Most of the engineering orgs that optimized for token spend got exactly what they optimized for: a lower AI bill.
This is the conversation for engineering leaders who survived the tokenmaxxing phase and are trying to figure out what comes next. The Rebellion starts with value delivery — and it requires a different foundation.
Why token spend is the wrong scoreboard
Size matters not. Neither does token count. The orgs delivering value at scale are optimizing for something else entirely.
What AI is actually revealing about your org
AI reduces the cost of experimentation, and surfaces signal faster. But it can’t fix a system where engineering has disclaimed ownership of value. What happens when orgs try to jump to lightspeed without solving that problem first?
What has to be true for AI to actually accelerate delivery
A feature that ships on time and goes unused is not a return. These aren't the outcomes you're looking for — learn what the right ones are, and what it takes to build a system that produces them.
