Start with a task you already understand deeply
The strongest proof project usually sits inside your existing domain expertise: a reporting workflow for an accountant, a lesson adaptation workflow for a teacher, a support-summary workflow for a service manager, or a requirements draft for a project manager. You can judge output quality because you already know the work.
Generate occupation-specific proof ideas →
Show the human-controlled workflow
Document five things: the task, input, AI-assisted step, verification step and final human-edited output. The interesting part is often the correction: what did the model misunderstand, omit or overstate, and how did your experience catch it?
| Weak proof | Stronger proof |
|---|---|
| “Used ChatGPT for reports” | Redacted before/after report workflow + verification checklist |
| “AI proficient” | Three tested prompts, failure cases and final reviewed artifact |
| Certificate only | Course + project showing application in your field |
Use safe data from the beginning
For a public portfolio, synthetic data is often the easiest choice. If you use real work examples, remove confidential identifiers and follow employer/client policy. Do not paste customer, employee, patient, legal or financial records into an external AI tool simply to create a case study.
Measure something modest and truthful
You do not need a dramatic ROI claim. Useful evidence might include time taken across several test runs, number of manual steps removed, number of issues caught by your checklist, or consistency of the final format. If you did not measure an outcome, do not let AI invent one.
Turn the project into résumé language
Use a simple structure: Built + workflow + professional purpose + verification.
This is stronger than listing a tool because it gives an interviewer something concrete to ask about.
Put the proof somewhere visible
Depending on your field, add a short project description to LinkedIn Featured/Projects, a portfolio page, GitHub, a PDF case study or a résumé Projects section. LinkedIn's profile tools support Projects, Featured, Courses and other sections that can surface current learning and work samples.
A one-week proof sprint
- Choose one recurring task you understand.
- Create synthetic or public input.
- Build a simple AI-assisted workflow.
- Test it three times and note failure cases.
- Create a verification checklist.
- Write a one-page case study.
- Add a concise line to résumé/LinkedIn only after completing the work.
Sources & further reading
- ILO: Old Skills for New Technologies (Aug 2026)
- AARP: AI and older workers research
- LinkedIn Help: Add sections to your profile