Using AI Well: Your Personal Edge

Reading about AI gets you the vocabulary. Using it gets you judgment.

The people who sound most credible about AI use it daily. They've felt where it's brilliant and where it falls on its face, so a slick demo doesn't fool them. This chapter is your practice plan: which tools to use, how to brief them, ten workflows built around your actual week, what never to paste in, how to check the output, and a 7-day challenge to make it stick.

Pick your tools

As of September 2026, seven assistants matter. They leapfrog each other every few months, so don't marry one.

• ChatGPT (OpenAI). The most widely used; OpenAI reported more than 900 million weekly users in February 2026. A strong all-rounder for writing, voice, images, research and file analysis. Its agent, ChatGPT Work, takes on longer projects.
• Claude (Anthropic). Known for strong writing, careful reasoning over long documents, and coding. Popular with businesses. Its agent, Cowork, handles multi-step tasks across your files.
• Gemini (Google). Built into Gmail, Docs, Drive, Android and Chrome. Strong with video, images and long files. Google said the app passed 1 billion monthly users in August 2026. Google's NotebookLM, a research notebook that grounds its answers in sources you upload, is excellent for teaching.
• Microsoft Copilot. Lives inside Outlook, Teams, Word, Excel and PowerPoint. If your company licenses Microsoft 365 Copilot, its edge is access to your work email, meetings and files. It offers models from both OpenAI and Anthropic.
• Perplexity. An answer engine that shows citations with every answer. Great for quick, sourced lookups.
• Grok (xAI, now part of SpaceX). Plugged into X for real-time chatter. Looser guardrails and a history of controversies; check whether your company allows it.
• Meta AI. Built into WhatsApp, Instagram, Facebook and Ray-Ban Meta glasses. Free, everywhere, consumer-first.

The setup to aim for: your company's approved tool for anything work-related, plus one paid personal account (about $20 a month as of 2026) for learning with non-confidential material. For anything that matters, pick the most capable model in the menu, usually a reasoning model. The fast ones are for quick lookups.

Features worth turning on

• Custom instructions. Tell it once who you are and how you like answers, and every chat starts briefed. It works like a personal system prompt. A template is below.
• Projects. A workspace with its own files and instructions (Gemini's closest equivalent is Gems). Make one for your Georgetown course or a recurring planning cycle, and every chat inside starts with the background loaded.
• Memory. The assistant remembers facts about you across chats. Useful, but review what it stores and switch it off for sensitive work.
• Voice mode. Talk instead of type, on a walk, a hands-free drive, or in an airport. Rehearse a pitch, or have it play a tough partner CFO and push back.
• Deep research. Chapter 5's agents in action: it searches dozens of sources for several minutes and returns a cited report. Ideal for partner and market research.
• Agent modes. Cowork, ChatGPT Work and Copilot's agents take multi-step projects off your plate. Start with low-stakes, read-only tasks.

Paste this into your custom instructions and edit it to fit:

About me: I'm a VP of Betting & Gaming at a sports data and technology company, covering the Americas. My background is partnership and sponsorship sales in pro sports. I also teach sports industry management as an adjunct professor.

How to answer: Be direct and concise. Lead with the answer, then the reasoning. Use plain English and explain technical terms. Use bullets for lists and short paragraphs otherwise. If you're unsure, say so and tell me what would change your view. Flag anything time-sensitive so I can verify it. Don't flatter me or pad the answer.

Prompting that works

The mental model: brief a brilliant new hire on their first day. They've read nearly everything ever published and they work fast. But they know nothing about you, your company, your partner or what "good" looks like here. A vague brief gets generic work. A sharp brief gets work you can use.

A strong prompt covers six things:

1. Context. Who you are, the situation, the audience.
2. Role. Who it should act as: "a skeptical CFO," "a veteran industry analyst."
3. Goal. The decision or outcome the work serves.
4. Examples. Paste one you like. This is the single biggest quality lever.
5. Format. Length, structure, tone: "one page, bullets, three headers."
6. Constraints. What to avoid, what must be included, what to do when unsure.

Then iterate. Treat the first answer as a first draft and push back: "shorter," "more skeptical," "this is generic, use the details I gave you," "what's missing?" Three quick rounds beat one perfect prompt.

Two power moves work almost everywhere. Start with "Ask me any questions you need before you start." And end with "Give me three options, then tell me which you'd pick and why."

Ten workflows for your week

Each prompt is ready to copy. Replace anything in [brackets]. Anything confidential belongs only in your company's approved tool (more on that in the next section).

1. Meeting prep

I have a [45-minute] meeting on [date] with [name, title] at [company]. Purpose: [e.g., first intro / renewal of a data partnership].
Using public information only, give me:
1. A 5-bullet snapshot of the company: business model, recent results, key markets, and news from the last 90 days.
2. What [name] has said publicly (interviews, posts, conference talks) and what they likely care about.
3. Three smart questions that show I did my homework.
4. Two objections they might raise, and how I could respond.
Keep it to one page. Cite a source for every factual claim.

Pro move: Run it the night before in deep research mode and read it on your phone on the way in.

2. Partner research

Act as an experienced analyst covering [industry, e.g., sports media and technology]. Build a research brief on [company] for someone evaluating a strategic partnership.
Cover: ownership and financials, the markets and regions where they operate, product strengths and weaknesses, publicly announced technology partners, regulatory issues, leadership changes, and strategic direction from their last two earnings calls or public statements.
End with "What this means for a potential partner": 3 opportunities and 3 risks.
Use only sources you can link. Flag anything older than 6 months.

Pro move: When the report comes back, ask: "Which three claims here are you least confident in, and why?" Check those first.

3. Deal memos

Turn my rough notes below into a deal memo for my leadership team.
Structure: 1) The ask, in one sentence. 2) Deal summary: partner, term, value, key rights. 3) Strategic rationale. 4) Financials and assumptions. 5) Risks and mitigations. 6) Open questions. 7) Recommendation.
Tone: crisp and neutral, no hype. Maximum 2 pages.
Where my notes are missing something a skeptical CFO would ask about, insert [NEEDS INPUT: ...] instead of guessing.

My notes:
[paste notes]

Pro move: Follow up with "Now act as the most skeptical member of the investment committee. What are the five hardest questions about this deal?" Deal terms are confidential, so this one lives in your company's tool.

4. RFP responses

You're helping me respond to an RFP from [e.g., a league / a media company / a government agency]. Below are (A) the RFP questions and (B) our previously approved answers and product descriptions.
For each RFP question:
- Draft an answer using only facts found in (B).
- If (B) doesn't cover it, write [GAP: what's needed] instead of inventing anything.
- Keep each answer under [150] words unless the RFP sets a length.
Then give me a table with columns: Question #, Status (Drafted / Gap), and who I should ask to fill each gap.

(A) [paste RFP questions]
(B) [paste approved content]

Pro move: The "only facts from (B)" rule is the whole game. An AI that invents a capability in an RFP creates a contractual problem, not just an embarrassing one.

5. Summarizing long contracts

Summarize the attached agreement for a business reader. I'm not asking for legal advice; I'll confirm anything important with counsel.
Give me:
1. Parties, term, renewal and termination mechanics.
2. Money: fees, minimums, revenue shares, payment timing.
3. Our obligations and theirs, as two separate lists.
4. Exclusivity, territory, and data or IP rights.
5. Key dates and notice deadlines.
6. Anything unusual or one-sided compared with a typical commercial agreement.
For every point, cite the section number and quote the exact language.

Pro move: "Quote the exact language" turns checking into a two-minute job instead of a reread. Today's context windows fit even very long agreements, but contracts are confidential: approved tool only.

6. Drafting emails

Draft a reply to the email below. Goal: [e.g., decline the proposed terms but keep the door open for a smaller pilot].
Tone: warm, direct, confident. Under 150 words. No clichés like "I hope this finds you well."
Give me two versions: one more formal, one more casual.

[paste the thread, with confidential details removed]

Pro move: Paste three emails you've written and add "match my voice." For sensitive emails, ask: "How will the recipient likely feel reading this, and what might they misread?"

7. Pitch deck outlines

I'm building a pitch deck for [audience] to [goal, e.g., convince a partner to expand a data partnership into media and advertising].
Draft a 10–12 slide storyline. For each slide: a headline that states the takeaway as a full sentence, 3 supporting points, and the evidence or chart that would prove it.
The story should flow: their problem → cost of doing nothing → our solution → proof → economics → next steps.
Then tell me which slide is weakest and why.

Pro move: Read only the headlines, top to bottom. If the story lands from headlines alone, the deck works. Consultants build "ghost decks" this way: headlines first, slides later.

8. Analyzing a spreadsheet

Attached is a spreadsheet of [e.g., monthly revenue by partner for the last 24 months].
First, describe the data back to me: columns, date range, and anything missing or odd. Don't analyze until I confirm you've read it correctly.
Then give me: the top 5 trends, the biggest changes versus last year, and anything that looks like an outlier or a data error.
Show the calculations you used so I can check them, and make one chart that tells the main story.

Pro move: "Describe it back first" catches a misread column before it poisons the analysis. Then spot-check two numbers yourself. To practice, use public data, like a public company's quarterly results or government economic statistics.

9. Preparing a lecture

I teach a graduate course in sports industry management at Georgetown. Help me build a 75-minute session on [topic, e.g., how AI is changing sports media rights].
My students are working professionals who want real-world cases, not theory.
Give me: 3 learning objectives, a minute-by-minute agenda, a 10-minute opening hook, one case study with discussion questions, a small-group exercise, and a 5-question exit quiz.
Flag any facts I should verify before presenting.

Pro move: Put your syllabus in a Project (or NotebookLM) so every session builds on the last. Never paste student names, grades or work into an unapproved tool; student records are protected by federal privacy law (FERPA) and university policy.

10. Learning a new topic

I want to understand [topic, e.g., how private equity firms value a company]. I'm a smart non-expert: explain it from the ground up, using everyday business analogies.
Teach me in steps. After each step, ask me one question to check I understood before moving on. If I get it wrong, explain it a different way.
At the end, give me a one-paragraph summary I could say out loud in a meeting, and the 3 best sources to go deeper.

Pro move: Do this one in voice mode on a walk. It also works on this book: paste in a chapter and say "quiz me."

What not to paste, and which account to use

One rule of thumb covers most of it: if you wouldn't forward it to your personal Gmail, don't paste it into a personal AI account.

Keep these out of any personal or unapproved tool:

• Partner contracts, pricing, rate cards, deal terms and pipeline
• Anything under NDA
• Non-public financials or strategy. Genius Sports is publicly traded, so material non-public information is a securities-compliance issue, not just an IT one.
• Personal data about customers, employees or students
• Security and investigation details: fraud or integrity alerts, internal investigations, system details
• Passwords, API keys and access credentials

Why the account matters. Consumer accounts (free or personal paid plans) may use your chats to train future models unless you opt out, some conversations can be reviewed by people, and chats are stored. Stored chats can become evidence: in The New York Times' copyright case against OpenAI, a federal court ordered OpenAI in 2025 to preserve user chats that would otherwise have been deleted. Turning off training helps, but it doesn't make a personal account enterprise-grade.

Business and enterprise versions of ChatGPT, Claude, Gemini and Copilot generally don't train on your data by default. They come with contracts, admin controls, retention settings and audit logs. That's what makes it acceptable to use real work documents in them, within your company's policy.

Three more habits:

• Know the policy. If your company's AI policy is unclear, ask IT or legal which tools are approved and for what data. Asking is what a leader does.
• Disclose AI notetakers. Tell people when an AI is recording or transcribing a call. Some U.S. states require everyone's consent to record, so with external partners, ask first.
• Anonymize when practicing. "A top-five U.S. customer" and rounded numbers work fine for drafting. Anonymizing reduces risk; it doesn't make confidential material acceptable in an unapproved tool.

Check the work

Treat AI output like directions from a GPS. It's right so often that people stop looking up, which is how cars end up in lakes. Follow it on the easy stretches. At the turns that matter, look out the windshield.

AI is weakest exactly where business is least forgiving: specific numbers, dates, names and quotes. That's the hallucination problem from chapter 3. Your look-up checklist:

1. Click the sources. Does the page exist, and does it actually say what the AI claims? A common failure is a real source with the wrong claim attached.
2. Check every number against the original document.
3. Ask for exact quotes with locations: section numbers, page numbers, timestamps.
4. Make it critique itself. "What are you least sure about? What would a skeptic challenge?"
5. Get a second opinion. Run the key claims through a different assistant.
6. Watch the dates. Every model has a knowledge cutoff. For anything recent, make sure web search is on.

Scale the checking to the stakes. A brainstorm needs none. An internal note needs a skim. Anything going to a partner, a board or a classroom needs every fact verified. You own what you send. Lawyers have been sanctioned by courts for filing briefs with case citations that AI invented, and "the AI said so" didn't save them.

The 7-day challenge

Fifteen to thirty minutes a day. By day seven it will feel like a habit.

• Day 1: Set up. Install your main assistant on your phone, paste in the custom instructions, and try voice mode once.
• Day 2: Prep a real meeting with workflow 1, using public information only.
• Day 3: Voice day. On a walk or a hands-free drive, talk through a problem you're chewing on. Ask it to push back.
• Day 4: Long read. Have it summarize a long public document, like a competitor's annual report, then quiz you on it. Check three facts against the original.
• Day 5: Deep research a question you actually care about, like how regulators are approaching AI in your industry. Click at least five sources.
• Day 6: Head to head. Run the same prompt in two assistants and compare. Note which you trust more, and why.
• Day 7: Teach it back. Explain one chapter of this book to the AI as if it were your class, and ask it to grade your explanation and find the gaps.

Keep a running note of the prompts that worked. That file becomes your personal playbook.

Check yourself

1. A colleague pastes a partner's draft contract into their personal ChatGPT account to get a quick summary. What's the problem, and what should they do instead?

2. You asked for a one-page brief on a prospective partner and got something generic. Which parts of a good prompt were probably missing?

3. A deep research report with 40 citations lands the night before a board pre-read. You have 30 minutes. How do you check it?

4. Why is it worth running the same important prompt through two different assistants?