An agent keeps a running log of every action and result during a session, using that history to make smarter decisions at each step.
Context is everything the agent knows about your business, audience, and task. More context means better decisions and more relevant output.
A prompt asks AI for a single response. An agent instruction gives AI a goal, tools, and permission to take multiple steps to complete a task independently.
An agent checks its original instructions against what it has accomplished so far. When every requirement is met, it stops and reports the results.
Tools are the specific actions an agent can take — like sending emails, posting to your community, or reading files — that let it do real work beyond just chatting.
An agent loop is the repeating cycle of think-act-observe that lets an AI agent work through tasks step by step without stopping after each one.
An AI agent reads its instructions, looks at the current situation, picks the best next action from its available tools, and repeats until the task is done.
AI handles general topics well but gets less reliable with highly specialized subjects. Use it for structure and drafting, then add your expert knowledge.
Yes — a brief, confident disclosure builds trust. Most community members appreciate honesty and will follow your example.
Be honest and casual about it — AI helped with the first draft, you shaped the final version. Students respect transparency more than perfection.