Writing on bespoke software.

When the cost of building software collapses, markets too small for a software vendor become worth serving, and the scarce input moves to the person who owns the problem and a place to run the software every day.

When a tool becomes good enough that everyone has access to it, the tool stops being the advantage — the differentiator moves to how you combine it with everything else.

Domain experts describe a system as axes of variation, not a list of scenarios, and the test cases worth writing are the intersections of those axes.

When custom software gets cheaper to build than a platform is to configure, money that used to flow to implementation services redistributes rather than disappears.

A feature added to please an entire customer base is a liability, not an asset — it's whichever capability was chosen deliberately for one workflow that holds its value.

Software built for one user and an AI operator can enforce correctness at the model level instead of relying on a human to catch mistakes.

Software designed for millions of users carries built-in compromises — attention-driven engagement, data collection as subsidy, feature bloat — because that's what mass-market economics requires.

As AI makes coding accessible to anyone, the scarce resource stops being technical skill and becomes domain knowledge — years in an industry that no AI shortcut compresses.