What You Need to Know
A stakeholder here is a colleague who reads your report on a Claude trial and decides what happens next. Reporting to them has one rule: say what is true, including the parts that are not impressive. It serves two audiences, the enthusiast and the sceptic.
Take a tyre fitter whose office manager is reporting on a three-month Claude trial. Accuracy here is strategy as well as modesty. If she over-promises, she wins a mandate she cannot deliver. The first visible error is then read as proof the whole thing was oversold. If she under-claims, the work is starved of the support it earned. An accurate claim stands up to a sceptic.
Stating Value in Four Parts
State value in four parts: the task, the before, the after, and how you know. "The monthly board pack takes two hours instead of five, measured across three months" is a claim the tyre fitter's manager can defend. "Claude has transformed how we work" is not a claim: it names no task and no measurement, so nobody can check it. An audience that has heard that sentence before will discount everything that follows it.
Anthropic's enterprise guidance says the same: productivity gains, such as hours saved, measured through periodic user surveys and reported to stakeholders on a regular cadence. It pairs quantitative data with qualitative examples, in place of enthusiasm.
Every figure in the report appears because somebody measured it over a stated period, never because it sounds about right. A measured saving belongs to its task. The board pack figure is never projected onto work the trial did not touch.
The Untested Category
Limitations get stated plainly: what still needs a person and why, what went wrong during the pilot, and what hasn't been tested. People omit the untested category, and it causes trouble later: silence gets heard as a claim. A stakeholder never told that some work went untrialled will reasonably assume it was covered. The eventual failure then lands on the report that stayed quiet, as well as on the work. If the tyre fitter never tried Claude on warranty claims, naming that costs one sentence. Leaving it unnamed costs the report its credibility when the gap surfaces.
A Caught Error Is Evidence
A caught error is evidence for the process. Say a booking confirmation used the wrong date and the read-through caught it. Reporting it tells a sceptic the checking step works, the very thing they doubted. If the error is hidden and surfaces later, every other claim in the report gets re-read as curated. This is the Diligence element of AI Fluency in reporting form: staying accountable for what the AI produced, including in what you tell colleagues about it.
The Enthusiast and the Sceptic
Stakeholders arrive in two postures, and each needs a different service from the same truthful account. The enthusiast, perhaps the tyre fitter's owner, wants it everywhere by Friday. They need the limitations and the human gate without dampening the momentum that will carry the work. So the answer to "can it handle all of it now?" names what stays human, not a flat no. The sceptic, perhaps a fitter, suspects a toy, a risk or a threat to somebody's job. They need the measured result, the named human step, and a straight account of what went wrong and how it was caught.
The overcorrection fails with both: so many caveats that a working result sounds like a failure. Under-claiming is not honesty. It hands the sceptic a conclusion the data does not support.
In the exam
Treating a caught error as evidence marks a prepared candidate. Whether a use is permitted, and who must approve it, is Domain 6's territory. This objective covers the honest account of results to colleagues, never a governance sign-off.
The number rule
In this objective's items, the only number that can support a keyed answer is one the stem itself says was measured. Any option quoting a saving nobody measured, or projecting a measured saving onto untested work, is wrong however reasonable the figure sounds.
Exam Traps
Presenting enthusiasm as evidence
A transformation claim with no task, no before, no after and no measurement cannot be checked, so a sceptical audience discounts it, and the genuinely measured result underneath goes down with it. The keyed answer states the four parts and stops.
Projecting a measured saving onto untested work
A measured result belongs to the task it was measured on. Extending it to a category the trial never touched quotes a number nobody measured, and the exam treats it as wrong regardless of how plausible the projection looks.
Leaving the pilot's caught error out of the report
When the error surfaces later, every other claim gets re-read as curated. Disclosed, the same error was evidence that the checking step works, which is exactly what the sceptical audience needed to hear.
Burying a working result under caveats
The caveat avalanche is the overcorrection: so many warnings that a process that works sounds like one that failed. Under-claiming starves the work of support just as surely as over-claiming discredits it, and the exam tests both directions.
Practice Scenario
The coordinator of a talking newspaper for blind and partially sighted listeners has trialled Claude for three months. Listener letters now reach a first draft in minutes rather than half an hour, measured across the trial, with every letter still read and approved by a volunteer before it goes out. Edition scripts saw no saving, because the recording sessions were always the bottleneck. One draft gave the wrong date for the annual listeners' tea and was caught at the read-through. The committee has asked for what the trial showed, with nothing projected or hypothetical and nothing left out. What should the report to the management committee say?
Build Exercise
The Three-Part Account
What you'll learn
- How to state a value claim in four defensible parts
- How to name the untested category explicitly
- How to present a caught error as evidence for the process
- How to answer the enthusiast and the sceptic from the same truthful account
- Take any Claude use you have actually run for a few weeks; the augmentation from the 4.4 exercise is ideal
Why: The account only teaches honesty when the material is real; invented pilots have no inconvenient findings.
You should see: One named piece of work with at least a few weeks of history behind it.
- Write part one: what changed, with the task, the before, the after, and how you measured it
Why: The four-part shape is what makes a claim defensible to a sceptical reader.
You should see: One or two sentences a sceptic could check rather than merely believe.
- Write part two: what did not change and why, and what you have not tested, named explicitly
Why: Silence about the untested category gets heard as a claim; naming it is what prevents the later surprise.
You should see: An honest paragraph including at least one thing the trial never touched.
- Write part three: what stays human and why, including one example of something the human step caught, however small
Why: The caught error is the evidence the sceptic needs that the checking step works.
You should see: A named human gate and one concrete catch, presented as the system working.
- Strike every number you did not measure, then rehearse two replies aloud: the enthusiast asking can it do all of it now, and the sceptic asking so it makes mistakes
Why: The two postures are the objective’s test of whether one truthful account can serve both audiences.
You should see: An enthusiast answer that names the human gate without a flat no, and a sceptic answer that treats the caught error as evidence.
Sources
- Claude Enterprise Administrator Guide — Anthropic
- AI Fluency: Framework and Foundations — Anthropic (the element names are the course's module titles; the one-clause glosses of each element are our paraphrase of the course content)
- Claude Certified Associate – Foundations Exam Guide — Anthropic. No Anthropic document covers stakeholder communication as a skill. This lesson draws on the exam guide's objective and standard professional practice; the Enterprise Administrator Guide and AI Fluency support specific points.