The Thing Is Not The Thing
Sangeet Paul Choudary, observing that "in an AI economy, the by-product may become more valuable than the product":
Most firms treat drafts, rejected options, failed experiments, intermediate reasoning, and abandoned designs as waste because the economic objective has historically been the finished output. But those discarded iterations contain information about why decisions were made, which alternatives failed, what trade-offs were considered, and how judgment evolved.AI can turn that exhaust into reusable capital. Once intermediate work becomes machine-readable, the firm can search it, recombine it, identify conceptual gaps, train future workflows, and personalize outputs for different contexts. The finished product is only one bundle assembled from a much larger underlying knowledge base.
Publishing provides a strong example. A traditional publisher monetizes the finished book while most research notes, alternate structures, case material, rejected arguments, and conceptual connections disappear economically once publication occurs. An author who converts that material into a structured knowledge graph can produce multiple new narratives, detect gaps in the underlying theory, answer context-specific questions, or create entirely different products.
The strategic inversion is important: firms may discover that the asset was never merely what they shipped. It was the accumulated trail of learning generated while figuring out what to ship.
Another reason to make the work legible.
The obvious move is to use AI to finish the thing faster.
The more interesting move is using it to make the trail useful: the drafts, dead ends, trade-offs, taste, arguments and almosts.
The thing you ship still matters.
But the more valuable thing may be the compounding learning loop that got you there.