AI Agent
An AI agent is software that pursues a goal on your behalf: it reads the situation, plans the next step, acts through tools (email, calendars, databases, APIs) and checks the result before continuing, instead of answering one question and stopping.
No jargon, no math
In plain words, what is it?
A chatbot is a brilliant colleague behind glass: you ask, it answers, nothing happens. An agent is the same colleague with house keys and a to-do list. You give it a goal (“prepare the weekly stock report and email it to operations”) and it loops: read the data, plan the steps, call the tools, check what came back, adjust. The loop runs until the goal is done or the agent hits a boundary you set: a spending limit, a missing approval, an action outside its permissions. That is where it stops and asks a human. The difference from classic automation is not speed, it is judgement: the agent handles a messy input it has never seen before, where a rigid script would crash.
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Set the goal. You give the agent a goal and boundaries: which tools it may call, up to what limit.
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Plan. The goal becomes an ordered list of concrete actions.
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Act. Each action runs through a tool: an API call, a query, an email.
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Check. Success feeds the next step; failure triggers a re-plan.
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Stop at boundaries. Over-limit or out-of-permission actions go to a human, and everything is logged.
Terms that live nearby.
Agentic Workflow
An agentic workflow is a business process whose steps are executed by AI agents: they plan the work, call tools, read results and decide the next move, instead of following a fixed script that breaks the first time reality differs.
ReadTool Use
Tool use is the capability of an AI model to do more than write text: it can call external tools, such as searching a database, sending an email or running a calculation, by emitting a structured request that software executes for real.
ReadGuardrails
Guardrails are the checks and limits wrapped around an AI model so its behaviour stays inside your rules: they screen what goes in, constrain what the model can do, and verify what comes out before it reaches a person or a system.
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Want this running in your stack?
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