Readable Code without Prescription Glasses | Ocasta

cubic blog: The real problem with AI coding

Can you ship AI-generated code without creating a maintenance nightmare six months from now? Can you debug it when it breaks? Can you modify it when requirements change? Can you onboard new engineers to a codebase they didn’t write and the AI barely explained?

Most teams haven’t realized this shift yet. They’re optimizing for code generation speed while comprehension debt silently accumulates in their repos.

One team I talked to spent 3 days fixing what should have been a 2-hour problem. They had “saved” time by having AI generate the initial implementation. But when it broke, they lost 70 hours trying to understand code they had never built themselves.

That’s comprehension debt compounding. The time you save upfront gets charged back with interest later.

The Programmer Identity Crisis ❈ Simon Højberg ❈ Principal Frontend Engineer

I prefer my tools to help me with repetitive tasks (and there are many of those in programming), understanding codebases, and authoring correct programs. I take offense at products that are designed to think for me. To remove the agency of my own understanding of the software I produce, and to cut connections with my coworkers. Even if LLMs lived up to the hype, we would still stand to lose all of that and our craft.

Vibe code is legacy code | Val Town Blog

When you vibe code, you are incurring tech debt as fast as the LLM can spit it out. Which is why vibe coding is perfect for prototypes and throwaway projects: It’s only legacy code if you have to maintain it!

The worst possible situation is to have a non-programmer vibe code a large project that they intend to maintain. This would be the equivalent of giving a credit card to a child without first explaining the concept of debt.

If you don’t understand the code, your only recourse is to ask AI to fix it for you, which is like paying off credit card debt with another credit card.

Vibe coding and Robocop

The short version of what I want to say is: vibe coding seems to live very squarely in the land of prototypes and toys. Promoting software that’s been built entirely using this method would be akin to sending a hacked weekend prototype to production and expecting it to be stable.

Remy is taking a very sensible approach here:

I’ve used it myself to solve really bespoke problems where the user count is one.

Would I put this out to production: absolutely not.

The Recurring Cycle of ‘Developer Replacement’ Hype

Here’s what the “AI will replace developers” crowd fundamentally misunderstands: code is not an asset—it’s a liability. Every line must be maintained, debugged, secured, and eventually replaced. The real asset is the business capability that code enables.

If AI makes writing code faster and cheaper, it’s really making it easier to create liability. When you can generate liability at unprecedented speed, the ability to manage and minimize that liability strategically becomes exponentially more valuable.

This is particularly true because AI excels at local optimization but fails at global design. It can optimize individual functions but can’t determine whether a service should exist in the first place, or how it should interact with the broader system. When implementation speed increases dramatically, architectural mistakes get baked in before you realize they’re mistakes.