AI agent
An AI system that selects its next steps within defined limits and uses tool results to guide further work.
What is an AI agent?
An AI agent works toward a goal by having a model select next steps during the process and take feedback from its environment into account. It may use available tools, such as search or a query in a business system. The application defines its scope for decisions. Usage of the term varies, so for a specific proposal you should ask which actions the system can actually choose, what access rights apply, and what conditions govern completion or handover.
In a fictional service case, an agent is to prepare an answer to a customer's technical question. Depending on the available information, it may search approved manuals or ask for a missing equipment detail. Search access gives it no authority to close the case or order spare parts. The team plans checks involving incomplete information, unsuccessful searches and conflicting matches. A useful handover identifies open questions and sources already checked. The process assesses completion against the results; a persuasively worded answer alone is insufficient.
Sources
Related terms
- Agentic workflowA process combining AI-assisted decisions and tool actions, with fixed checks and variable paths through the work.
- Human-in-the-loopHuman-in-the-loop actively involves people in an automated process. Useful review requires understandable information and ways to intervene.
- Function callingA language model requests a described function with structured arguments; the connected application executes it.
- LLM evaluationLLM evaluation tests model outputs against defined tasks and criteria. One good example does not establish overall quality.
- AI guardrailsGuardrails constrain and check AI application behaviour. Model instructions and technical enforcement perform different tasks.
- Prompt injectionPrompt injection attempts to redirect an AI application through inserted instructions. Retrieved documents can contain them too.
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