In the era of vibe coding, is code really a valuable IP when exit?

I was recently talking to a friend who is the VP of engineering at a sizable SaaS company owned by a PE fund. We spoke about buy vs build for some of the new AI initiatives. He mentioned that the company has a mandate that they are not willing to hire third-party vendors to participate in the development process even though the machine learning engineer post has been vacant for a while and they also do not have internal resources that have the experience developing AI features in production. The primary reason is that the leadership fears that the code the vendor develops will hurt the value of the IP as the company may be put in the market by the PE owner in a couple of years. I am in no position to criticize or endorse the philosophy. But it does bring up a good debate: in the era of vibe coding, is the codebase of a SaaS company really the valuable IP that calls for huge valuation like in the past? What is the enduring value of a SaaS when someone buys it? Talent? Market Access? Customer List? Suffice to say, one thing is only valuable in the eyes of the beholder. That said, I am curious in this age of vibe coding and era of producing AI agents faster than McDonald's Drive Through, is one's codebase really a valuable IP that can meaningfully add value to a buyout?

I believe it is, but only to a specific type of company. In general, for a SaaS company that is known for reliability when serving millions of customers, absolutely. For example, if Zapier is up for sale today, no doubt the codebase that sustains that many users that fast is not something vibe coding can easily replicate. Another example is complicated industry software like Synopsys, I also believe it is a heavy Yes. However, a long-tail SaaS that serves a very niche field that is less mission-critical like a playground reservation software, I'd argue probably not.

That brings up a second aspect, the original debate was about AI features. Can one reliably vibe code AI features? Well, can one? Yes, one can. That's why LinkedIn is flooded with thought-leader-turned-AI-experts. Is it useful? Probably on a small scale. But AI features have their very unique nuance. First, AI features invariably read data, which immediately invites a few problems: first is security. Think of it this way, can OpenClaw merge multiple financial statements in Excel format on a computer and do a good enough job? Very likely yes. But should an accountant allow it? I question it since it involves someone else's financial data and it could be a big risk if there is any type of malicious attack. Second, AI features more often than not take actions: for example, can Claude Chrome take over my AWS Root Access and grant my Fargate app VPC access to my RDS? I am sure it can. But can I trust it to do so by opening the RDS to 0.0.0.0/0 ? I don't think I can. Because Vibe Coding often means the requirements are less well defined, refined and thought out. A lot of these things can evolve over a long period of time with trial and error. Unfortunately, trusting AI features to take actions in a system with a lot of users being affected is just not a good place to start with unless someone very experienced can oversee what it is trying to do and why it is doing it.

Third, and this is one people really overlook, is eval. How do you know your AI feature is any good? With normal software it is straightforward: you run a test, the output either matches or it does not, done. AI is a completely different animal. You ask it the same question twice and you get two different answers. So now what? Now you need proper benchmarks, you need people who actually know the domain to look at the output and tell you if it is acceptable, and you need monitoring because the model's behavior drifts over time especially if you are using a third-party LLM API that updates without telling you. Think of it this way: if you built a RAG feature on top of GPT-4 six months ago, it probably behaves differently today than when you shipped it. Did anyone notice? Did anyone measure it? That kind of ongoing vigilance is not something you vibe code in an afternoon. Teams I have worked with spent months building evaluation pipelines and they are still iterating on them. That is institutional knowledge. And I would argue it is worth far more than the codebase itself.

All of this makes me circle back to the original question: what even is the IP here? When a PE fund looks at a SaaS company and says we need to protect the codebase, I have to ask, protect it from what exactly? Someone rewriting it? Anyone with Cursor and a weekend can rewrite a CRUD app. Code is becoming a commodity faster than anyone wants to admit. What you cannot replicate is the team that knows why that one API endpoint has a 30-second timeout instead of 10. The runbook for when the payment processing queue backs up on Black Friday. The engineer who remembers that one customer on the enterprise plan whose webhook integration breaks if you change the JSON field ordering. That is the real IP. Good luck vibe coding that.

So here is what I would tell my friend. I get it, the PE fund wants to protect the asset. Totally understandable. But let us think about what actually happens in practice. You will not hire vendors because of IP concerns. You do not have internal ML talent because the role has been open for months. So what ships? Nothing ships. Meanwhile the competitor down the street who is less worried about who touches their Git repo is already on version three of their AI feature. They have learned what prompts work, what guardrails to put in place, which use cases customers actually care about. They are building all that institutional knowledge while your team is still in a meeting debating whether to even start. I have seen this play out multiple times now. Speed of learning beats purity of ownership. Every time.

And here is the real kicker. By trying so hard to protect the value of the IP for a future sale, they might actually be destroying it. Think about what a buyer sees in 2026 when they do due diligence on a SaaS product with zero AI capabilities. They are not going to say wow look at this beautifully pristine vendor-free codebase. They are going to say why does this product have no AI features when literally every competitor does? And honestly that is a much scarier conversation to have with a potential acquirer than hey we brought in a specialized vendor to help us build our ML pipeline two years ago.

Look, code is a means to an end. Always has been. The product is not the codebase, the product is the experience, the reliability, and the outcomes you deliver to your customers. If this whole era of vibe coding and AI agents has shown us anything, it is that writing code is getting cheaper every single day. What is not getting cheaper? Knowing what to build. Knowing why to build it. And knowing how to keep it running when real people depend on it. That is the IP worth protecting.