Session Debrief

This week we launched the AI Executive Accelerator with three cohorts and 16 participants. These notes synthesize what we covered and what emerged across all sessions.

Common Concerns Across Cohorts

You are not alone. These concerns came up repeatedly, and they are the right concerns to have.

Hallucinations and Trust
How do you know when AI is making things up? This was the most common concern. The short answer: you verify. AI generates plausible text, not retrieved facts. Cross-check claims that matter. Use multiple models. Check cited sources. We will go deeper on verification workflows in Module 5.

Overreliance and Critical Thinking
Several of you asked: if I lean on AI too heavily, will I lose my edge? This is a real risk, but it depends on how you use it. If you outsource your thinking, yes. If you use AI to accelerate your thinking while staying in the driver's seat, no. The goal is augmentation, not replacement.

Data Privacy and Security
What happens to the information I share with these tools? The answer varies by tool and subscription level. Claude Pro does not train on your conversations by default. ChatGPT does unless you opt out. Enterprise versions offer stronger guarantees. When in doubt, do not share anything you would not want in a training dataset.

Tool Proliferation
Which tools should I use? There is no single answer. Different models have different strengths. The approach we are taking: start with Perplexity for research (it aggregates multiple models), Claude for extended reasoning and writing. The skill is knowing when to use which, and that comes with practice.

Confirmation Bias
Will AI just tell me what I want to hear? It can, especially if you prompt it that way. The antidote: ask it to argue against your position. Ask what you might be missing. Use it to stress-test your ideas, not just validate them.

Key Frameworks Introduced

Fluid vs. Crystallized Intelligence
This comes from Arthur Brooks' work. Fluid intelligence is raw processing speed: quick recall, pattern matching, learning new things fast. It peaks early and declines. Crystallized intelligence is accumulated wisdom: judgment, context, knowing which facts actually matter. It keeps growing.

AI provides fluid intelligence on demand. You bring the crystallized half. The combination is more powerful than either alone. You are not learning a new trick. You are gaining access to the missing half of your intelligence profile at the exact moment when your crystallized intelligence is at its peak.

The Time Shift
Right now, most executives spend 9 hours organizing and processing for every 1 hour of real thinking. AI can flip that ratio. The goal is not to do more work. It is to do better work.

Amplification, Not Replacement
If you are good at something, AI can help you become great at it. If you are great at something, AI can help you become extraordinary. Your domain expertise is the multiplier. AI is the accelerant.

What We Covered

• Introductions and surfacing concerns (this sets the tone for everything)
• Why AI matters for executives specifically
• Getting started with Perplexity (for those new to it)
• Prompt specificity: weak prompts vs. strong prompts
• Source verification: check the footnotes, not just the answer
• Time-boxing: set limits to prevent rabbit holes

Homework for Module 2

1. Use a new tool for research this week. If you have not tried Perplexity, use it instead of Google for your searches. If you are already using Perplexity, try pushing it deeper on a question until you get an insight you would not have reached on your own.

2. Read "The Shape of Meaning." This is a visual explainer on how large language models actually process language. It is cocktail-party level, not technical. The goal is building intuition for why these tools behave the way they do.

3. Optional: Read "Two Roads of AI." A visual timeline of AI history, from Turing through transformers. Helps explain why modern AI can approximate intelligence but cannot follow rules reliably.

4. Prepare one moment to share. Come to Module 2 ready to share either a win (something that worked well) or a loss (something that did not). Both are valuable.

All materials are available at jayfontanini.com/accelerator/curriculum/module-1/

What is Coming in Module 2

• Homework review: wins, losses, and reactions to "Shape of Meaning"
• Introduction to Claude: why this model specifically, how it differs from ChatGPT
• Projects and context management: keeping conversations productive over time
• Hands-on practice with longer-form tasks

A Note on This Course

I am not positioning myself as an expert. I am someone who has jumped in significantly and stubbed my toe in places I think you should know about. The value here is in the room: experienced professionals learning from each other, not from someone who has all the answers.

If something is not working, tell me. Formal feedback requests come at the end of each 3-week module, but you do not have to wait.

See you next week.