool-using agents. They explain how Agent RFT enables models to learn directly from their interactions with custom tools and reward signals, leading to significant improvements in performance, latency, and efficiency on specialized tasks. The session includes a detailed code demo, best practices, and success stories from companies like Cognition, Ambience, and Rogo.

Oct 27, 2025

How Claude is transforming financial services

Anthropic's team discusses Claude for Financial Services, an agentic AI solution designed to transform financial workflows. They explore how Claude's core strengths in coding and reasoning are applied to tasks like real-time data analysis and generating investor-ready reports, highlighting practical customer examples and future developments.

Oct 09, 2025

Building with MCP and the Claude API

A discussion with Anthropic engineers Alex Albert, John Welsh, and Michael Cohen about the Model Context Protocol (MCP). They cover its origins as an open standard, best practices for tool design and prompt engineering, and the future of the ecosystem where high-quality MCP servers will become a key competitive advantage.

Oct 02, 2025

Building the future of agents with Claude

Experts from Anthropic discuss the evolution of the Claude Developer Platform, the philosophy of "unhobbling" models with tools rather than restrictive scaffolding, and the future of building sophisticated, autonomous AI agents with features like the Claude Agent SDK, advanced context management, and persistent memory.

Sep 17, 2025

Beyond Prompting: The Emerging Discipline of Context Engineering Reading Group

This summary covers a deep dive into the paper "A Survey of Context Engineering for Large Language Models". The discussion reframes the conversation from simple prompt engineering to a more systematic approach of building information environments for LLMs. It explores the foundational components of context engineering—generation, processing, and management—and their application in advanced systems like Retrieval-Augmented Generation (RAG), memory, tool use, and multi-agent systems.

Aug 25, 2025

Deploying Executable Agent Workflows

Gal Peretz introduces CodeAct, a paradigm where LLMs generate and execute Python code for tool interaction, offering a more flexible and powerful alternative to traditional JSON-based function calling for building complex, production-ready AI agents.