AI Can Code, But It Can't Build Software: The Enduring Need for Technical Leadership

AI Can Code, But It Can't Build Software October 27, 2025

Have you noticed a significant number of people currently seeking technical co-founders or CTOs? I certainly receive a surprising volume of these inquiries, most of them along the lines of, "Hey, I have this 'vibe-coded' app; would you be interested in making it production-ready?" I've developed a profile for these individuals: often someone knowledgeable in their business domain—perhaps a legal counsel or an account manager—but who has consistently lacked the technical skills to bring their ideas to fruition.

Why Do These Individuals Still Need Me?

This question has occupied my thoughts, and I believe it points to a crucial insight: What exactly are they unable to accomplish with Generative AI alone? This is a question everyone is grappling with, isn't it? Everyone wants to understand the capabilities of these models, or, to be more direct, which jobs are on the verge of obsolescence. The fact that I'm receiving these requests speaks volumes about the current state of software engineering. If software engineering were truly automated, no one would be searching for technical co-founders.

I believe I understand why these proposals are so prevalent. The core truth is that AI can code, but it cannot build software. This is the conclusion I've drawn after spending considerable time writing AI-assisted code and observing demonstrations from others.

There's an old adage that states: "Coding is easy; software engineering is hard." It seems reasonable to say that Large Language Models (LLMs) are already capable of automating a significant portion of coding tasks. GPT-5 and similar models can solve isolated, well-defined problems with a remarkable success rate. However, coding, in isolation, is not what most people are paid for. Building a production-ready application isn't just coding; it's software engineering.

The way I see it, coding transitions into software engineering at the point where you attempt to evolve your demo into a genuine product—which, coincidentally, is precisely when these individuals approach you with their pitches.

I don't fully understand why AI cannot yet build software (at least for now). Perhaps it relates to the fundamental nature of the job. When you develop software for a living, your primary challenge is managing complexity. The average production software typically performs numerous simple tasks. The real difficulty lies in coordinating hundreds of these simple tasks simultaneously while ensuring the entire system remains maintainable. To rephrase this in the current context: demonstrating a feature is one thing; building that feature in a manner that supports integration, expansion, and long-term maintainability is a far more arduous endeavor.

When you examine the code these individuals provide, you often realize that "making the app production-ready" effectively translates to scrapping the entire existing project and starting afresh.

I believe this insight reveals a great deal about our current position in the technological landscape.

Article by Matias Heikkilä