Vibecoding is becoming a deal-breaker test in software acquisitions
Vibecoding is now being used to decide whether one company should buy another. Vibecoding means building software mostly by telling an AI what you want and letting it write the code, instead of typing the code by hand. According to a report by The Decoder, the consulting firm Bain & Company uses this trick during deal checks. Before a big buyer pays for a software company, Bain asks an AI to quickly copy that company’s product. If the copy works well, it raises a red flag: maybe the product is not as special as the price suggests.
This is a big shift. For years, the secret code inside a software company was treated like gold. Now, when an AI can rebuild a lot of it in a short time, buyers are asking a hard question: is this code really worth all that money?
What is happening during M&A due diligence
M&A means mergers and acquisitions, which is just companies buying or joining with other companies. Due diligence is the careful checking a buyer does before paying. It is like inspecting a used car before you buy it.
The Decoder reports that Bain & Company now builds quick AI-made copies of a target company’s software as part of this checking. The goal is simple. If a cheap, fast copy can do most of what the real product does, then the real product may not have a strong moat. A moat is the special edge that keeps rivals from easily copying you.
Rebecca Burack, who leads Bain’s global private equity practice, described the value of these copies in plain terms. She said it is “kind of the difference between seeing something in 2D versus 3D.” The firm uses vibecoding, she said, “to show what a software company can and can’t do, to understand where it fits in the value chain.” Private equity, by the way, means investment firms that buy whole companies, fix them up, and later sell them for a profit.
From a special team to everyday consultants
This is not a one-off experiment. The Decoder says the practice began in 2023, when it needed a dedicated team of software engineers. Now, ordinary consultants at the firm can do it. They have reportedly built hundreds of these prototypes. A prototype is an early test version of a product.
That change matters. When only expert coders could copy a product, it stayed expensive and rare. When regular staff can do it with AI tools, the test becomes a normal part of almost every deal.
When the AI copy kills the deal
These copies are already changing real decisions. The Decoder reports that one investor pulled out of a bidding war after Bain built an AI copy of an analytics platform the investor was thinking of buying. The copy showed the product could be matched, so the buyer walked away.
One anonymous private equity investor put the new mood bluntly. “If it’s in the question box, we’re not going to touch it,” the investor said. In simple words: if there is any doubt that AI can copy the product, the deal is dead.
The market backdrop
This caution is happening while software deals are already cooling. According to KPMG data cited by The Decoder, the total value of private equity deals in tech, telecom, and media fell by 69 percent in the first three months of 2026 compared with the last three months of 2025. That is a steep drop in just one quarter (a three-month period).
Public software companies have also taken a hit. The report notes that big enterprise software vendors such as Salesforce and ServiceNow lost more than a third of their value in 2026. Two Silicon Valley private equity firms have reportedly slowed their dealmaking and added more checks for AI risk.
| Key fact | Detail (per The Decoder / KPMG) |
|---|---|
| Who runs the test | Bain & Company, during deal due diligence |
| When it started | 2023, with a dedicated engineering team |
| Scale now | Hundreds of AI prototypes, built by regular consultants |
| PE tech/telecom/media deal value | Down 69% in Q1 2026 vs Q4 2025 (KPMG) |
| Enterprise software vendors | Salesforce, ServiceNow lost over one-third of value in 2026 |
| Real impact | At least one investor withdrew from a bid after an AI copy |
Why it matters (especially for India and founders)
For founders, the lesson is sharp. If your only edge is the code itself, that edge may be shrinking fast. AI tools are getting strong enough to rebuild many features. New, faster models keep raising the bar, like the recent GLM-5.2 AI model and low-level speedups such as the MoonMath AMD MI300X attention kernel. As coding gets cheaper, raw code becomes easier to copy.
This is a clear signal for India’s large software and SaaS scene. SaaS means software sold as a monthly or yearly subscription over the internet. Indian startups that hope to be bought one day cannot lean only on clever code. Buyers will now test how easily an AI can clone it.
So what is left as a real moat? The things an AI cannot quickly copy. That means loyal customers, hard-to-get data, deep ties with big clients, strong distribution, brand trust, and tricky rules or licenses. Founders who build these will look far safer in a deal.
FAQ
What is vibecoding in simple words?
Vibecoding is building software mostly by prompting an AI to write the code for you, instead of writing every line by hand. You describe what you want, and the AI produces working code.
Why are acquirers using it in due diligence?
To test how special a product really is. If an AI can quickly build a working copy, the buyer worries the product has no strong moat and may not be worth a high price.
Has this actually stopped a deal?
Yes. The Decoder reports that at least one investor dropped out of a bid after Bain built an AI copy of an analytics platform that showed the product could be matched.
What should founders do about it?
Build moats that AI cannot copy fast: loyal users, unique data, strong distribution, brand trust, and key partnerships. Do not rely on the code alone.
The takeaway
Vibecoding has moved from a fun hobby to a serious test in big money deals. When an AI can copy a product quickly, the code alone is no longer proof of value. For buyers, it is a sharp new tool. For founders, it is a wake-up call to build an edge that machines cannot rebuild overnight.
