Path
Agent system construction
The design and implementation of autonomous AI Agents, covering architectural patterns, tool invocation, multi-Agent collaboration and memory management.
Topic
Agent system construction
The design and implementation of autonomous AI Agents, covering architectural patterns, tool invocation, multi-Agent collaboration and memory management.
Agent system construction focuses on how to design and implement AI agents that can make decisions autonomously, call tools, and complete complex tasks.
architectural patterns
- ReAct (Reasoning + Acting): Alternate reasoning and action, suitable for multi-step tasks
- Plan-and-Solve: Plan first and then execute, suitable for scenarios that require global strategies
- Reflection: Self-reflection and correction to improve the quality of task completion
Engineering Challenges
- Tool Design: How to design tool interfaces that are easy for Agents to understand and use
- Error Recovery: Agent’s ability to self-heal when an error occurs during execution
- Cost Control: Token consumption optimization for long-chain Agent calls
- Observability: Track the Agent’s decision-making process and intermediate states
Index
Knowledge Index
Core subtopics and learning directions for this topic.
ReAct modePlan-and-SolveTool call designMulti-Agent collaborationMemory and context management
Reading paths
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Resources
Resources
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