AIWA "The One Thing" #28: Same Intelligence. 20x the Price. Sharp CFOs + CTOs Aren't Cutting Jobs, They're Funding Them. Especially Entry-Level.

Everyone is spending more on AI. But how well are they doing it?

Based on some outstanding research from Ramp, their data tells quite a story.

*"How much does it cost to be AI-pilled?" by Ara Kharazian of Ramp 06.26.26

“Price is what you pay. Value is what you get.” - Warren Buffett

Intelligence (tokens), available on demand, has a 20x cost difference.

So when one token costs $0.07 and another $1.42, how do you know which one to pick?

Are you paying for a chainsaw when all you need is scissors? A Lamborghini when a bicycle gets you there?

Tokens are the unit of cost that covers inference. Inference is the roundtrip that happens when you query ChatGPT. You ask a question, the model thinks and responds.

You delegate a task to Claude Cowork and the agent executes a number of automated workflow steps on your behalf, that’s inference. That’s what you’re paying for.

Cost = the model you pick x the tokens it burns.

This is where chainsaw vs scissors, bicycle vs Lamborghini and the 20x comes into play.

Tokenmaxxing is over.

*AIWA TOT #23

*AIWA TOT #27

Show me a CFO + CTO on the same page about how they deploy AI token capital to ensure right model, right token, right job, right team and I’ll show you a company that’s about to rip a whole lot of market share from their competition.

Disciplined token allocation frees capital as you stop overpaying for intelligence.

So what are the implications and where do the disciplined ones put that freed capital?

1: They build intelligent systems that diversify and protect optionality.

*"How much does it cost to be AI-pilled?" by Ara Kharazian of Ramp 06.26.26

2: They hire more people.

*"Companies hire more after AI adoption" by Ara Kharazian of Ramp 06.30.26

3: Especially entry level.

*"Companies hire more after AI adoption" by Ara Kharazian of Ramp 06.30.26

Humans + Machines. Never Humans vs. Machines.