Example: Irina, a lawyer — one knot, not the whole workbook
Irina is a composite character; the situation is ordinary. This is a short example: not a full pass through a workbook but one painful knot — checking, and cognitive debt. Checked: 2026-09.
The full passes are Marina the marketer and Pyotr the accountant. This one is different: what to do when AI is already built into the work, saves real hours, and is dangerous for exactly that reason.
Irina is 36 and handles contracts in-house. She uses AI every day: reviewing incoming contracts, drafting replies, searching case law. The saving is real — an hour per contract instead of three. So is the problem: she once cited, in a written opinion, a provision the model named confidently and which does not exist in that wording. A colleague caught it, not her.
What the mode audit showed (chapter 8)
Irina worked through the AI working mode audit and got an unwelcome but accurate result.
| Question on the sheet | Honest answer |
|---|---|
| Do I read the model's answer in full | Diagonally, if it looks well structured |
| Do I check citations against the source | I used to; lately only sometimes |
| Could I do this work as fast without AI | Not any more |
| Has it become harder to formulate things myself | Yes — I catch myself waiting for a draft |
Mode: self-automator in analysis, centaur in negotiation.
Why this is an honest answer: the temptation was to write "centaur" everywhere, which reads better. Irina separated the areas: where she holds the context and argues, the mode is healthy; where she accepts finished work, it is not.
Where the debt actually accumulates
Not in the AI writing drafts. In the fact that the checking weakened unnoticed: first selectively, then "by how convincing it feels".
That is precisely the trap the cognitive debt checklist warns about: how convincing a text is and whether it is correct are different things, and the first grows faster than the second.
What she changed
- No exceptions rule. Every reference to a rule or a case is opened in the source before it reaches a document. The model's wording can be used; its citation cannot.
- Two separated modes. "Draft" can be fast and AI-assisted. "Signed opinion" starts with her own position in three lines, and only then the model — as an opponent, not an author.
- One review a week without AI. Not on principle, but to see whether she can still formulate things herself. That is friction instead of a finished answer.
- A skill of her own for contract review, with a required line — a quoted clause for every risk — so the check is built into the answer format.
The three-month check
Not "does it feel better" but measurable: how many times in a quarter a citation she did not open herself reached a document under her signature. Target: zero. In the first month, two — both caught by her own check.
Why this is not an invented problem
Citations that do not exist are a measured effect, not a scare story. The Stanford RegLab and Stanford HAI study "Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools" (Magesh, Surani, Dahl, Suzgun, Manning and Ho; preprint 2024, published in the Journal of Empirical Legal Studies, 2025) tested purpose-built legal AI tools — Lexis+ AI and Westlaw AI-Assisted Research — and recorded hallucinations in 17% to 33% of answers. These are tools built specifically for law and sold on a promise of reliability.
The lesson for the worksheet is simple: the more convincing an answer looks inside your own field, the more it needs an outside check. Professional accountability does not transfer along with the work — the signature stays yours.
Next: the AI working mode audit · the cognitive debt checklist.