Allie K. Miller: Show the Evidence for Your AI Skills

The Lesson

You use an AI assistant often, so you feel comfortable with it. Then a colleague asks how you checked its last result. You can describe the prompt, but you cannot show the source, the correction you made or the version you finally used. That is a useful learning gap to identify.

In her July 17, 2026 newsletter about AI readiness, Allie K. Miller argues that a person’s confidence and an organization’s actual capability can diverge. She begins with awareness of how work is really done, rather than judging readiness from the people and tools around you. Her official site identifies her AI business education and advising work.

You can apply that idea to your own learning without buying an assessment. Pick one ordinary task and look for evidence of what you can already do. A completed task gives you something more specific to examine than a broad label such as beginner or expert.

Suppose you used AI to turn public event information into a short volunteer briefing. There are several skills inside that task: selecting the relevant information, explaining the request, checking the result and revising it for the reader. Being able to start a conversation with an assistant does not establish all of them.

Find the result and its source. Which facts did you check? Which sentence did you change? Could another person see why your correction was needed? If you no longer have that evidence, mark it as unavailable and choose a new practice task. You do not need to reconstruct a success story from memory.

Separate an observed ability from an ability you expect to have. You may have checked names and dates carefully, but never tested whether the brief omitted an important instruction. Write both statements down. That gives you a concrete next practice: check completeness against a short source.

You can also notice a strength that your general confidence hides. Perhaps you feel behind because you have not built an agent, yet you consistently detect unsupported statements in generated copy. Record that skill with an example. It is useful work, and the evidence helps you decide what to learn next.

For a team, keep the discussion tied to tasks. One person may be good at finding source material, another at writing a clear request and another at checking an output. Avoid turning the exercise into a public ranking of people. Ask which step needs better support or an example someone can teach.

The worksheet below is a small learning record. It does not certify readiness across a company or reproduce Miller’s assessment. Its purpose is to help you choose a practice you can observe.

Reflection

• What is the last useful task I completed with AI?
• What can I show about the way I checked it?
• Which ability have I only assumed I possess?
• What could I practice next with a short, checkable source?

Practice

Original SelfGrowthVideos exercise: make an evidence sheet for one task. This is our exercise, not Allie K. Miller’s AI-First Index.

1. Choose a completed learning or work task whose material you can appropriately share. Alternatively, make a fictional event notice for practice.
2. Write the intended result in one sentence: who needed what?
3. Make three headings: what I did, evidence I can show, and what remains untested.
4. Record one step you performed, such as checking every date in a generated brief. Link that step to the source and the reviewed result.
5. Record one change you made and the reason for it. If you have no record, say so.
6. Name one untested ability. Keep it narrow, such as checking whether a brief preserves all three instructions.
7. Choose a short new practice that would let you observe that ability. Define what you will inspect before you begin.

Keep the sheet alongside your practice result. A useful entry describes an action and its evidence, rather than awarding yourself a general score.

Review

After the next practice, replace one assumption with an observation. What did you check, what did you miss and what did you change?

If you work with a peer, ask them to trace one entry from your claim to the evidence. Use any confusion to improve the explanation or choose another practice.

Go Deeper

• Allie K. Miller’s creator profile links to her original writing and selected videos.
• AI Learning & Career Skills collects practical ways to build understanding.
• AI for Business & Agency connects learning with real work.
• Tina Huang: explain and change one AI-generated function makes a coding skill observable.