Claude Agent SDK [Full Workshop] — Thariq Shihipar, Anthropic

AI Engineer · Advanced ·🤖 AI Agents & Automation ·4mo ago
Learn to use Anthropic's Claude Agent SDK (formerly Claude Code SDK) for AI-powered development workflows! https://platform.claude.com/docs/en/agent-sdk/overview https://x.com/trq212 **AI Summary** This workshop by Thariq Shihipar (Anthropic) details the architecture and implementation of the **Claude Agent SDK**. The session moves from high-level theory—defining "agents" as autonomous systems that manage their own context and trajectory—to a live-coding demonstration. Shihipar builds an agent "Harness" from scratch, implementing the core **Agent Loop** (Context Thought Action Observation), integrating the **Bash tool** for general computer use, and demonstrating **Context Engineering** via the file system to maintain state across long tasks. **Timestamps** 00:00 Introduction: Agenda and the "Agent" definition 05:15 The "Harness" concept: Tools, Prompts, and Skills 10:10 Live Coding Setup: Initializing the Agent class and environment 15:45 implementing the "Think" step: Getting the model to reason before acting 25:20 The Agent Loop: connecting `act`, `observe`, and `loop` 33:10 Tool Execution: Handling XML parsing and tool inputs 42:00 The "Bash" Tool: Giving the agent command line access 49:30 Safety & Permissions: "ReadOnly" vs "ReadWrite" file access 58:15 Context Engineering: Using `ls` and `cat` to build dynamic context 01:05:00 The "Monitor": Viewing the agent's thought process in real-time 01:12:45 Handling "Stuck" States: Feedback loops and error correction 01:21:20 Multi-turn Complex Tasks: Building a "Research Agent" demo 01:35:10 Refactoring patterns: "Hooks" and deterministic overrides 01:48:39 Q&A: Reproducibility, helper scripts, and non-determinism 01:50:31 Q&A: Strategies for massive codebases (50M+ lines) 01:52:00 Closing remarks and future SDK roadmap * **Evolution of AI Capabilities:** Shihipar argues we are shifting from **LLM Features** (categorization, single turn) to **Workflows** (structured, multi-step chains like RAG) to **Agents**.
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Chapters (16)

Introduction: Agenda and the "Agent" definition
5:15 The "Harness" concept: Tools, Prompts, and Skills
10:10 Live Coding Setup: Initializing the Agent class and environment
15:45 implementing the "Think" step: Getting the model to reason before acting
25:20 The Agent Loop: connecting `act`, `observe`, and `loop`
33:10 Tool Execution: Handling XML parsing and tool inputs
42:00 The "Bash" Tool: Giving the agent command line access
49:30 Safety & Permissions: "ReadOnly" vs "ReadWrite" file access
58:15 Context Engineering: Using `ls` and `cat` to build dynamic context
1:05:00 The "Monitor": Viewing the agent's thought process in real-time
1:12:45 Handling "Stuck" States: Feedback loops and error correction
1:21:20 Multi-turn Complex Tasks: Building a "Research Agent" demo
1:35:10 Refactoring patterns: "Hooks" and deterministic overrides
1:48:39 Q&A: Reproducibility, helper scripts, and non-determinism
1:50:31 Q&A: Strategies for massive codebases (50M+ lines)
1:52:00 Closing remarks and future SDK roadmap
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