# Using agents

> Delegating work to an agent and checking what comes back.

Page: https://schubergphilis.github.io/ai-training/using-agents/
License: CC BY-SA 4.0, https://creativecommons.org/licenses/by-sa/4.0/

This course teaches you to hand a task to an agent and decide how much it may do on its own, then check what comes back against what you asked for.

## Working with an assistant

- [Finding information with an assistant](https://schubergphilis.github.io/ai-training/using-agents/finding-information/): Ask an assistant what a newcomer must know from a text you supply, with a quote behind each claim, and see why the same question from memory gives a confident wrong answer.
- [Working from your own files and images](https://schubergphilis.github.io/ai-training/using-agents/working-from-files/): Hand an assistant a screenshot of a table instead of describing it, get the rows back for a spreadsheet, and count the cells that came back wrong. Then compare two versions of a contract with a brief that says which differences matter.
- [Thinking a problem through with an assistant](https://schubergphilis.github.io/ai-training/using-agents/thought-partner/): Ask an assistant which of two job offers to take and get your own framing back as advice, then brief it to argue against your lean and list what you left out, so the thinking is yours.
- [Drafting a text and asking for critique](https://schubergphilis.github.io/ai-training/using-agents/drafting-and-critique/): Brief a chat assistant for a short email and check every fact in the draft, then ask for critique of it as a colleague's text against criteria you wrote first, and get problems in place of praise.

## Delegating to an agent

- [Delegating a task to an agent](https://schubergphilis.github.io/ai-training/using-agents/delegating/): Write a brief, choose how much the agent may do on its own, and review the result against what you asked for.
- [How much the agent may do before it asks](https://schubergphilis.github.io/ai-training/using-agents/choosing-autonomy/): Choose draft only, ask before anything that can't be undone, or run to completion by what a wrong step costs, add check-ins on a first run, and write the setting as one sentence.
- [Changing the brief while the agent works](https://schubergphilis.github.io/ai-training/using-agents/adjusting-the-brief/): Run a brief with a gap in it, answer the agent's question in the brief instead of the chat, state a changed limit as a replacement, and stop a run whose first result shows the goal was wrong.

## Decomposing work

- [Breaking a task into pieces an agent can finish](https://schubergphilis.github.io/ai-training/using-agents/breaking-work-into-pieces/): Hand a three-part report to an agent as one prompt and see it blend. Then split the task into pieces that each have an input, an output and a check, and run the first one.
- [Delegating in rounds](https://schubergphilis.github.io/ai-training/using-agents/delegating-in-rounds/): Delegate one piece of a split report, check the result line by line, change the brief with what the miss showed, and carry the change into the next piece, with a two-line log per round.
- [When to stop delegating and do it yourself](https://schubergphilis.github.io/ai-training/using-agents/when-to-stop/): Read three round logs, name the three signs that another round costs more than doing the step yourself, and see why taking a step back says nothing about the tool or about you.

## Choosing models and tools

- [Chat, agent or automation](https://schubergphilis.github.io/ai-training/using-agents/chat-agent-or-automation/): Pick chat, agent or automation for a task by its worst case, match the checks to the level, and write the rule that would move the pick up or back.
- [Trying two models on the same task](https://schubergphilis.github.io/ai-training/using-agents/trying-two-models/): Run one reformatting task, one classification task and one ambiguous request on a small and a large model, time each answer, and read a six-cell table to see where the large model earns its price.
- [The steps that stay human](https://schubergphilis.github.io/ai-training/using-agents/steps-that-stay-human/): Walk an eight-step hiring process twice, once for what an agent could do and once for what stays with a person, and learn the three reasons a step stays human and why the list is decided early.
- [Reasoning across tool levels](https://schubergphilis.github.io/ai-training/using-agents/reasoning-across-tool-levels/): Read two before-and-after pairs, a summary and a filed folder, and name the check that stopped working when a tool took over the level and the check that replaces it one level up.