AI Agents: Building Autonomous Systems

The Rise of AI Agents

AI agents go beyond single-task AI to systems that can autonomously plan, reason, and execute complex multi-step tasks.

What Makes an Agent?

Key Capabilities

Goal-directed behavior

Environmental interaction

Planning and reasoning

Learning and adaptation

Tool use

Architecture Components

Perception

Planning module

Memory systems

Action execution

Feedback loops

Types of Agents

Reactive Agents

Simple stimulus-response behavior.

Deliberative Agents

Planning and reasoning capabilities.

Hybrid Agents

Combine reactive and deliberative elements.

Multi-Agent Systems

Multiple agents collaborating or competing.

Building Agents

Planning Methods

Chain of thought

Tree of thought

ReAct framework

Plan-and-execute

Tool Integration

API calls

Code execution

Database queries

Web browsing

Memory Systems

Short-term context

Long-term storage

Episodic memory

Semantic memory

Applications

Research assistants

Coding agents

Customer service

Data analysis

Task automation

Challenges

Reliability

Safety and alignment

Error recovery

Resource management

Evaluation

Future Directions

More capable reasoning

Better tool use

Multi-agent collaboration

Improved safety

Conclusion

AI agents represent the next frontier in AI capability, enabling increasingly autonomous systems.