JMA Blogs - Vibe Coding vs. AI-Assisted Software Development

Artificial Intelligence (AI) is everywhere in 2026. It reminds me of the Agile wave that swept through the software industry years ago.

A new generation of consultants, founders, and influencers are showcasing impressive applications built in days instead of months. Social media is filled with stories of products launched over a weekend, startups built by solo founders, and applications created almost entirely through conversations with AI.

Much of this work is described as vibe coding, a term I've never been particularly fond of.

At the same time, software engineers are sharing cautionary tales about systems nobody understands, security vulnerabilities introduced through AI-generated code, and applications that become nearly impossible to maintain after only a few months. Both groups claim to be talking about the same thing.

The software industry has always evolved rapidly. We moved from assembly language to higher-level languages. From waterfall to Agile. From on-premises servers to the cloud. From manual testing to automation.

Each shift increased developer productivity while changing the skills required to build software. AI-assisted development is simply the next step in that evolution.

The problem is that many people use the term vibe coding to describe any use of AI in software development. As a result, disciplined engineering practices are being lumped together with approaches that ignore architecture, testing, maintainability, security, and technical understanding. Not all AI-generated software is created equally.

So, is vibe coding good or bad?

The question itself may be flawed.

Vibe coding is not the same thing as AI-assisted software development.

AI-assisted software development uses AI as a tool. The developer remains responsible for architecture, design decisions, security, testing, deployment, and long-term maintainability. AI accelerates implementation, but it does not replace engineering judgment. Humans remain accountable for the outcome.

Recently, I was prototyping a utility designed to help organizations improve the way they work. AI helped me scaffold much of the initial application. Within minutes, I had a working prototype and could begin exploring the idea.

As I reviewed the generated code, however, I noticed several service-layer files had become quite large and contained multiple responsibilities. The prototype worked, but the design would not scale in a production environment. AI had optimized for speed, not maintainability.

That observation highlights the distinction.

Vibe coding, in its purest form, delegates engineering decisions to AI. The human describes desired outcomes, reviews results, and iterates through prompts without deeply understanding how the system works. AI is not just writing the code, it is making many design decisions.

The difference is not whether AI writes code. The difference is who is making the engineering decisions.

When experienced engineers use AI to move faster, the result can be better software delivered more efficiently. When AI is used without engineering discipline, the result can be technical debt generated at unprecedented speed.

AI assisted software development is likely the future of software engineering. The ability to rapidly prototype, generate boilerplate code, create tests, and automate routine development tasks is simply too valuable to ignore.

But software engineering has never been about typing code. It has always been about making sound decisions under constraints. AI can accelerate those decisions. It can even suggest them. It cannot yet own them.

Vibe coding may be an effective way to explore ideas and validate concepts. However, once software must be secure, scalable, maintainable, and relied upon by real users, engineering judgment still matters.

The future is not AI replacing software engineers. The future is software engineers who know how to leverage AI outperforming those who do not.