What happened
Bain Capital's private equity arm is running AI-generated replicas of software companies it is considering buying, CryptoBriefing reported Sunday, citing people familiar with the process. Deal teams feed a target's public documentation, marketing site, and any reverse-engineerable feature list into large language models, then have engineers shape the output into a working prototype.
Bain staff refer to the workflow as vibecoding, the same shorthand Andrej Karpathy popularized in early 2025 for building software by describing what you want and letting the model write it. The output is not a polished competitor. It is a diligence artifact: a running copy of the product the partnership is about to bid on, built in days rather than the months a traditional build-versus-buy analysis would take.
According to the report, the replicas are circulated internally to challenge the seller's pitch on technical defensibility before Bain commits a term sheet.
Why it matters
Software buyouts have been priced for years on the assumption that the code itself is a moat. Rebuild costs run into the tens of millions, the thinking went, so any acquirer was paying for years of accumulated engineering. Vibecoding tears at that assumption.
If a small team with Claude or GPT can replicate a SaaS product's surface area in a long weekend, the durable advantage sits in distribution, data, and switching costs, not the code. That is a very different valuation framework. Multiples on me-too SaaS targets get compressed.