Bain Uses AI Vibe Coding to Stress-Test Software M&A Targets

When a consulting firm can use AI tools to rebuild a target company's software from scratch in a matter of days, the question 'what's this technology worth?' gets a lot harder to answer confidently. According to reporting by the Financial Times, Bain & Company has built hundreds of software prototypes as part of what it calls 'outside-in' diligence, using AI vibe coding tools including Anthropic's Claude Code to recreate acquisition targets' products and test whether their competitive moats hold up.

The logic is direct: if consultants can replicate the core functionality of a SaaS platform in days, that platform's moat may be shallower than its pitch deck suggests. Conversely, features that resist replication represent genuine defensibility that warrants a higher acquisition price. Bain documented an early version of this approach in an October 2025 report focused on an AI-native healthcare software company, and the practice has since moved from proof-of-concept to standard operating procedure, according to Crypto Briefing's coverage of the FT story.

The honest caveat is what this test can and cannot capture. Vibe-coded replicas can check whether a target's user-facing features are genuinely difficult to build, but they are less likely to surface moats that live in proprietary training data, deep customer integrations, or network effects that took years to accumulate. What the reporting also does not give you is whether any specific deal was actually repriced as a result of this methodology, or what the legal and IP implications are of replicating a target's product even as a diligence exercise.

For investors and acquirers in software M&A, the more significant forward implication is this: the bar for claiming technical differentiation just went up. Companies whose moats genuinely lie in hard-to-replicate models, proprietary data pipelines, or complex compliance layers now have a cleaner way to demonstrate that, because the replica will fail in visible and documentable ways. The firms whose moats are purely interface-deep may find premium multiples harder to justify.