The sparkle button by the commit field promises to spare you the boring part: it will write the message from your changes itself. The temptation is to accept the generated text without looking and commit: it saves seconds, it looks tidy. But a commit message is not decoration but a record of intent for whoever reads the history a year from now, and autopilot here quietly spoils exactly that.
The mechanics are worth understanding before pressing. First you stage changes in the git panel, then you press the sparkle by the message field; the feature analyzes the staged diff and offers text that you must read and edit before committing. It is available to all paid users without limits and gives the best result on small, focused commits. The key word is offers: here too the last word belongs to the human.
A good message explains intent rather than listing files. "Updated three files in auth" is what the diff already shows; what is valuable is the other thing - why it changed and what is now true: "fixed the token expiry check that was rejecting valid sessions". Generated text on its own tends toward describing the changes; the human's work is to raise it from what was touched to what was done and why.
Hence a technique that begins before the button - at the staging stage. Stage only related changes: one commit, one intent. Keep mechanical formatting, a change in behavior and a schema migration in separate commits rather than dumping them into one. Then the generated message comes out precise too, because what has to be described is one coherent thing, not a jumble.
The generation has an unexpectedly useful role - it works as a probe of the commit's width. If the model cannot briefly and clearly describe the staged diff and produces a vague "various improvements", that is not its weakness but a signal: the commit is too wide and mixes several intents. A vague auto-message is a reason not to touch up the text but to reassemble the stage itself into narrower parts.
Separately, on privacy - and here the exact wording matters. The documentation states verbatim that your code and commit messages remain private: they are not stored and not used to train the models. This is a strong and concrete promise - but it is given precisely for the AI commit messages feature. Extending it automatically to all agents, to the cloud and especially to third-party ACP is a reading error.
Why the boundary of the promise must be held firmly. Different Devin surfaces have different data policies, and third-party ACP agents work entirely under their provider's terms, where privacy and training are governed differently. A promise given for one narrow feature does not carry over to another environment just because the brand is the same. Whoever judges privacy by a line from one page will easily be wrong about the data boundaries on another.
The cost of autopilot is twofold. Accept the generated message without looking, and the project history fills with lines that list files but explain no decisions; half a year later such a log does not help understand why the code became what it is. Carry the privacy promise over to all environments, and you send sensitive code where that guarantee does not hold. The first trouble is slow, the second is one-time and expensive.
You should verify the result with two different questions. The first, to the text: does the message explain the intent so that a colleague understands the reason for the edit without opening the diff? If not, finish it by hand. The second, to the scope: does the staged diff correspond to the one intent the message describes? If the model started speaking in generalities, narrow the stage. And the privacy claim is checked not against the memory of this chapter but against the current page of the feature or environment in question.
It helps to remember why a message is written separately from the diff at all. The diff shows what changed line by line; the message keeps what the lines do not hold - the reason, the context of the decision, the link to a task or a bug. These are two different layers of the project's memory, and they must agree: if the message promises one thing while the diff does another, both lose trust. So you edit not for the beauty of the wording but so that the record of intent does not diverge from the record of changes. A good habit is to keep the subject short and to the point and to move the details and the reason into the body, where they have room.
The typical failures are predictable. Accept the auto-message as is - and "misc changes" stays in the history instead of a reason. Mix formatting, behavior and a migration in one commit - and neither the human nor the model describes it briefly. Decide that it is all private since it says so - and extend one feature's promise to the cloud and ACP. The common sign: the text, the scope and the privacy boundary were all taken on autopilot. Read, narrow and check the source, and the commit tells the truth again.