Could AI unlock the creation of more bespoke software? (medium.com)

AI-driven code generation is poised to change the economics of software development: if models can write, maintain, and test code at a fraction of human cost, the long-standing bias toward maximal reuse (shared libraries, design systems, microservices) may loosen. The argument: once “each line of code” becomes cheap because AI can generate features, resolve dependency conflicts, and run end-to-end flows automatically, teams could feasibly deliver more bespoke experiences—custom purchase funnels, region-specific onboarding, or campaign-specific UI—completed in days rather than weeks while reusing only portions of existing systems. That shift matters because it changes the cost/benefit calculus that has driven architecture for decades. Core infrastructure (auth, payments, observability, data layers) will still demand rigorous reuse and consistency, but product and marketing teams could iterate far faster. Technical implications include increased automation of maintenance tasks, faster feature parity between bespoke and shared code, and new patterns for when to abstract vs. customize. The risks are real: many bespoke branches multiply attack surfaces, complicate testing and upgrades, and can balloon technical debt if not disciplined. The winners will be teams that codify decision criteria for bespoke vs. shared work and pair AI productivity gains with strong guardrails for security, quality, and maintainability.