A client asking "did you use AI for this?" rarely means what it sounds like.
Keito, a billing platform built around AI-assisted agency work, put it plainly in a recent post: "Clients demand visibility into whether AI was used and what value it delivered." That's two different questions wearing one sentence.
The first one — did you use it — is rarely what they actually care about. Nobody refuses a chair because a machine cut the wood. What they're really asking, even when they don't phrase it that way, is closer to: can you show me the work happened, and was it worth what I'm paying?
A token count doesn't answer that. A client doesn't know what a token is, and an invoice line that says "4.5 hours" doesn't say whether those hours built the feature or re-read the same three files after a failed attempt.
What answers it is closer to a paper trail: hours that map to commits, commits that map to a shipped feature, on a timeline the client can open without pinging you for a status update. Not a transparency stunt — just evidence that survives a second look.
That's the part already built into Estela, the open-source tool we're building: a read-only panel, one per client, from the hours and cost it reconstructs locally from Claude Code and Codex session logs plus git. The client opens a link instead of asking you for an update.
If you bill clients for work an agent touched, what do you actually show them when they ask?
AI & ML
Source:https://dev.to/jdevleon/what-clients-actually-mean-when-they-ask-did-you-use-ai-for-this-l11
What clients actually mean when they ask "did you use AI for this?"
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