Most of the vocabulary around agentic AI describes simple ideas. Here are the terms worth knowing, defined the way we use them in the room.
Agent
A piece of AI given a goal and the means to work towards it - rather than a single question and a single answer. An agent can take several steps, check its own progress and use tools along the way. The word sounds grander than the reality: a well-built agent is usually narrow, doing one job dependably.
Agentic workflow
Several narrow AI steps connected so they hand off to each other: one gathers, one drafts, one checks. The workflow is the unit that does useful work - most of the value people attribute to “agents” comes from a well-shaped workflow, not from any single clever step.
Orchestration
Deciding how the steps connect: what runs first, what each step passes to the next, and where a human sits. Orchestration is the skill that separates using AI from building with it - it is closer to delegation than to programming.
Prompt
The instruction you give a model. Prompting well matters, but it is a single-step skill; the shift that changes your working week is going from writing one good prompt to orchestrating several narrow ones.
Context
Everything the model can see when it works: your instructions, the documents you give it, the conversation so far. Most disappointing AI output is a context problem, not an intelligence problem - the model was never shown what good looks like.
Second brain
A structured, maintained store of your own context - how you write, what good looks like, what your business knows - kept where your AI tools can draw on it, so you stop re-explaining yourself in every conversation. It is the fix for context being the bottleneck: build the supply once instead of retyping it each time. Building one from your own material is a day’s work - we run a bootcamp for exactly that.
Tool use
An agent calling something outside itself - searching the web, reading a file, updating a spreadsheet. Tool use is what turns a text generator into something that can act on your systems rather than just describe them.
Pipeline
Another word for a workflow, borrowed from engineering: work flowing through stages in order. If you can sketch your task as three boxes with arrows, you have designed a pipeline.
Scout, drafter, reviewer
The shape we teach first, because it fits an enormous amount of knowledge work: a step that gathers the raw material, a step that produces a first version, and a step that checks it against a stated standard before a human sees it.
Human in the loop
The deliberate decision to keep a person at the point of judgement - approving, correcting, deciding - while the machine handles the assembly around them. Good agentic design is mostly about placing this point well.
Model
The underlying AI - ChatGPT, Claude, Gemini and their peers. For business use the differences matter less than people expect; the shape of your workflow matters more than which model runs it.
MCP (Model Context Protocol)
A standard that lets AI tools connect to your systems - calendars, files, databases - in a common way, so an agent can reach the things your work actually lives in. You do not need to know how it works; you will increasingly benefit from tools that use it.
No-code
Building all of the above through plain-language instructions and existing tools, without programming. The entire Oxford Agentic Bootcamp runs this way: the constraint is clear thinking about your task, not code.