Anatomy of an Agent
Learn the core components that make up an AI agent and how they work together
Your Progress
0 / 5 completedInteractive Demo
Build your own agent by selecting components and watch it execute a task in real-time.
Agent Configuration Builder
🧠Reasoning Engine
💾Memory System
🔧Available Tools
🔄Control Loop Pattern
Understanding Component Trade-offs
Reasoning Engine Impact
- GPT-4: 95% accuracy, $0.03/1K tokens, 2-3s latency
- GPT-3.5: 75% accuracy, $0.001/1K tokens, 500ms latency
- Trade-off: Quality vs Cost vs Speed
Memory System Impact
- No Memory: Fast, cheap, but forgets everything
- Short-term: Remembers conversation, limited by context window
- Long-term: Persistent knowledge, +$0.01/query, +500ms
Tool Configuration Impact
- Few tools (1-5): Agent focuses, less confusion
- Many tools (10+): More capable but slower decisions
- Trade-off: Versatility vs Decision Quality
Control Loop Impact
- ReAct: Flexible, adapts to failures, most common
- Plan-Execute: Efficient for predictable tasks, no replanning
- Reflexion: Best for error-prone tasks, slower (3x iterations)
💡Component Selection Guide
For simple Q&A bots:
GPT-3.5 + No Memory + Search tool + ReAct
For customer support:
GPT-4 + Long-term memory + Email/Search tools + ReAct
For code generation:
GPT-4 + Short-term + Code exec/File tools + Reflexion
For data processing:
Claude 3.5 + No memory + Calculator/API tools + Plan-Execute