# M01-L01 — Meet the workbench assistant

**Outcome:** Classify three useful tasks and choose an appropriate verification step.

**Start:** CP00 and basic familiarity with a firmware function.

An assistant can help you understand a function, propose a small edit, or organize a test table. Choose a first task whose result you can inspect. Asking for an explanation of a supplied comparison is a better defined exercise than asking for a complete unknown system. The goal is to make the work reviewable.

A model generates output; an application provides an interface; an agent can use permitted tools to read, execute, or edit. A command shown in chat has not necessarily run. In an agent interface, inspect the action record and execution context as well as the final explanation. [Codex IDE extension](https://learn.chatgpt.com/docs/codex/ide)

For the worked example, use the original `report_state` excerpt in Chapter 1. It returns WARN for an ordinary finite Celsius input at or above 28.0 and OK below it. Ask for an explanation separating code-supported statements, document-dependent statements, and physical claims. Keep the actual response. If access is unavailable, analyze the explicitly illustrative response in the chapter.

The statement about the comparison is supported by the code. The function alone cannot establish how often a sensor is sampled, which board pins are used, or whether the physical reading is accurate. Its parameter name expresses an intended unit; inspect the caller to know what actually arrives. Write a claim, label, supporting line or reference, and next check for every consequential statement.

The core sensor-monitor project uses controlled synthetic input and cross-compilation. Host tests can establish behavior for that input; compilation can establish a build for the selected target. Neither establishes a physical measurement. A useful result is precise about its positive scope: “The boundary cases passed in the host program” is informative without suggesting a board was tested.

The demonstration ends with an evidence worksheet, not a verdict that all AI output is reliable or unreliable. A strong worksheet preserves a useful explanation and rejects only the claims that outrun the evidence.

![The engineer defines acceptance; the model proposes; tools act; compiler, tests, and instruments supply different evidence.](../../../../book/figures/D01.png)

*D01. The engineer defines acceptance; the model proposes; tools act; compiler, tests, and instruments supply different evidence.*

## Practice and completion

Complete the [exercise](exercise.md), then compare your artifact with the separately distributed instructor answer. A lesson acknowledgment records your own progress; it does not certify that a physical test occurred.

## Reading and figures

[Chapter 1](../../../../book/chapters/ch01/chapter.md). Resources: [Original reporting excerpt](../../../../book/chapters/ch01/resources/report-state.cpp). Figure references: SS01-01–03; D01.