Planck vs. Chauffeur Knowledge: Don’t Get Chauffeured by AI

Charlie Munger told a great story about the two kinds of knowledge in the world:

After Max Planck won the Nobel Prize in physics, he went on a lecture tour around Germany. His chauffeur had heard the same speech so many times that he joked he could give it himself. One day, they actually swapped roles. The chauffeur delivered the talk perfectly. But when someone in the audience asked a tough question, the chauffeur snapped back, “Well, I’m surprised that in an advanced city like Munich I get such an elementary question. I’m going to ask my chauffeur to reply.”

The takeaway?

• Planck Knowledge: Real, earned expertise.
• Chauffeur Knowledge: Memorized, giving the impression of knowledge but lacking the true aptitude.

Now with AI, we’re dealing with chauffeur knowledge on a different level.

Is AI a Chauffeur?

Here’s a real-life scenario. We wanted to ask a developer for a scope and hourly estimate to build a field ticket app. We ran our inquiry by ChatGPT first along with the full requirements doc to analyze. We also asked for information on training hours.

To its credit, it nailed the dev hours. Right on the money. But then it said the training would only take 4 hours.

Cue the chauffeur.

Anyone who has actually rolled out a new system or application knows training takes more than a few hours, especially when you’ve got a mix of field and office staff. Just putting together the materials and a decent plan takes longer than that.

A real expert (Planck-style) would ask questions first:

• Who are we training?
• How many?
• What’s their tech skill level?
• Is this remote or in-person?

Instead, ChatGPT gave a slick, shallow answer. No nuance. It sounded right—but it wasn’t.

Why This Matters

Right now, people all across your organization are using AI. Some of it’s part of an official rollout. Some of it’s happening under the radar (aka shadow AI).

Everything’s fine until someone blindly follows AI’s advice and makes a bad call. That decision can snowball into inaccurate budgets, missed deadlines, or even have legal ramifications.

We’re seeing it already. AI saves time, but when people stop thinking and just copy/paste what AI spits out, that’s a problem.

Getting in Front of It

Don’t wait until a “who-approved-this” moment to set some parameters around AI use. Here are some steps to take ahead of time:

1. Teach people how to use AI smartly. Instead of just focusing on how to prompt, focus on how to think critically about the output and discern what’s accurate and reliable.
2. Create clear AI guardrails. Help teams know when to lean on AI and when to double-check with humans. Give real examples that pertain to your industry and specific business processes.
3. Encourage safe experimentation. Give people a space to try AI without risk.
4. Bake AI into your workflows thoughtfully. Keep humans in the loop for key decisions and maintain oversight of AI outputs. Leave room for verification before implementing what AI suggests.

How to Spot and Avoid Chauffeur Knowledge

If you’re using AI on your own or across your team, keep this checklist handy:

• Give context-rich prompts. Don’t expect great results from a one-liner or general question. Think about how you would give instructions to a new team member who’s learning your process for the first time. You wouldn’t give them a brief rundown and expect them to know exactly what to do. Same with AI. Give it what it needs to get the job done.
• Ask follow-ups. Don’t let the first answer be the final answer. Ask clarifying questions, or even rephrase your request to compare outputs if something seems off.
• Reality check with experts. Use AI to draft, then verify with someone who’s done it before.
• Think of AI as a fast intern. Great for a starting point, not so great as your final call. It’s very helpful, but it doesn’t know the ins and outs of your business the way you do.

Being Planck-Smart About AI

This is not a case against AI, but rather a caution. AI is very useful and we’re using it in numerous ways at Trenegy both internally and to help organizations become more efficient. It’s just not reliable as the chief source of truth. If you’ve got Planck knowledge and AI is the chauffeur, be careful not to swap roles. AI-derived insights might sound convincing, but when push comes to shove, real experience should be the guide. And if you’re running a company, give your people the training and tools to get Planck-smart with AI.

At Trenegy, we help organizations leverage AI strategically to become more efficient and effective. To chat more about how we can help, email us at info@trenegy.com.