Getting Started with AI Agents

AI agents are transforming how we interact with technology. In this guide, I'll show you how to build your first intelligent agent.

What is an AI Agent?

An AI agent is a system that can:

Perceive its environment
Make decisions autonomously
Take actions to achieve goals
Learn and adapt over time

Core Components

1. LLM Foundation

Choose your language model:

OpenAI GPT-4
Anthropic Claude
AWS Bedrock
Open-source alternatives

2. Tools & Actions

Agents need tools to interact with the world:

def search_web(query: str) -> str:
    # Tool implementation
    pass

def send_email(to: str, subject: str, body: str) -> bool:
    # Tool implementation
    pass

3. Memory Systems

Short-term: Conversation context
Long-term: Vector databases (Pinecone, Weaviate)
Working memory: Current task state

4. Planning & Reasoning

Implement reasoning loops:

ReAct (Reasoning + Acting)
Chain-of-Thought
Tree of Thoughts

Building Your First Agent

Here's a simple example using LangChain:

from langchain.agents import initialize_agent, Tool
from langchain.chat_models import ChatOpenAI

llm = ChatOpenAI(temperature=0)

tools = [
    Tool(
        name="Search",
        func=search_web,
        description="Search the web for information"
    ),
]

agent = initialize_agent(
    tools,
    llm,
    agent="zero-shot-react-description"
)

result = agent.run("What's the weather in Tokyo?")

Best Practices

Start Simple - Build incrementally
Test Thoroughly - Agents can be unpredictable
Add Guardrails - Implement safety checks
Monitor Performance - Track costs and quality
Iterate Quickly - Learn from failures

Multi-Agent Systems

Scale your solution with multiple specialized agents:

Research agent
Writing agent
Code agent
QA agent

Resources

Want to dive deeper? Check out my AI Agents 101 interactive platform for hands-on learning.

Next Steps

In the next article, we'll explore:

Advanced agent architectures
Model Context Protocol (MCP)
Production deployment strategies

Stay tuned!

Questions? Reach out on Twitter or GitHub.

Getting Started with AI Agents: A Practical Guide