Function Calling / Tool Use, explained
Function calling (also called tool use) is a capability that allows an AI model to trigger predefined actions — like running a database query, calling an API, or searching the web — rather than only producing text.
A language model on its own can only produce text. Function calling changes that by letting developers define a set of tools the model can invoke. When answering a question, the model might decide it needs to check live stock prices, look up a customer record, or send a calendar invite — so instead of making something up, it outputs a structured call to the appropriate tool, gets the result back, and incorporates it into its response.
This is what separates a basic chatbot from an AI agent. An agent with tool use can take sequences of real actions: search for information, check results, make decisions, update records. The model is still producing language output, but some of that output is structured instructions to external systems rather than prose for a human to read.
From a practical standpoint, function calling is why products like AI assistants can book meetings, pull CRM records mid-conversation, or query live data. The AI developer defines what tools are available and what each one does; the model decides when and how to use them. Keeping tool definitions clear and narrow is one of the keys to reliable AI agent behavior.
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Wield's AI at Work: Business track covers this hands-on, in plain English, with real examples and a copy-paste prompt to try it yourself.
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