Here is a line that stops most leaders cold: you should probably be spending more on tokens than on new hires.
Not as a provocation. As a budget line.
For a decade we measured ambition in headcount. The next company will measure it in inference. That sounds absurd until you look at what the boldest teams already do: they treat compute the way they used to treat recruiting, as the thing you scale when you want more capacity, more output, more reach.
But trading people for tokens is not the interesting part. The interesting part is what it lets you build.
Hold agents to your best hire, not the busywork. Most teams benchmark their agents against the work nobody wanted: the tickets, the copy-paste. Move the bar. Measure the agent against your best hire on the dimensions where software can genuinely win: speed, availability, consistency, breadth, the patience to redo a task a hundred times without tiring. On several of those, the honest answer is already “the agent wins.” Where it is not, you know exactly what to build next. Average was never the target. Your best person is.
Run an agent per customer, not one assistant for everyone. The old instinct is a single large system that serves the whole market. The frontier looks different. Picture a dedicated agent for each customer: its own isolated environment, its own persistent memory of that account, spun up on demand and torn down when the work is done. Not one model juggling everyone, but thousands of focused instances, even tens of thousands, working in parallel every day. No human organisation can hire at that scale. A software one can. I already run whole fleets of agents in parallel on a single problem, each in its own isolated workspace. That is the real shift: you stop asking who to assign and start asking how many instances to spin up. And what you can offer, in personalization and in scale, changes completely.
Fear the timidity, not the boldness. Betting the org on agents brings real fear: of wagering wrong, of what it means for the team, of the sheer speed. Not just how fast you have to execute, but the pace of transformation the market now forces on everyone. It also brings a justified excitement at everything that suddenly becomes possible. That mix is normal. It means you are doing the work, not talking about it. But what you should really be wary of is the opposite: not going far enough, tinkering at the edges when the whole organisation needed rethinking, and bolting AI onto the safe, incremental version instead. That is what a serious, ambitious leader should be afraid of.
Train everyone, then let them ship. This is the step companies skip, and it matters most. Do not stand up a small AI team and wall it off. Teach the whole company, from the CEO to the newest frontline hire, how to build with agents. Not a lecture series. A few intense weeks that end with something real in production. When someone in operations, someone in support, and an engineer can each put a working agent into the business, you no longer have an “AI initiative.” You have an AI company.
Which leaves the only question that really counts.
Most companies are asking how to add AI to what they already have. It is the wrong question, and you can hear it in the answers: a chatbot bolted to the side, a copilot in one tool, a pilot that never leaves the lab. The better question is harder and far more useful. If you were starting this company today, from scratch, knowing what agents can now do, what would it look like?
Answer that one honestly and most of your roadmap rewrites itself.
So before you sign off on the next headcount plan, run the other version. Same goal, same budget, but agents first, humans where they are irreplaceable, tokens where they are not.
What would you build if you started today?