Gate one
Granularity
The unit of AI value is the task. Not the job, and not "operations." Name the task, name who does it, and put an hourly cost on that person. If you cannot do all three, there is no project yet.
The instrument
Pass or fail, cheapest kill first, no partial credit. I run this on other people's AI projects for a living, and roughly four in ten survive it. Most of the rest die on question two. Killing a project in week two is cheap. Killing it in month six is a loan you are still paying on.
Before you start
If you own the business, this is a focus instrument: what to build next, and what Monday looks like. If you lend to one or invest in one, it is a diligence instrument: is the AI story value or narrative. Same engine, different output.
Bring one task you already suspect is bleeding money. Nothing you type here leaves your browser unless you ask me to send it.
Stage one
A strength on one gate does not offset a fail on another. If you fail one, stop, fix that, come back. Then, and only then, argue about what the thing is worth.
Gate one
The unit of AI value is the task. Not the job, and not "operations." Name the task, name who does it, and put an hourly cost on that person. If you cannot do all three, there is no project yet.
Gate two
Every AI system has an error rate, and it is never zero no matter what the demo says. So the question is what a wrong answer costs you, and whether checking the output is cheaper than producing it. Most cases die right here.
Gate three
Build where your data or your workflow is the thing that makes you different. Buy where it is a commodity. Most small businesses have no moat here, and that is fine, but then you are buying operating leverage and you should price it like opex. If your advisor never says "just buy that," get a different advisor.
Is the data or the workflow behind this task something a competitor could not easily copy?
Does a product already on the market do most of this?
Is the honest answer that the technology is not there yet?
Gate four
Before you build, say in writing what a correct output is, and have a fixed set of inputs where you already know the right answer. Without that you cannot tell whether a change helped, you cannot swap to a cheaper model when one lands next quarter, and you cannot defend the spend to the person who signed the check. No eval set, no build.
Can you write down, in a paragraph, what a correct output looks like?
Do you have, or could you assemble inside two days, real inputs with known correct answers?
No score resurrects a kill. No valuation, however pretty, waives a gate.
Stage two opens when all four gates passStage two
It survived, so it gets valued, and like any good valuation it gets discounted. These four are where otherwise good projects quietly bleed out. A bad decay score is an instruction to redesign, not to abandon. Redesign, re-score, and re-run the gates only if the redesign changed a gate answer.
Readiness
The page
The output is never a yes or no on "should we do AI." It is a short ranked list of the things that survived, with owners and dollar figures on them, and a longer list of the things you are done pretending about.
Next
One task with an hourly cost on it, the cost of getting it wrong, and the honest answer about where your data lives. That is the whole intake. Book time directly, or send me the run and I will read it before we talk.
There is no model behind this page. It is arithmetic you can check. Seemed like the best way to build a tool whose whole job is killing AI projects.