Software acquisitions are getting a new kind of stress test. Bain & Company is using vibecoding to create AI-generated replicas of companies' software, giving potential buyers a more concrete way to judge how defensible a target's technology really is.
The point is not to produce finished products. The point is to test whether a software company's apparent advantage can be reproduced as the cost of building software drops fast.
Why vibecoding matters in due diligence
In a traditional acquisition review, buyers study a target's product, market position, and technical claims. Bain's approach adds a practical demonstration: build a rough AI-generated version of the software and see what that reveals.
According to the Financial Times, these replicas are designed to show potential buyers how difficult it would be to recreate a target company's technology. That question has become more important as software creation becomes cheaper and faster.
The replicas also help buyers think about how a product might develop over time. A mock-up can make technical strengths and limits easier to see than a slide deck or written assessment alone.
"It's kind of the difference between seeing something in 2D versus 3D," says Rebecca Burack, head of Bain's global private equity practice.
Burack said Bain uses vibecoding "to show what a software company can and can't do, to understand where it fits in the value chain and to understand whether it is the actual code that is the defensible part of the business or something else," she said.
From specialist work to consultant workflow
Bain says hundreds of rough prototypes have already been vibecoded as part of the firm's AI due diligence work. That scale is notable because the practice did not begin as a broad consultant workflow.
What started in 2023 with a dedicated team of software engineers is now being used by rank-and-file consultants. In practical terms, that means the method has moved from a specialized technical exercise into a more routine part of evaluating software businesses.
The shift also changes what can be tested during a deal process. If regular consultants can build rough prototypes, buyers can ask sharper questions about whether a product's code, features, or positioning are actually hard to copy.
That does not mean every software business is exposed in the same way. The source describes Bain's work as a way to understand whether code is the defensible part of the business or whether the advantage lies somewhere else.
AI risk is changing deal decisions
The source article describes a market already reacting to AI disruption. Public markets are pricing in that risk, and enterprise software vendors like Salesforce and ServiceNow have lost more than a third of their value this year.
Private markets are also under pressure. According to KPMG data, the total value of private equity-led tech, telecom, and media deals collapsed by 69 percent in the first quarter of 2026 compared with the final quarter of 2025.
Against that backdrop, potential buyers are becoming more cautious. Two Silicon Valley private equity executives told the FT they had slowed their dealmaking and increased scrutiny of AI risk in every target they reviewed.
"If it's in the question box, we're not going to touch it," one of them said.
The second investor said a Bain-vibecoded recreation of an analytics platform played a role in their firm's decision to drop out of the bidding. That example shows the method is not just a research exercise. It can affect whether a buyer continues pursuing an acquisition.
What the new test asks
Vibecoding changes the acquisition question from a broad claim about software quality to a more direct test of reproducibility. If an AI-generated mock-up can quickly resemble the target's product, buyers may question how much of the company's value is protected by the code itself.
That does not automatically answer whether a company is worth buying. It gives buyers another way to pressure-test the case for a deal. It can reveal what a product can and cannot do, where the company sits in the value chain, and whether its software is the real competitive moat.
For software companies, the implication is straightforward: technical claims may need to survive comparison with fast AI-built prototypes. For buyers, vibecoding offers a way to turn AI risk from an abstract concern into something visible during due diligence.
That visibility is why the practice is becoming important in software acquisitions. As AI lowers the cost of building software, the ability to recreate a target's product becomes part of the valuation conversation. In some cases, it may become the reason a bidder walks away.