Smokejumper perspectives · October 23, 2026
The first AI requirement is a better question
The information that makes AI useful is often held by the people doing the work.
Talk with Dan ↗The work in practice
Ask for the real task
A process diagram can tell you what is supposed to happen. An experienced employee can explain what happens when the order is incomplete, the invoice is unusual or a part is missing.
Ask them to walk through a recent example. What did they notice? Which system did they trust? What made them escalate the decision? These details explain why a generic automation may fail and what a useful capability must handle.
The work in practice
Listen across the handoffs
One person rarely sees the whole process. Finance, operations, sales and leadership may describe the same problem differently because each bears a different consequence.
Smokejumper connects these conversations with the company’s data and tools. The purpose is to understand the rules, exceptions and decisions well enough to form a plan, then validate that understanding through the work.
The work in practice
Give people something to challenge
Conversations inform development; they do not replace it. A prototype lets an employee say, “That is not how we make that decision,” before the assumption becomes expensive.
Use realistic examples and explicit acceptance criteria. Keep responsibility for consequential decisions clear. The employee’s contribution is not just information extraction—it is judgment about whether the result will work.
The work in practice
Build understanding while building capability
When employees help shape and test a capability, education becomes part of real work. They learn what AI can do, where it can fail and how their own judgment remains important.
That participation is central to the Innovation Center. The aim is a stronger operation and people better equipped to improve it.
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