The latest thinking on Tokenomics
Episode 16·Aug 25, 2026·25 min Routing Wars: Tokenomics in Action From San Diego, J.R. Storment turns the model router story around and reports it from the buy side. Early, directional data from the State of Tokenomics survey shows how far enterprises have already gone on routing, how many are building rather than buying, and exactly […]
Only about a quarter of a platform's AI spend is typically direct model consumption. The rest is GPU, infrastructure, memory, database, compute and the labour around all of it — so a cost model that stops at the token line item misses roughly three quarters of the bill, and the value formula built on top of it is wrong.
New Foundation brings together 30 industry leaders to develop open frameworks, specifications and best practices for measuring the cost, value and return on AI spend
KEY INSIGHT: AI is not coming for the FinOps practitioner who is learning to use it. It is coming for the practitioner who is sitting still. The fundamentals of FinOps have not changed, the job is still to connect every…
MetLife’s approach to enterprise tokenomics starts with visibility, moves through optimization, and ends with measurable business value.
Day 1 of FinOps X 2026 covered token economics and the rise of AI spend management, and the role FinOps and Tokenomics play in it. The intent to form the Tokenomics Foundation was announced with supporting organizations, uniting token users and suppliers to build open best practices and standards for AI billing.
Tokenomics Foundation brings together industry leaders from major enterprise AI buyers, hyperscalers, frontier model providers, and NeoClouds to define the economics of AI infrastructure.
Organizations scaling AI confidently have visibility into cost per query, model right-sizing, and spend attribution that connects every dollar to a business outcome.
Every interaction with a generative or agentic AI system can be decomposed into input tokens (the prompt, the retrieved context, the system instructions, the conversation history) and output tokens (the generated response, the tool call, the chain of reasoning).
You buy a Ferrari. Three weeks later it clocks itself down to a station wagon.
Your PTU runs out mid-request. The call gets routed to pay-as-you-go. Same model, different cost per token.
The AI Value Paradox is the definitive podcast for founders, tech leaders, creative professionals, and business executives.
The age of abundant AI is over. JPMorgan's analyst desk reports memory chips are sold out for all of 2026.
The human in the loop a squishy human meatball that is needed in some part of every workflow on the horizon. Inelegant but accurate.
Fear is what happens to my job if agents start doing this work. The FOMO fear is what happens to my career if I don't figure this out fast enough.
What AI agent cost looks like in production right now, and how FinOps practitioners closest to the problem are still figuring out the levers.
One pattern emerging underneath all of the FinOps X talks. AI is now in everything, even the talks that aren't ostensibly about AI, and this episode is what that convergence actually looks like.
A deep dive into the framework Frederik and his colleague Maida Nazifi have built at SAP to actually do that work, at multi-billion-dollar multi-cloud scale.
