Building Intelligent AI Agents

AI agents are autonomous systems that can perceive their environment, make decisions, and take actions to achieve specific goals. Let's explore how to build them effectively.

What Makes an AI Agent?

An effective AI agent has several key components:

Core Capabilities

1. Perception: Understanding inputs from the environment
2. Reasoning: Processing information to make decisions
3. Action: Executing tasks in the real or digital world
4. Learning: Improving performance over time

Architecture Patterns

The ReAct Pattern

Combine reasoning and acting in an iterative loop:

async function reactAgent(task: string) {
  let thought = await reason(task);
  let action = await planAction(thought);
  let observation = await execute(action);
  
  while (!isComplete(observation)) {
    thought = await reason({ task, observation });
    action = await planAction(thought);
    observation = await execute(action);
  }
  
  return observation;
}

Tool-Using Agents

Agents become more powerful when they can use external tools:

const tools = {
  calculator: (expr: string) => eval(expr),
  search: (query: string) => webSearch(query),
  database: (query: string) => executeSQL(query)
};

async function agentWithTools(prompt: string) {
  const response = await llm.generate(prompt, { tools });
  return response;
}

Memory Systems

Agents need memory to maintain context:

• Short-term Memory: Recent conversation history
• Long-term Memory: Persistent knowledge and experiences
• Working Memory: Current task state

Implementing Memory

class AgentMemory {
  private shortTerm: Message[] = [];
  private longTerm: VectorStore;
  
  async remember(content: string) {
    this.shortTerm.push({ role: "user", content });
    await this.longTerm.store(content);
  }
  
  async recall(query: string) {
    return await this.longTerm.search(query, k=5);
  }
}

Planning and Execution

Effective agents break down complex tasks:

1. Task Decomposition: Break goals into subtasks
2. Sequential Planning: Order subtasks logically
3. Parallel Execution: Run independent tasks concurrently
4. Error Recovery: Handle failures gracefully

The best AI agents are those that know their limitations and ask for help when needed.

Evaluation and Improvement

Measure agent performance across dimensions:

Real-World Applications

AI agents are being deployed for:

Building effective AI agents requires careful design, robust error handling, and continuous monitoring. Start simple, iterate quickly, and always prioritize safety and reliability.