// LEARN · AI LITERACY

Learn AI, in plain English

Short, practical lessons on using AI well — written for people who run small organizations, not engineers. No jargon, no hype. Just what the tools actually do today and how to get useful work out of them. New module added regularly.



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The modules

Each module stands on its own and takes a few minutes to read. Start at the top if you’re new to this.

  1. AI Basics — what you can actually do with it
  2. Writing a good prompt — getting better answers

This curriculum is the training spine behind our AI Operator-in-Residence work — the part of the job that’s about leveling up your team, not just shipping automations.



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AI Basics — what you can actually do with it

Most people who “have access to AI” use it for one thing — drafting an email — and never find out what else it’s good for. This is the wide-angle tour: ten everyday jobs you can hand off today, with the tools you already have.

10 useful ways to use AI

  1. Writing assistance — draft emails, posts, or reports from a few notes.
  2. Research aid — summarize long articles, documents, or threads down to the point.
  3. Idea generator — brainstorm names, angles, offers, or plans when you’re stuck.
  4. Learning tool — get plain-English explanations of anything you don’t understand yet.
  5. Rewrite & edit — tighten, shorten, or change the tone of something you already wrote.
  6. Translation — move text between languages, including casual vs. formal register.
  7. Planning & organizing — turn a messy brain-dump into an agenda, checklist, or schedule.
  8. Read an image — describe, transcribe, or pull data out of a photo, screenshot, or scan.
  9. Code helper — write, explain, or fix small scripts and spreadsheet formulas.
  10. First-draft anything — policies, FAQs, job posts, replies — a starting point beats a blank page.

The point isn’t that AI does all ten perfectly. It’s that any one of them turns a blank page into a draft in seconds — and the draft is where your time actually goes.



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Writing a good prompt — getting better answers

The biggest difference between people who find AI useful and people who find it underwhelming isn’t the tool — it’s what they ask for. A vague request gets a vague answer; a clear one gets something you can use. You don’t need special syntax. You need to tell it what you’d tell a sharp new hire on their first day.

The 4 things a good prompt has

  1. Role — who it should act as. “You’re a customer-service rep for a dental office.”
  2. Task — what you want, specifically. “Write a reply to this upset patient.”
  3. Context — the details only you know. Paste the actual email, the policy, the names, the dates.
  4. Format — what the output should look like. “Under 150 words, warm but professional, don’t apologize for the fee.”

Most weak prompts are missing the last two. The model can’t read your mind or your inbox — give it the raw material and tell it the shape you want back.

Before and after

Weak: “Write a follow-up email.” → generic filler you’ll rewrite anyway.

Strong: “You’re me, a roofing contractor. Write a follow-up to a homeowner I quoted $14k for a roof replacement two weeks ago and haven’t heard back from. Friendly, no pressure, one short paragraph, end with a soft question. Their name is Dana.” → something you can send after a quick tweak.

Three habits that beat any trick

  • Show an example. Paste one email you’ve sent that you liked: “Match this tone.” Examples teach faster than adjectives.
  • Iterate, don’t restart. The first answer is a draft. Just reply: “Shorter, and drop the second paragraph.” It remembers the conversation.
  • Ask it to ask you. “What do you need to know to do this well?” — a great move when you’re not sure what to include.

Where this still goes wrong

Even a perfect prompt won’t make AI reliable on facts it can’t verify — specific numbers, dates, names, quotes, or legal and medical specifics. It will sometimes state a confident, wrong answer. Treat anything checkable as a draft to confirm, not a source. (That’s the next module.)



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Want this for your team?

These lessons are how we get a client’s whole team using AI, not just one curious person. If that’s the gap you’re trying to close, the AI Operator-in-Residence engagement is built around exactly this — ship real automations and level up the people next to them. Get in touch and we’ll talk through where to start.