The Real Talk Guide to Using AI Agents and Generative AI—Plus When *NOT* to use AI

"Nate, I need an AI project for the board this quarter. I gotta have one. Can I use it for the quarterly sales reports?"

"Nate, my boss told me to do AI but I don't think he knows what he's asking for. What do I do?"

"Nate, where do I actually use AI agents? I hear so much about them and I don't want to fall for the hype."

These questions all boil down to one thing: we don't know how to match problems to solutions anymore because AI is drowning out common sense.

I get messages like these every single day. Smart people being asked to force AI into places it doesn't belong. Engineers who know better but can't articulate why ChatGPT is the wrong tool for their reporting problem. Product managers trying to navigate between board pressure and technical reality.

After years of watching this pattern—first with big data, then machine learning, now with generative AI—I've developed a horse sense about when to use what tool along with executive talk tracks that help me communicate what I mean to anyone who needs to listen.

This week I’m sharing all of it here, so you’re equipped to actually know when to use AI Agents, when to use Generative AI, and so you know how to push back when simpler tools work better.

What you're getting:

1. A four-category framework that instantly clarifies which tool fits which problem

2. The exact scripts I use when executives demand AI for problems that need simpler solutions

3. Real examples from companies like Walmart, JPMorgan Chase, and BMW showing what actually works

4. A simple decision tree you can use in any meeting to determine the right approach

5. The risk-adjusted ROI calculations that make the business case clear

The framework doesn’t take an engineering degree to understand, I promise. Once you get it, you'll spot AI washing instantly, know when agents actually make sense, and save yourself and your team from expensive mistakes that should have been cheap wins.

Most importantly, you'll finally have the confidence to make the right call. When someone demands AI for that quarterly sales report, you won't just know they're wrong—you'll know exactly why, what to propose instead, and how to explain it in terms they'll understand. That's the difference between being right and being effective.