The bottleneck is moving
For much of the software industry, the scarce resource was the ability to build: assemble a technical team, translate requirements into code, operate infrastructure and ship a reliable product. AI-assisted development does not eliminate those jobs or their importance. But it can reduce the time and specialized effort needed to produce a credible first version of many software products.
That changes the economics of competition. If more companies can create similar capabilities quickly, the existence of a feature becomes less defensible. The question becomes: who can consistently place that capability in front of the right customer, earn permission to use their data and workflow, and make adoption feel lower-risk than doing nothing?
In this framing, distribution—not code generation—becomes the more constrained capability.
Software is not the same as a business
A product can be technically functional and still fail commercially. Customers must discover it, understand it, trust it, evaluate it, procure it, implement it and keep using it. In enterprise settings, those steps may involve security review, integration work, internal champions, training and budget ownership. In consumer and small-business markets, the friction may look different, but attention, credibility and habit still matter.
AI may make the supply of software expand faster than the supply of customer attention and organizational capacity to adopt new tools. That creates a difficult environment for undifferentiated applications. A useful workflow can be copied, approximated or bundled by another vendor. Product quality remains necessary, but it may be insufficient as a moat.
The durable advantage may sit closer to the customer: an established audience, a trusted brand, a sales motion, embedded integrations, a community, a channel partnership or control of a workflow where users already spend time.
The opening for distribution-as-a-service
This suggests a potential new business layer: distribution-as-a-service. The idea is not simply advertising, affiliate marketing or outsourced sales. It is an operational system that helps software creators access qualified demand and move customers through adoption.
A distribution-as-a-service provider could combine several elements:
- **Audience access:** channels with a defined user base or buyer community.
- **Targeting and matching:** identifying which products fit a customer’s role, tools and stated problem.
- **Trust infrastructure:** vetting, implementation support, clear accountability and credible recommendations.
- **Workflow placement:** integrations, marketplaces or embedded surfaces where software can be activated rather than merely discovered.
- **Adoption operations:** onboarding, configuration, training and measurement of whether a product actually delivers value.
The distinction matters. Sending leads is a marketing service. Helping a buyer select, deploy and retain the right software is closer to a distribution system. As the number of AI-built products rises, that system could become more valuable than another catalogue of tools.
Who is positioned to win
Existing platforms, vertical software companies, service firms and communities may have an advantage because they already possess customer relationships or workflow context. They can decide which third-party products to surface, how deeply to integrate them and what commercial terms govern access.
That could produce new opportunities for builders as well. Rather than trying to own every stage from product creation to customer acquisition, a small team may specialize in a narrow capability and rely on a distributor with domain access and implementation capacity. The trade-off is clear: creators may gain reach but surrender margin, customer ownership or both.
What to watch next
The thesis is not that software creation becomes free, or that distribution alone guarantees a winning company. Complex products still require domain expertise, reliability, security and sustained product work. And customers may resist intermediaries that obscure pricing or limit choice.
The test is whether new distribution models can prove better outcomes than conventional acquisition: faster adoption, lower implementation burden, stronger retention and clearer accountability. If they can, the next valuable AI-era infrastructure may not be another tool for generating software. It may be the system that gets the right software into the right workflow—and keeps it there.
