AI Has No Wisdom and Neither Will You

There's a continuum between "vibe coded by someone with no technical knowledge or inclination" and "hand written domain driven design development". You can absolutely use coding agents AND have maintainable code. But yes, the coding agents will not magically make everything maintainable if you don't tell them to.

"Code maintainability and good architecture don’t have good measurements that we can apply"

Who has no wisdom? There are dozens of ways to measure code maintainability. Cyclomatic complexity is just one.

Nothing stops you from wiring up something like SonarQube metrics to your agentic coding workflow.

In the beginning of August 2026, I started a hobby project: building a MongoDB-like database. I have 20 years of industry experience and a master's degree in computer science, so I followed a disciplined, spec-driven development model using Claude, Kiro, Qwen Coder, and Cursor.

The first version was built in about two weeks of part time work. Then I started exploring. I learned relational algebra, researched almost every kind of database, reworked the internals, built a small relational algebra layer, a query planner, and an executor, covering everything from the backend storage to the query language. I learned more in those two months than in the previous 20 years.

Did I care what code the agents wrote? No. I read zero lines of generated code. What I cared about was correctness, verified through tests, and the high-level product features. For the first time in my career, I acted as a senior product manager, steering the project along the right roadmap. Without AI, I wouldn't have been able to do that.

When you have superpowers in your hands, you don't need to worry about the laundry. For the first time in my career, I can produce code in C, C++, Java, .NET, or any other language. Sometimes it takes me longer than a senior developer in that language, but does that really matter? Absolutely not.

Writing documentation and code by hand in 2026 is like driving a horse and buggy. It doesn't matter how skilled you are with the reins; you'll never compete with a car.

My hobby db pr […]

Maybe I've just given up, or maybe I'm a realist? But I fully believe AI will just...catch up with everything?

There's so much money in it right now. There's such a momentum. There are zero incentives to slow down for those that are in charge.

I've accepted that in 5-10 years, the vast majority of human devs. and engineers will not touch a single line of code. It'll be small increments, with a couple of big ones here and there.

And there will not be any triumph for those that hold steadfast to the principle of human coding. They'll be tiny boutique shops that do custom stuff, in the same way cobblers are to the mega shoe factories.

Man.. just code, let people build, design, adjust. Who cares? Who are these people writing these posts? Why should we give anything they have to say warrant? These posts are getting old, very quick.

> I’m going to make a prediction of my own… In the future we will see more and more companies proudly boasting their “NO-AI” policy as a competitive advantage. And they will be right

I'm going to make my own prediction: this isn't going to happen

Most software is not good, using these rules. And that is written by human developers. The problem is that most software developers have less than 5 years experience. The community doubles every 5 years. Experience is scarce. So AI, learning from all the stuff online, does not learn great code, it learns from available code.

You can make it produce better code, if you do the hard work of defining better in terms the AI understands.

I've been trying to find a way forward with AI generated code, using my own definition of 'good architecture', and results with chatgpt 6 are promising. Not perfect, but good enough.

I used a book I was writing as input, you can read an unfinished version of it here: https://programming-for-wizards.dev.muze.nl/

(Still working out the kinks of the underlying software)

The other approach is to explicitly keep the whole decision tree as a causal chain in a repository: https://github.com/muze-labs/spiral-developer

Still testing that one out.

I've read a lot of posts similar to this recently and keep asking myself if the past 20 years of my professional experience was that atypical.

I’m sure there are companies who are writing “perfectly maintainable and highly scalable code”. However, for half of my career I’ve been brought into startups to clean up the mess created by engineering teams.

While AI may create an unmaintainable mess (I’m not totally convinced), from my perspective many (not all) engineering teams have been doing that all along. #v2 #refactor

I believe many of us here knows that the idea of a simple prompt to make something more than a sketch or a prototype don’t really work.

Unless you steer and understand what an LLM will produce, you will end up with something that possible ”works” that has no future plans baked in. Suno generated music has a very unpleasant feeling of sounding like competent music with nothing to say.

I’d say that vibecoded software is similar. My speculation is that current breed of LLMs do not have an I, and I really don’t exactly knows what goes on in those vast arrays of numbers. There’s something there perhaps, but no person.

Still even in the short term someone wants to run a company that expects responsibility of its organisation, how are you going to exact that responsibility if no one actually understands how the thing the organisation makes works.

Maybe a simple crud system can be made fast and loose. But a bank settlement? A pacemaker? Deletion of sensitive data?

I know some companies are betting on that the agent can fix what the agent breaks. It may be true, but up until now everytime I try to relax on strict steering of an agent it tends to go badly rather fast.

Again I don’t know, but I think as long as we don’t invent synthetic persons with their own ideas on what they want to do, which btw opens a massive can of worms, the current situation will persist. However clever the current breeds of systems are.

I do want to state that a find the current trajectory fascinating. I use L […]

> Fact is, vibe-coded projects devolve over time into an unmaintainable mess. The reason is simple, yet hard to fix: code maintainability and good architecture don’t have good measurements that we can apply, because it takes months, years even, to notice the effects of bad architecture or of unmaintainable code.

Oh boy do I have some news for you about legacy codebases.

I’m not even sure that his axiom is true. A project started with a 2024/5 model can subsequently be worked on by more capable models (who don’t, unlike some humans, have a deep aversion to paying down technical debt). I’ve seldom seen a human written legacy application spontaneously acquire a better engineering team every six months.