TL;DR: An AI agent is essentially a new type of control structure that combines a large language model with tools, enabling software to understand plain English instructions and execute the appropriate code automatically.
The term “AI agent” has become ubiquitous in technology discussions, yet its meaning often remains frustratingly vague. In a concise explanation from Microsoft Developer, Seth Juarez cuts through the noise to offer a practical definition that business leaders can actually use.
The Core Concept
At its foundation, an AI agent comprises three essential components:
- A large language model — the intelligence that understands natural language
- A prompt — the instructions and context that guide behaviour
- A collection of tools — the actions the agent can take
What makes this combination powerful is the ability to transform conversational requests into actual code execution. Consider asking “What’s the weather like today?” — an AI agent recognises this as a request that should trigger a specific function call to retrieve weather data.
Why This Matters for UK SMEs
For small and medium-sized enterprises, AI agents represent a fundamental shift in how software can be built and deployed. Rather than requiring users to navigate complex interfaces or learn specific commands, applications can respond to natural language instructions.
Practical implications include:
- Reduced training costs — Staff can interact with systems using familiar language
- Faster automation — Repetitive tasks can be delegated to agents without custom development
- Scalable solutions — Agents can orchestrate multiple tools and even other agents
The Scalability Factor
Juarez highlights an important aspect: AI agents can scale. The tools available to an agent might include other agents, remote API calls, or complex function chains. This creates a hierarchical structure where simple requests can trigger sophisticated, multi-step workflows—all initiated by a plain English instruction.
Getting Started
For businesses exploring AI agents, the key insight is this: start with clear use cases where natural language interaction would genuinely improve efficiency. Customer service enquiries, data retrieval tasks, and document processing are common starting points.
The technology is maturing rapidly, with major platforms from Microsoft, Google, and others making agent development increasingly accessible. The question for UK SMEs is not whether to explore AI agents, but which processes would benefit most from this new paradigm.
Watch the full explanation from Microsoft Developer embedded above, or view on YouTube.