Early-stage stack decisions are not about technical merit. They are bets about constraints: iteration speed, staffability, and time-to-next-primitive.
Creating a comprehensive Markdown page that includes all possible GitHu
The obstacle to AI adoption in an established company is rarely the model. It is judgment that lives in people's heads and was never captured.
Token counts and adoption dashboards measure activity, not impact. To know if AI helped, measure whether the outcomes you already trust actually moved.
Your scaling constraint is not headcount. It is how many people can take an idea from ambiguity all the way to shipped. Most companies have too few.
In a regulated codebase, a passing test suite is not a compliance check. AI writes code that works and violates rules nobody encoded as a test.
Startups reward competent rule-breakers. Regulated industries change the stakes. The real skill is telling soft rules from load-bearing ones.
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