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AI Agent System Design
Designing autonomous language-model agents: tools, memory, multi-agent, guardrails, and evaluation. · 29 lessons. Read them top to bottom and tick each as you go.
Lessons
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- The Agent Design Interview Playbook
- LLM Internals for Agent Builders
- Agent Foundations
- Agent Design Patterns
- Building an Evaluator-Optimizer Loop
- Tools and MCP
- Memory and Context Management
- RAG for Agents
- Multi-Agent Systems
- Reliability and Guardrails
- Agent Evaluation
- Production and Cost
- Scenario Debugging
- Rapid-Fire Q&A
- Code Lab
- Thinking Models and the Token Budget
- Python Concurrency and Async for Interviews
- LLM Inference Performance
- Computer-Use Agent
- How Claude Code Works
- Form-Filling Agent
- How Cursor Works
- How Antigravity Works
- Multi-Agent Research System
- Harness and Loop Engineering
- Autonomous Agent
- Customer Support Agent
- SQL / Analytics Agent
- Document Processing Agent