AI Agent
An autonomous AI system that can plan, reason, use tools, and complete multi-step tasks without human input at each step. Unlike basic LLM calls, agents can browse the web, query databases, send emails, and loop until a goal is met.
73%
of knowledge work tasks partially automatable by AI agents
McKinsey 2024
Expert insight
The difference between an LLM call and an AI agent: one answers a question, the other completes a task end-to-end.
In a real workflow
A support agent reads a new ticket, looks up the order in Shopify with a tool, checks the refund policy, then drafts a reply for a human to approve.
Common mistakes
- Giving an agent write access to systems before its decisions have been reviewed on real cases.
- Letting the agent loop without a step limit, which wastes tokens and can take repeated actions.
Complexity level
Technical term used in production automation systems.
Related terms
Quick facts
73%
of knowledge work tasks partially automatable by AI agents
McKinsey 2024
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n8n vs Lindy vs Relevance AI vs Gumloop (2026): Best AI Agent Builder for Your Business
The four AI agent builders small teams shortlist most, compared on what decides production success: reliability, ease of building, credit-based pricing at volume, self-hosting and data control, with a clear pick by use case.
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AI agents in production are not magic they are structured workflows with an LLM at the core, surrounded by memory, tools, error handling, and human oversight. Here is exactly how we build them.
15 AI Agent Examples That Work in Real Businesses (Not Just Demos)
Most AI agent demos show chatbots answering questions. These 15 examples show agents doing real work: screening candidates, processing documents, qualifying leads, and managing client communications.