Tokenomics

I wrote this for The Meg & Amy Show newsletter 20 - cross posting here.

Token economics have entered the chat

In mid 2025 I began to worry about how we were accounting for AI spend. I asked people who are smarter than me on this topic and got deeply unsatisfying responses. This is when I knew things were going to get awkward.

Having run large scale operations with massive margin improvement goals, I understood instinctively that the math would become uncomfortable quickly. When you run massive organizations you realize that small "perks" become expensive. Giving everyone a t-shirt or a spot bonus or even a clutch patagonia jacket at a startup is an easy decision. Doing that for an org 10x the size might make you think and for a group 100x you start to feel pretty uncomfortable, especially when you recognize that budget miss could result in layoffs to reconcile the gap. You have to ask yourself is giving everyone a t-shirt the right call in a tough budget year? Maybe it is, but maybe not. Maybe you decide it isn't and the layoffs happen anyway. 

If you follow the tokenmaxxing stories you notice that people are beginning to see what I was concerned about. Side note, this is a recurring pattern for me, I've learned that most people don't understand what I'm talking about until the problem is real for them. It makes me empathize with Cassandra. 

With each phase of #AI transformation, I have been uncomfortable in ways that I struggle to articulate. I was able to write a note about the early days of AI Fluency programs and I have seen some good discussion on the obvious challenges of token leaderboards. The challenge for me goes a bit past Goodhart's law, but that is a solid place to start. Measuring a thing is good and also a risk, especially when the "why" gets lost along the way (as is VERY apt to happen in large groups, and with people who have been conditioned to expect a playbook in lieu of first principles understanding).

So instead of just living in the world of I told you so, I want to offer a few suggestions on how to break down this problem. I am using a financial tracking lens because I believe this is the missing piece right now, not because this is the only way to look at opportunity. I also want to remind everyone that the opportunity is new value capture. Capital allocation should be in service of that goal. 

Given my intention is to Invent the future, I need more people to be thinking about sustainable innovation vs. the current behaviors (YOLO'ing tokens and hoping something smart emerges). 

Financial tracking

You need to be tracking both usage and budget in the following buckets. It's going to be hard to get the specificity you need - instead of waiting for precision expect to refine as you go, especially for those costs that have to be allocated vs. attributed. Take a guess and document your assumptions - refine over time but whatever you do get started now.

1. Cost of Sales - break down AI that you use to generate revenue. This is both what is used in the delivery of your product AND what is used for customer acquisition. Keep track of tools, FDE and tokens and evaluate unit economics and margin closely. You are likely to observe that your intuition for how your business works and what "good business" looks like will change dramatically in the next few years lean into that learning. Ask a lot of new questions to get grounded in the numbers.

2. Internal IT Costs - The cost of worker productivity is also changing. There is a subset of the AI costs that looks a lot like email or laptops or cellphones. Things that are non-negotiable for work and generally beneficial to the business in broad ways. You don't monitor who can use excel today- you trust your workforce to use excel if they need it. Microsoft is counting on this (and Google of course) in their growth plans and this general spend should not be confused with the bigger value prop of AI. This should be where you capture your existing vision of "30% productivity improvement".

3. AI Initiatives - here is the big one and where there a lot of confusion is living. I think many businesses are beginning to realize that not all AI projects are worth the cost and yet sorting that out when both cost structures and organizational priorities are evolving quickly is very hard. Here is the place where most businesses need to put on their transformation hats and ask the bigger questions - things that used to live in the build/buy/partner, business transformation and [portfolio/business/product] Strategy domains. A few things to think about in this bucket:

   1. Pick a small number of specific Initiatives - stop with the thousand flowers nonsense, you don't have time for that anymore. It is the job of leadership to pick the right initiatives that will be the most impactful for your business goals. It is ok to lack certainty and it's totally fine to adjust this over time, but getting moving on something specific and strategic will be more helpful for everyone than becoming a chaos factory of token usage. 

   2. Directionally correct metrics are better than no metrics - Token usage might be the best metric in the early days. Especially getting most people out of zero. Getting started does matter, but be thoughtful here because the "for what" matters a lot. It is the job of leadership to and clarify the success outcomes you are focused on, and to make sure you are also measuring progress toward real goals. Odds are early metrics on outcomes are hard. This is why you need to read Patty's book Move - specifically the chapter about control points and limping cows (chapter 4). 

   3. Track costs ruthlessly - continue to ask yourself if you are making the right bets and if you are allocating the right amount of capital to the opportunity. Here you must track both AI costs, opportunity costs and human costs. This is not to suggest that you shouldn't be willing to incur extra costs but financial measures are the language of business and it is important for all stakeholders to understand the bets being taken. Cost transparency will do more to drive alignment than you realize. Help bring the organization along with clear financial transparency and measurement.

The pendulum is shifting from no one thinking about this, to people believing that tokens are the new unit of economic value or the new sales and marketing or it's nothing or everything. Winning organizations will make real bets on where and how to leverage AI to deliver (or expand) their strategy. The gap is widening, time to get moving.

Or if you prefer a video watch this instead.