A new wave of startups is emerging: SaaS that are built with AI-assisted tools that translate a product vision directly into software. This approach, often referred to as “vibe coding,” is enabling users, solo founders, and lean teams to launch polished, scalable products at unprecedented speed.
And as the barrier to launching a software falls, acquirers may place greater scrutiny on what makes a product and the company defensible in the long term.
Acquirers are responding to the novelty and velocity of these models, but time will ultimately tell how buyers price risk, structure retention, and evaluate the durability of these companies. Some may lean in, while others may mitigate risk with earnouts or milestones.
And we are beginning to see real M&A activity in this space. Wix’s $80 million acquisition of Base44 and Lovable’s $1.8 billion valuation and $100M in ARR suggest growing demand for companies that build with AI at the core. However, it is still an early market, where defensibility matters even more.
At L40°, we’re tracking this closely not just for what it says about artificial intelligence, but for how it may impact M&A strategy across the board.
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What is vibe coding and why it’s redefining software development
Vibe coding refers to the practice of building software using AI models that interpret a founder’s high-level intent rather than detailed specs to generate working applications.
Instead of wireframes and feature lists, the inputs are often descriptions, reference designs, or product goals. The output: functional, design-forward applications or new features that are production-ready from the start without writing code.
This model dramatically shortens development cycles. What once required a cross-functional team that included software engineers, design, and product management, to mention a few areas, can now be accomplished by a solo founder with a clear vision and the right tooling.
However, the technical speed enabled by vibe-coding alone isn’t enough to drive valuation. If it turns into hype that anyone can replicate, vibe-coding could actually cap how much these startups are worth. The strategic value in these types of startups will need to be demonstrated in other ways, whether through user engagement, proprietary workflows, or emerging distribution edge.
Platforms like GPT-4o, Framer AI, and builder frameworks with built-in LLM orchestration make it possible to go from idea to launch in days, not months.
This evolution may need a different kind of scrutiny when buyers evaluate a business that goes far beyond the question of whether the product works, how much it generates and if people are using it, and sticking to it. In the future, valuations may also focus on how it was built, how defensible it is, and how much of the roadmap is institutionalized versus founder-driven.
"A.I. coding tools have existed for years. Earlier ones, like GitHub Copilot, were designed to help professional coders work faster, in part by finishing their lines of code the same way that ChatGPT completes a sentence. You still needed to know how to code to get the most out of them, and step in when the A.I. got stuck.
But over the past year or two, new tools have been built to take advantage of more powerful A.I. models that enable even neophytes to program like pros," wrote The New York Times tech columnist Kevin Roose.
What to expect in diligence when your product is vibe-coded and AI-powered
As vibe-coded startups make their way into the M&A conversation, new ways of doing diligence are still taking shape. Acquirers are learning in real time how to assess AI-built products, how to distinguish between velocity and volatility, between automation and architecture, as well as long-term focus vs hype.
While this happens, SaaS founders may have to answer questions and face a growing focus on areas that previously might have been secondary in early-stage deals.
Here are some of them:
Clear strategic differentiation
One of the more nuanced questions emerging for AI-built startups is whether speed becomes a liability when differentiation is unclear. Buyers may increasingly ask:
- What makes this product hard to replicate?
- Where does the moat lie (aka: the sustainable competitive advantage)?
Founders might need to articulate defensibility in less traditional terms—such as distribution access, retained users, or hard-to-copy UX patterns—especially when the code itself is easily recreated.
Code integrity
Even when code is AI-generated, buyers will still want to understand what they’re acquiring. They may evaluate whether the output is modular, readable, and maintainable, or whether the codebase could create bottlenecks post-acquisition.
Technical diligence teams may run static code analysis, dependency reviews, or integration tests, even for solo-founded or no-code-heavy products. While practices will vary by buyer, clear documentation helps mitigate perceived risk.
Tip: Even if your code was auto-generated, annotate it. Add structure and comments so reviewers can follow the logic.
Stack clarity and use of AI tools
Vibe-coded products often rely on a mix of hosted AI services, LLM APIs, and emerging UX layers. This makes stack transparency essential. Acquirers may ask what’s running where, who owns the infrastructure, and whether dependencies introduce technical or legal risk.
In some cases, these tools enable exceptional speed. In others, they may raise questions about portability, cost, or long-term stability.
Tip: Prepare a short technical architecture doc. List your key services, APIs, and dependencies, especially those tied to third-party AI platforms.
Founder roadmap
In lean teams, the founder often is the roadmap. That’s not necessarily a red flag, but it will likely come up in the due diligence. Buyers may explore how much of the vision is documented, how easily the existing team or a future team can continue executing, and whether the product’s success depends on founder involvement past acquisition.
Tip: Codify your roadmap. Share near-term goals and backlog priorities to show continuity, even if the current team is small.
IP ownership and AI-generated code
Because vibe-coded products are often built with external tools, IP clarity matters. Buyers may ask whether the code was generated by the founder, by contractors, or by AI tools under acceptable-use licenses. Usage terms for models like GPT-4o and frameworks like Framer AI are evolving, and diligence teams may want assurance that you retain the right to deploy, monetize, or transfer the product.
The risk of a product being easy to replicate has long been part of the SaaS and tech M&A conversation. What vibe-coding and AI is changing is how fast that replication can now happen and by whom.
Tip: Review the licenses and terms of service for any AI tools in your stack. Flag anything that could complicate transferability or ownership.
Read: AI Due Diligence: Revolutionizing Deal Assessments
How vibe coding may reshape M&A
Vibe coding is likely to play a growing role in how early-stage startups are built and how they’re evaluated (and valuated) by acquirers. As AI-native development tools become more capable and accessible, we may see more lean teams shipping production-ready software at speed and scale, without traditional specs or engineering hierarchies.
On the other hand, as building SaaS products becomes easier,whether for early-stage startups or mature companies, staying relevant, competitive, and differentiated may become harder. For acquirers, the conversation will shift from “Can it be built?” to “Why this version and what makes it hard to copy, fast?”. The question isn’t new, but the context and emphasis are.
At L40°, this evolution reflects a broader theme we see in founder-led M&A: the need to bridge innovation velocity with deal readiness, and to help founders anticipate not just how a product is evaluated, but why it might be acquired. Reach out to start a conversation.
Read: Tech M&A Market Update: 2025 Mid-Year Snapshot | L40° Insights
