The compounding curve

Ask an AI for a status report and watch what it actually does. It hunts for where project information lives. It guesses which systems matter. It makes assumptions about what your words mean. It pulls in some wrong things, misses some right ones, and after a revision or two you have your report.

That works. It’s also the most expensive way to get a status report, because tomorrow someone else asks — and the AI does every bit of that discovery again. From scratch. For every person, every time. There is a direct cost to not being intentional about this, and most companies are paying it daily without seeing it on any invoice.

We describe the way out as a curve with five stages.

Tinker. Each person figures it out alone. People are learning, champions emerge — but every gain is siloed, and every task starts from zero.

Ignite. What works gets shared. Prompts get passed around. Better — but shared prompts are fragile. Copies drift apart, model updates silently break them, and two people running the “same” prompt get different results because the AI sees each person’s own context.

Enable. Shared prompts become shared skills, maintained centrally. Now an improvement made once benefits everyone, and someone actually owns the infrastructure. This is the first stage where the organization has AI capability rather than AI usage.

Transform. The work itself updates the shared context. The skill that completes a task records the status as it goes; decisions and blockers land where everyone — human and agent — can see them. The status report stops being expensive synthesis and becomes near-instant retrieval, accurate by construction because it was written as the work happened.

The status report isn’t solved by building a better report generator. It’s dissolved by making reporting a side effect of doing the work.

Compound. The system reviews how work gets done and improves itself. Friction gets surfaced automatically, well-understood reasoning gets replaced by code, and standard procedures improve because they are the system, not a document in a shared drive. Each improvement makes the next one easier to find. The system gets better at getting better.

Most companies sit at Tinker and assume the next step is better prompting. The early stages feel productive — everyone is busy with AI — which is exactly what makes them easy to stay in. But the curve isn’t about using AI more. It’s about paying for cognitive work once, and keeping what you paid for.

The usual worry follows: what happens to the people? The status report is work that matters and that almost nobody wants to do. When it dissolves, people do more of the work that moves the status forward and less of the work that reports on it. The role shifts from doing and reporting to directing and deciding. That isn’t headcount reduction. It’s capacity multiplication.

You don’t climb this curve with a transformation plan. You climb it by noticing what your organization keeps paying to rediscover — and deciding, once, to write it down where the system can keep it.