Episode Details
EPISODE INFO
- Released
- October 17, 2025
- Duration
- 18m
- Channel
- Anthropic
- Watch on YouTube
- ▶ Open ↗
EPISODE DESCRIPTION
Anthropic’s Alex Albert (Claude Relations) sits down with Erik (Multi-Agent Research and co-author of our blog post, Building Effective Agents) for a discussion on the evolution of agents over the past six months, including tips for building multi-agent systems, common multi-agent patterns, and best practices for using skills, MCP servers, and tools. 00:00 - Introductions 00:35 - Training Claude to tackle agentic tasks 1:30 - Making Claude more autonomous with code 3:20 - Using the Claude Agent SDK to build agents 5:00 - Tips for using Agent Skills 6:40 - The evolution of workflows and agents (workflows of agents) 8:30 - The value of simple agent architectures 9:30 - Building multi-agent systems: orchestrators, subagents, and tool calling 11:40 - Training Claude to use subagents 12:25 - Multi-agent use design patterns: parallelization, MapReduce, and test-time compute 13:20 - Coordinating problem solving with tools and subagents 14:15 - Common agent failure modes 15:00 - Best practices for getting started with building agents (context engineering, MCPs, and tools) 17:15 - The future of agents: coding, computer use, and beyond Read the original blog post: https://www.anthropic.com/engineering/building-effective-agents Learn more about Agent Skills: https://www.anthropic.com/engineering/equipping-agents-for-the-real-world-with-agent-skills
SPEAKERS
Erik
guestMulti-Agent Research team member at Anthropic focused on agentic behavior, multi-agent architectures, and tool-using systems.
Alex Albert
hostLeads Claude Relations at Anthropic and hosts conversations about building and using Claude for agent workflows.
EPISODE SUMMARY
In this episode of Anthropic, featuring Erik and Alex Albert, Building more effective AI agents explores how Anthropic builds, scales, and debugs effective Claude agents Claude’s agent strength comes from training on open-ended, multi-step tasks with tool use and reinforcement learning across environments like coding and search.
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