Agentic AI FinOps Playbook

An exclusive guide to tokenmaxxing AI costs in your organization

Jevons Paradox is causing your model bills to grow faster than anyone planned, buried in infrastructure invoices, and distributed across dozens of teams with no coherent view of what they’re buying or why.

Over the last few years, companies have pushed to become AI-ready by pushing their employees to use AI as much as possible

But now the bills are coming in, and it’s not nice.

If your CFO is starting to ask questions and the CTO doesn’t have clean answers, its a tough spot to be in.

So I wrote this playbook as a six-phase programme for getting that situation under control. I figure that, as usual, this is not simply about cutting costs, but building the institutional capability to manage AI spend the same way mature organizations manage cloud spend. If some terms are unknown, I added a glossary at the end.

Tokenmaxxing isn’t about spending less. It’s about spending right.

I did not invent the term, but I’ve been using it since my last post on the topic.

Tokenmaxxing is about extracting the maximum business value from every token, not just minimizing them and organizing them into 6 sequential phases

Each phase has a clear goal, a set of concrete actions, and named departmental owners.

You can run this progressively, Phase 1 before Phase 2 or adapt it to wherever your organization already is.

I will now go into more detail for each of these phases, but I believe they are fundamentally clear, and this document serves as a high-level playbook, rather than a deep dive.