The three-week proof of value: de-risking AI before you commit
Six-month AI roadmaps fail for predictable reasons. A tightly scoped proof of value tells you in three weeks what a roadmap can't.
Why big AI projects stall
The failure pattern is consistent: months of planning, a large budget approved on faith, and the first real accuracy numbers arriving too late to change course. By then the sunk cost defends itself.
The alternative: prove value in three weeks
A proof of value is not a demo. It's a narrow, honest test of the riskiest assumption — usually "can the model do this task accurately enough on our data?" — with real inputs, an eval harness, and a number at the end.
What three weeks buys you
- Week one: real data in, baseline out. No slides — a working pipeline on your actual documents or tickets.
- Week two: iteration against the eval. Prompting, retrieval, fine-tuning — whatever moves the number.
- Week three: a decision-grade readout: accuracy, cost per task, and a production roadmap — or an honest recommendation not to proceed.
The decision, not the demo
Either outcome is a win. A green light backed by evidence earns real budget. A red light after three weeks costs a fraction of the same discovery made in month six.
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