AI Agent
An AI agent is a system that uses an LLM to autonomously plan, make decisions, use tools, and take actions to complete a goal.
What Is an AI Agent?
An AI agent is an AI system that can autonomously plan, decide, and act to complete a goal - not just respond to a single question. Built on a large language model, an agent is given tools (web search, code execution, file access, API calls) and a task, then works through a sequence of steps to accomplish it without requiring human input at each decision point.
The simplest agents follow a loop: reason about what to do → take an action → observe the result → reason again. This continues until the task is complete or a stopping condition is met.
Agent vs Chatbot
| Chatbot | AI Agent | |
|---|---|---|
| Input/Output | One message in, one response out | Multi-step task execution |
| Memory | Usually none (or short conversation) | Maintains state across steps |
| Tools | Rarely | Core capability |
| Autonomy | None - waits for user | Can act independently |
| Examples | FAQ bot, customer support | Code assistant, research agent |
How Agents Are Built
A minimal AI agent needs:
- An LLM with good instruction-following and reasoning (GPT-4o, Claude 3.5 Sonnet)
- A set of tools the model can call (defined as JSON schemas)
- A loop that feeds tool results back into the model until it signals completion
- A prompt that explains the task and available tools
Frameworks like LangChain, LlamaIndex, and Anthropic’s agent SDK make this easier, but many production agents are built with minimal frameworks to reduce complexity.
Real-World Agent Use Cases
- Coding agents (Claude Code, Devin): read a codebase, implement features, run tests, fix failures
- Research agents: search the web, aggregate information, write reports
- Customer support agents: access CRM data, look up orders, escalate to humans when needed
- Data agents: query databases, generate visualizations, summarize findings
- Workflow agents: connect to Slack, email, and calendars to execute business processes
Key Takeaway
AI agents represent the shift from AI as a question-answering tool to AI as a task-executing one. For startups, agents unlock automation of complex, multi-step knowledge work that previously required human judgment. The technology is powerful but requires careful product design: constrain the action space, validate outputs, and keep humans involved for high-stakes irreversible actions.
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