Eight Software Markets That AI Will Transform Differently

The text argues that AI coding will reshape software unevenly because different markets have different constraints. Where the limit is developer time or skill, AI can unlock more production and create Jevons-style growth. Where the limit is procurement, regulation, safety, or market demand, cheaper code changes less.

It walks through eight markets and separates them by likely impact. Internal tools, vernacular software, games, academic research, and startups should see strong expansion, while enterprise SaaS, government software, and safety-critical systems are less likely to grow just because building code gets cheaper.

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• Software should not be treated as a single commodity, because different markets face different constraints and different demand elasticities.
• If the binding constraint is implementation skill, AI helps a lot; if it is domain knowledge, politics, or regulation, AI helps much less.
• Jevons paradox only appears when demand is elastic, so cheaper production increases total use only in some markets.
• Internal tools are often blocked by developer time, so AI can make a large hidden backlog buildable and trigger strong growth.
• Enterprise SaaS is limited more by customer acquisition, switching costs, and market size than by coding cost, so AI mainly speeds up competition.
• Vernacular software is a new category in which non-programmers build personal tools for themselves, with disposability as an expected feature.
• Academic research software is heavily labor constrained, and AI can improve reproducibility and let researchers spend more time on science.
• Games are likely to see more content across the whole pipeline, with a larger long tail and many mediocre outputs alongside a few strong ones.
• Government software is constrained by procurement, risk aversion, and contractor incentives, so AI changes little in the short term.
• Safety-critical software faces certification, liability, and long product lifecycles, so AI may be adopted last and could create temporary quality risks.
• Startups and MVPs benefit because lower barriers let more founders prototype and test ideas with smaller teams.
• The strategic question is not how AI changes software in general, but which market a product belongs to and what its specific dynamics are.