The consultancy is the first Bet
Issue 001 introduces Sparker.ai’s operating model and puts its first commercial assumption under the same evidence standard it recommends to clients.
What changed?
Sparker.ai now has a defined first offer: the AI Product Decision Sprint.
That is not proof that the market wants it. It is a hypothesis specific enough to test.
Why does it matter?
A consulting practice can become as assumption-heavy as the products it advises. It is easy to spend months polishing a service menu, publishing broad ideas, and interpreting attention as demand.
Sparker.ai should meet the standard it asks clients to use: define the decision, limit the investment, collect evidence, and stop when the evidence says stop.
This week’s Bet
Hypothesis: product and technology leaders will pay for a short engagement that helps them decide whether and how to pursue one AI opportunity.
Experiment: publish the offer, speak with at least five qualified leaders, ask for a paid pilot, and record the objections.
Investment cap: 90 days and 20 prospect conversations.
The evidence
The offer and evaluation criteria exist. Market evidence does not—not yet.
That distinction matters. Preparation is an input. Buyer behavior is evidence.
The current decision
Researching. The next step is to test whether the problem feels urgent in the buyer’s own language and whether a clear decision is valuable enough to fund.
The practical meaning
When your organization says an AI initiative is “strategic,” ask what evidence would cause the team not to invest. If there is no acceptable answer, the initiative is not yet being managed as a decision.
The invitation
If your team is evaluating an AI investment in the next six months, start a Decision Sprint conversation. If you are building your own decision system, reply to the newsletter with the hardest stopping rule you have had to set.