Note
Business → Systems → Data → AI → Products
The path matters: business pressure, system shape, data reality, AI leverage, product interface, reliability, and proof.
Context
Starting with AI can skip the problem. Starting with business pressure reveals what the system must change, who owns the workflow, and which evidence would show the change mattered.
Observation
Systems clarify repeated work. Data records what the system can observe. AI only becomes useful when those two layers are honest enough to support a product promise, eval path, and failure boundary.
What this changes
Product judgment is the final translation: what gets exposed, what stays hidden, what proof is public, what reliability is promised, and what the user can safely do next.
Open question
Where is the current bottleneck: business clarity, system shape, data quality, AI behavior, reliability, or product interface?