Why Write Code in 2026

"It’s about attention and understanding. To keep my attention, I must go beyond ‘read code’ like a passive observer of agents from afar. To really connect with the architecture of the system, it helps to truly experience the code"

I guess the funny answer that is behind this sentence is: You have to train your own mental model. We always argue about code in a very abstract and logical manner. But when coding the subconsciousness makes most of the decision ("this just feels right"). But for this to work you have to train it. And this does only work in a very limited way with code reviews or reading documentation. It requires repetition and deep focus.

When there is an issue in production with this mental model you will be able to point to the cause of an error message instantly. With generated code you'll search for a long time with your slow, conscious part of the brain.

For LLMs to be really helpful, they have to take over complete maintenance of the code. So you can treat them like an external library: Just assume it works. Otherwise this will always be problematic.

I always hated writing code but loved debugging. LLM super charges systems thinkers & auditors, it’s just a different process and no different than copy and paste from stack overflow. It all comes down to the architecture design and LLM just exposes how bad people are at designing dynamic architectures.

I need to write code because otherwise LLMs will write too much code, it’s only when you fully understand the problem you can generalise it enough to not end up with 10k lines and 5 abstraction layers for “hello world”. LLMs are token predictors, so all solutions are you tokens, the more problems to solve == the more tokens (code) to output.

Unless you want some unmaintainable shitty sloppy app.

I think fragility is the key reason i intervene in llm code too. Good article.

It seems to me that AI won the code Battle and that humans are just trying to justify the defeat. I will relax and wait for the Next AI generation to see how it fixed its problems. May be, everything will be ok.

> If we’re building a software factory, details matter. The details that establish architectural patterns. Down to algorithms and performance. Agents push us to evaluate, measure, and guard. They’ve made it cool to add CI into side projects early, not as an afterthought. That’s massive improvement to the state of software.

Why are you building a software factory though, and why weren't you immediately adding CI to every project?

> It’s our job to build the software factory - not just the software. Software engineers maintain the assembly line allowing anyone to prompt for a change and ship immediately.

Again, why? Where are you working where this is considered a good idea? This would mean that the software engineers are not just being completely kicked out of all business decisions, but asked to build a moat that ensures they stay on the other side of it.

Any business that intentionally devalues the insights gained through implementation will eventually starve itself to death by making too many passive thoughtless moves. No insight will ever be gained just spot checking AI. Is their intention really just to make tiny amounts of profit while riding the thing into the ground? Crabs in a bucket, man.

Prediction: in 2027 a coding agent will read this as inspiration for why it should code.

This is too generic. There's some code I need to write like core abstractions that are going to set the pace for everything. Or tricky steps that can look good without actually working well.

Then there's the mass. I don't need that anymore. The mountains of boilerplate, etc.

I write little islands which need high judgement that are then connected by the obvious goo.

I still exclusively write my code. The quality is higher. I know exactly how it works. It’s more extensible. You don’t have to generate it.

Do ppl think that programmers just write code from sratch each time..?!

Even without AI I barely write code. 95% of time are spend setting up integrations, configs, copying & adjusting code from previous projects.

AI is a tool. Learn how to use it!

Interesting article btw

lol what a slopper

"Why cook food in 2026 [while McDonald's exists]?"

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TL;DR: Write it so you’re actively involved and not a passive reviewer. Then a sign up link for his course.

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Recently, even a tourist lost to OAI's model in competitive coding. To be honest, I haven't been able to beat AI at coding since around 5.2. People often say 'AI can't write good code,' but in reality, the quality of AI's output is layered depending on the level of the prompt input. The deeper the prompt, the better the code actually gets.

Usually, when people say AI code is terrible, it's because they either don't understand the theory well but have grown through hands-on experience and can't explain things properly to the AI, or they don't know what they don't know. Or there are the very few who are just far better coders than AI. Some people will say they're among the rare few who can write better code than AI, and for some that may be true. But in my experience, the vast majority are not. Even from my perspective as a beginner, I could see flaws when I looked at their git code. It's a metacognition problem.

Realistically speaking, at the script level, it's quite common to see AI surpass human programmers as you increase the input level. You might disagree, but that's probably because you're a specialist in that field, deeply immersed in a very narrow area—it only holds true in that limited scope. In the general domain, most people would agree that AI writes code well.

Human programmers don't know much outside their own domain. But AI, while it loses in very narrow specialist areas, writes better code than humans across the broader range. It loses in the 1% zone (the expert's domain), but wins in the other 99%. Usually, when that's the case, you have two choices: become the 1%, or learn how to use AI.

Since I'm a non-native English speaker, I'm already at a disadvantage compared to native speakers in programming skills, so I chose the latter. But I still code. Not for any other reason—if I don't maintain at least some typing muscle, I won't be able to review AI code properly.

That's why I think coding is essential. Even if I can't understand the entirety of AI's output, I still need to understand the core business logic. At the very least, the core logic requires human understanding, so coding is necessary.