Software systems work best when they’re connected to each other. For years, incumbents use deep integrations as a competitive moat.

But AI upends this dynamic.

A few of our portfolio companies are starting to develop integrations with AI in a matter of hours, completely upending the two or three quarter timeframes of classic enterprise integration development.

This enables two important impacts to the sales cycle.

First, the integration a customer desires can be built during the sales cycle, demonstrating the startup’s technical agility.

And second, within a few quarters, a startup can have a vast number of integrations demonstrating breadth, establishing credibility & nullifying sales objections.

Developers working with coding agents drafting a PRD, developing integration tests, and then asking the AI to iterate until it succeeds.

In the medium term, companies that are able to use AI to write integrations are better equipped for agent-to-agent communications.

If one AI can develop an integration into another AI, well, then those two systems can talk together seamlessly irrespective of changes within API specification, network communication challenges, state management issues, historical problems that have plagued integration.

This sets the startups up well for the next generation of protocols, including model context protocol and agent2agent. AI generation of those interfaces further separates startups from incumbents.

With fast integrations, startups can shorten sales cycles and be among the first to build and deploy a complete AI architecture.