Starlight IntelligenceStarlightAcademy

Lesson 05 / 06 · Work

Teach through prediction and proof.

Turn an impressive output into a learning experience another person can repeat.

Your artifact: A worked example, critique and transfer attempt

Make the learner's judgment visible.

Begin with a concrete task and an unaided prediction. Show the relevant source and ask the learner to make a choice. Offer a hint before the complete worked example. Then compare the first attempt, revise one decision and repeat on a different case. This course adopts that sequence as a teaching design, not a claim of measured learning gains.

An AI teaching team should have complementary jobs: the architect identifies a mechanism, the builder produces an artifact, and a reviewer challenges it against frozen acceptance. These responsibilities can be prompts within one host or a bounded team where supported. Names and illustrated faculty are teaching identities; they do not prove a hosted multi-agent runtime.

Let the learner carry the original work, source trail and critique into their own agent. The Academy's existing connect, installation and evaluation routes provide continuity. A self-reported check is useful practice evidence, not a credential or independent assessment.

Worked example · illustrative

See the decision.

Before revealing a workflow map, ask which operation requires review. After the learner answers, show the authored boundary and explain it. A second case changes from drafting a message to sending it, so the learner must apply the rule rather than repeat the earlier label.

Run the prompt.

Use the supported host shown above and supply your own non-confidential context. Preview availability and tool access depend on your account.

Teach this workflow through one decision at a time. First ask me for an unaided prediction and a reason; wait for it. Then show only the source evidence I need. Give a hint before a worked example. Compare my answer to the authored example without treating disagreement as a verified assessment. Ask for one revision and a fresh transfer case. Keep original and revised reasoning distinct. Use Starlight's available learning, architecture and review skills only within their actual tools and permissions. End with a portable practice note containing artifact, sources, changes and unresolved questions.
Open the prompt library and studio

Make a first attempt.

Teach a peer one approval-boundary decision. Preserve their initial reasoning, the hint and the revision. Use a fresh case to test whether the explanation transfers.

Inspect your artifact

  • Prediction precedes the worked answer.
  • Hints preserve a meaningful learner decision.
  • First attempt and revision remain distinguishable.
  • Transfer uses a different case and makes no certification claim.

Transfer / A fresh case

Carry the idea further.

Use the same learning sequence for a design or source-quality decision instead of an approval boundary.

Keep a note of your prediction, what happened and one revision. These are self-study checks, not a graded assessment.

Read the primary sources.

Checked 2026-10-20. Recheck availability, access and API versions before a real implementation.