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When commissioning AI training, I'd ask to see the exercise used to assess participants.
Suppose a participant uses AI to turn a project brief into a delivery plan. Ask them which assumption affects the deadline and what they chose to revise. Then move the requested delivery date forward. What could change, and what would the team have to agree before promising it?
In the discussion, I'd want to hear how the participant interpreted the model's answer and chose what to keep. The exercise is hypothetical and comes from my article on making a person's contribution visible in AI training.
I publish the article; AI assisted the article and this post.
https://topmoller.com/articles/who-passed-your-ai-training-assessment/?utm_source=contra&utm_medium=community&utm_campaign=ai-assessment-202610&utm_content=changed-deadline
topmoller.com
Who actually passed your AI training assessment?
When an agent can complete a course quiz, the completion report leaves a question about the participant. Examine what the assessment actually proves.
do you test people on real tasks from their own job or more general prompts?
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You have a point but a time is coming when that manual work will be fully automated with Ai.
As most of us are still doing manual work some people are busy training Ai to take over that activities in nearby future
Manual work is always better than ai slop you can use ai for some clips but full video made with ai is unprofessional and a waste of money and resources
The point about people quietly training AI on today's manual tasks is the part most of us underestimate. Do you think the craft shifts to directing and curating those models, rather than disappearing entirely?
Proposal Writer: a custom Claude Skill that makes Claude follow one business's process every time.
The skill folder holds the steps (SKILL.md), a price list, a proposal template and a checklist. In a real Claude Code run, it turned call notes into a priced proposal in the house style. It used only the skill's own prices, flagged an unmeasured job as "price to confirm" and caught that 7 November 2026 is a Saturday, not a Friday.
An example I built for my portfolio, with demo data. For clients, I build skills around their own task and test them on their own examples.
For the "price to confirm" case, I'd test notes with a quantity but no matching unit, such as "12 panels" when the rate is per square metre. Does the skill ask for the missing measurement before calculating a total, even if the notes include the client's suggested budget?
When I scope clinical AI, I separate drafting from rule-based checks.
In Arogya, typed or dictated rounds become editable AI drafts with the original source preserved. Deterministic rules handle checks such as allergy conflicts and abnormal-lab flags. Clinicians review and approve AI content before it reaches the chart.
That separation matters when a model or prompt changes. I'd want the team to rerun the rule checks with the same inputs and inspect their results independently of the draft's wording.
For a client evaluating an AI scribe, I'd ask to see why a flag appears and how the clinician reviews it before approving the record.
Public case: https://kapilchauhan.netlify.app/case/arogya.html
kapilchauhan.netlify.app
Arogya / Aurora EHR: AI for inpatient care | Kapil Chauhan
Production hospital and EHR platform that accelerates rounds, documentation, records, and care operations with clinician-reviewed AI.