Key Takeaways

  • Danielle Fortier, partner at Cooley, observes that generative AI has removed historical resistance to copying and sharing proprietary codebases in corporate carve-outs.
  • Deal teams historically treated source code as the primary proprietary asset, leading to protracted battles over Transition Service Agreement (TSA) system access and intellectual property splits.
  • Sellers and buyers now routinely resolve codebase entanglements by duplicating shared software assets, allowing each party to walk away with identical underlying code.
  • Valuation moats in tech carve-outs have shifted away from raw code syntax and toward distribution, proprietary data access, and customer contracts.

The Disappearance of Code Paranoia

For two decades of software buyouts, the codebase was treated like state secrets. Carve-out negotiations frequently stalled over source code access. If a parent company sold an enterprise business unit that shared underlying infrastructure with another division, legal teams spent weeks debating IP ownership. Corporate sellers feared that granting an acquirer codebase access under a Transition Service Agreement (TSA) would risk their remaining business.

That dynamic has broken down. As Cooley partner Danielle Fortier notes, the market used to treat raw software as an unassailable advantage. “Back several years ago, and for most of my career, when you're doing a software deal, the code was really important, and kind of the secret sauce of the business,” Fortier said. “There used to be a lot more hesitation about either sharing code or, in the case of a TSA, giving the other side access to code beyond what they are using for the acquired business.”

Generative AI changed that calculation. When automated coding models can write, inspect, and refactor code in minutes, raw syntax no longer commands defensibility. Deal teams recognize that proprietary scripts can be rewritten cheaply. The technical wall has fallen.

The Copy-and-Split Playbook

The direct result is a simpler operational playbook during separation diligence. Instead of designing complex licensing structures, restrictive covenants, or walled-off code repositories, deal parties now choose a simpler path: duplicate the repository and move on.

“With AI, the level of protectiveness around code has definitely changed,” Fortier observed. “People are more willing to say, well, the source code is not really our secret sauce; our secret sauce is our customer relationships.”

This shift alters how dealmakers untangle technical overlap. Fortier points out: “Both businesses use the same piece of code. We are just going to copy that out, and you guys can take that piece and we will keep our piece and just go on your merry way.” Less sensitivity around proprietary rights makes separation faster. Legal teams spend fewer billable hours redlining code schedules, focusing instead on vendor contract repricing and pre-closing operational gap diligence.

Where Moats Migrate

When software syntax is commoditized, enterprise value concentrates in what cannot be generated by an algorithm. Buyers no longer pay software multiples for clean code alone.

Instead, carve-out underwriting centers on distribution density, existing enterprise integrations, and data history. If two competitors hold identical copies of the same core code repository, the winner is determined by account control and workflow lock-in. Sponsors who once spent weeks auditing software line counts in diligence are redirecting technical teams toward customer churn data, API dependencies, and sales distribution. The legal documentation reflects this reality: code separation terms are shrinking, while customer assignment provisions and commercial agreements take center stage.

Why It Matters

This shift signals that software defensibility has migrated from code architecture to customer and distribution moats. Sponsors pursuing software carve-outs can compress technical separation timelines, but they face higher stakes around contract transitions and operational gaps. In an environment where AI makes software easily replicable, acquirers cannot rely on proprietary IP alone to support exit multiples.