AI agents are autonomous systems that perceive their environment, reason about goals, and take actions to achieve them. They represent the next evolution beyond chatbots — from reactive Q&A to proactive task completion.
From Chatbots to Agents
| Capability | Chatbot | Agent | |-----------|---------|-------| | Input | User messages | Environment + user messages | | Processing | Single LLM call | Multi-step reasoning | | Actions | Generate text | Call tools, write code, browse web | | State | Conversation history | Persistent memory + task state | | Autonomy | Responds to prompts | Plans and executes independently | | Error handling | Returns best guess | Retries, adapts, seeks help |
The Agent Loop
At its core, every agent follows this loop:
``` Observe → Think → Plan → Act → Observe result → Repeat until done ```
- Observe: Receive input from the user or environment
- Think: Analyze the situation and available information
- Plan: Decide what action(s) to take next
- Act: Execute the chosen action (tool call, code execution, etc.)
- Observe result: Check the outcome of the action
- Repeat: Continue until the task is complete or the agent needs help
Types of AI Agents
ReAct agents: Interleave reasoning and acting. The most common pattern. The LLM thinks out loud, decides on an action, executes it, then reasons about the result.
Plan-and-execute agents: Create a full plan upfront, then execute steps sequentially. Better for complex multi-step tasks where the overall strategy matters.
Reflexion agents: After completing a task, reflect on what went well and what didn't. Use insights to improve future performance.
Tool-use agents: Specialized in calling external APIs and tools based on user requests. The LLM acts as an intelligent router.
Real-World Agent Examples
- Devin (Cognition): Autonomous software engineer that plans, writes, and debugs code
- AutoGPT: General-purpose agent that breaks down goals into tasks
- Operator (OpenAI): Browser-based agent that navigates websites to complete tasks
- GitHub Copilot Workspace: Plans and implements code changes from issue descriptions
- Replit Agent: Builds applications from natural language descriptions