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2026 field guide

Teach AI by building one useful thing.

Skip the tool tour. Pick one real task, add the right context, build it live, and send people home with a working artifact they can run again.

By Ryan WannerPractical guideReviewed August 20, 2026

The workshop operating system

One task. One build. One review gate.

  1. 01

    Pick one job, not ‘AI’

    Choose a task people already recognize: turn meeting notes into actions, draft a listing brief, or compare two documents.

  2. 02

    Show done first

    Open with the exact artifact participants will leave with. People learn faster when the finish line is visible.

  3. 03

    Teach the four-part brief

    Name the task, context, constraints, and output. Then show how each missing piece creates a weaker answer.

  4. 04

    Build in the room

    Use a real but safe source file. Let the model draft while you narrate the decisions, corrections, and uncertainty.

  5. 05

    Make them change it

    Participants replace your context with their own. Copying a prompt is not the same as learning the workflow.

  6. 06

    End with evidence

    Save the source, prompt, output, review checklist, and one next test. The take-home artifact matters more than a slide deck.

Copy the workshop-builder prompt.

This prompt creates the teaching scaffold. You still choose the real task, approved source material, and success standard.

60-minute AI workshop builder

You are helping me teach a practical AI workshop.

AUDIENCE
[role, experience level, and what they already know]

REAL TASK
[one task they already do at work]

SOURCE MATERIAL
[paste or upload the approved example, policy, template, or data]

LEARNING RESULT
By the end, each person must produce [specific usable artifact].

BUILD A 60-MINUTE PLAN
- 0–8: show the finished artifact and the problem it solves
- 8–18: explain task, context, constraints, and output
- 18–35: guided build with a starter prompt
- 35–47: participants adapt it to their own work
- 47–55: pair review against a five-point checklist
- 55–60: save the prompt, source, output, and next test

Return a time-boxed facilitator plan, participant worksheet, starter prompt, review checklist, and one fallback exercise. Do not invent facts missing from the source material.

Worked example

Meeting notes → owner-ready action plan.

Give the group a fictional transcript. Ask the model for decisions, owners, deadlines, open questions, and risks. Then compare every line to the transcript.

  1. Input: a 2-page safe transcript.
  2. Prompt: extract, don’t embellish, and cite the supporting sentence.
  3. Output: action table with “uncertain” where the transcript is unclear.
  4. Review: each action must map back to source evidence.
  5. Artifact: saved prompt + checklist + one completed plan.
Low-cost path:

Use the chat tool your team already has. A shared document, a safe sample file, and a timer are enough. Don’t buy an AI training platform before this manual workshop works.

Build the complete teaching system.

Workshop design

Design backward from a participant-built artifact.

Open standalone guide →

Prompt literacy

Teach task, context, constraints, output, and review.

Open standalone guide →

Evaluation rubric

Score source fidelity, judgment, revision, and receipts.

Open standalone guide →

Research sources

Check the current rules, capabilities, and source basis.

  1. 01OpenAI Academy: Prompting ↗

    First-party guidance on task, context, output, iteration, and prompt structure.

  2. 02OpenAI Academy: Abilene resource hub ↗

    A current workshop resource that emphasizes sensitive-data protection, human review, and practical prompt starters.

  3. 03NIST AI Risk Management Framework ↗

    A voluntary framework for trustworthy, risk-aware AI use and evaluation.

  4. 04NIST Generative AI Profile ↗

    Specific generative-AI guidance supporting human review, tracking, and documentation.

Product access, limits, local listing rules, platform policies, and laws can change. Re-check the linked authority before important or public work.

Keep building

Check us out on Skool for 30+ classes and growing.

AI Acceleration: Real Estate is a private, self-directed curriculum for practical AI work across content, communication, lead follow-up, CRM, client research, operations, and relationship management. Build it. Review it. Keep what works.

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No ranking, revenue, closing, or time-saving promise. The classes teach the work and the review systems around it.