For most of the software era, building an application required a team. A product manager to scope it, engineers to build it, designers to shape it, and months of iteration before it reached production. That cost - in time, talent, and capital - acted as a natural filter. Only software that served a large enough market or solved a painful enough problem justified the investment. Everything else was handled with spreadsheets, manual processes, or off-the-shelf tools that roughly fit.
AI is removing that filter.
The shift has a name: vibe coding, a term coined by Andrej Karpathy in early 2025 to describe a workflow where developers describe intent in natural language and AI generates functional code. What began as a novelty has become a default. By early 2026, over 80% of developers report using or planning to use AI coding tools (GitHub Octoverse 2025), and an estimated 41% of newly written code is AI-generated. The tooling ecosystem - Cursor, Claude Code, Bolt.new, Lovable, and others - attracted $9.4 billion in equity funding between 2022 and 2025, a signal that investors see this as structural, not cyclical.
But the more consequential shift is not that existing developers are faster. It is that the threshold for who can build software at all has dropped dramatically. Non-technical user adoption of AI coding tools surged over 500% year-over-year through early 2026. A founder who previously needed to hire a development team to test an idea can now prototype a working application in hours. An operations lead who managed a process through email and spreadsheets can now spin up a dedicated internal tool.
This has implications for the structure of the software market itself. Andreessen Horowitz framed it well: AI is collapsing the cost and complexity of software creation, unlocking the possibility of a long tail of tools that were previously uneconomical to build (a16z). Some of that software will be personal - built for a market of one. But much of it will be enterprise software that addresses the specific workflows, edge cases, and internal processes that horizontal SaaS products were never designed to serve. These are the workflows that organizations historically papered over with manual labor or brittle RPA solutions. With AI-assisted development, they can now justify dedicated tooling.
The economic logic is straightforward. When the cost to build a custom application drops by an order of magnitude, the number of applications worth building rises by a corresponding amount. Problems that were too niche, too internal, or too low-value to warrant a development project are suddenly viable. The long tail of enterprise software demand - suppressed for decades by the cost of supply - gets unlocked.
This does not mean SaaS disappears. Horizontal platforms that own critical workflows and switching costs retain structural advantages. But it does mean the boundary between "buy" and "build" shifts meaningfully toward build. Organizations that previously accepted the compromises of general-purpose software - the unused features, the workaround processes, the imperfect data models - now have a credible alternative.
For technology services firms, this is a significant expansion of addressable demand. The explosion of custom software doesn't eliminate the need for professional services - it reshapes and multiplies it. Someone still needs to architect systems that scale, integrate custom tools with existing infrastructure, manage data governance, and maintain what gets built. The gap between a working prototype and a production-grade application remains wide, and that gap is where services firms operate. AI compresses the commodity work but amplifies the need for judgment, architecture, and integration - the higher-value layers of the services stack.
The parallel to an earlier transition is instructive. Cloud computing didn't reduce demand for IT services. It shifted what those services looked like and expanded the population of buyers who could afford them. AI-assisted development is following a similar pattern: lowering the floor for what can be built, while raising the ceiling for what needs professional support.
We expect the next several years to produce an unprecedented volume of custom software - much of it built faster, cheaper, and by a broader population of builders than at any point in the industry's history. The firms best positioned to capture that wave will be those that combine AI fluency with the architectural and integration depth that vibe-coded prototypes cannot replace.
Alten Capital invests in technology services businesses. Reach out to explore potential partnerships.