Why Writing Code Remains Essential in 2026 Despite AI Agents

“Do you know what the industry term for a project specification that is comprehensive and precise enough to generate a program?

Code. It’s called code.”

- CommitStrip (https://www.reddit.com/r/ProgrammerHumor/comments/1p70bk8/sp...)

I think if you’re doing it right, the core of your code should be the simplest expression of the underlying business logic. Of course there’s always going to be supporting layers, and maybe those don’t need to be reviewed. But if you haven’t read the code, there’s an extent to which you don’t know the business logic.

"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.

The relevant question is who is going to pay you to write code manually. It's something that's increasingly hard to justify. The answer is of course that people are not paying for code to be written or generated but for some problem to be solved. Whoever does that with the least amount of drama and cost gets the business. And using AI tools just allows for compressing the timelines a bit in a way that is hard to ignore.

Most code out there isn't all that great. I've been in this industry since the nineties. There are a lot of not so great software engineers doing mediocre work. People are romanticizing how great and magnificent their code is (or used to be). The reality of manually crafted code is of course a lot less flattering. Many code bases become hard to maintain over time and are riddled with bugs. And it's not like sloppy code is a new thing. Poorly executed software projects have been very common for a long time. That's not going to go away.

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.

> For example, have you ever seen an agent follow the boy scout rule? Where they leave code better than they found it? And would you WANT them to try to do this?

Yes, it's in the rules; run profiles, check code coverage, do a critical review, post the report and follow up tasks. 90% of people I've worked with did not follow these boy scout rules nearly as well as today's frontier LLMs.

Is the author implying this is bad?

> 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.

If we look at the progress made from ChatGPT 3.5 (Nov 2022) and up to today...shoot, I'm really starting to wonder if we'll even be reviewing code in 4 years.

And I'm not saying this as some sort of AI maximalist. If progress keeps up, I seriously doubt software engineering and development will, as we know it today, will be a thing in the next 5-10 years. Maybe humans will be left with designing the UI, but everything else will be abstracted away and AI will be doing all the actual work behind the scenes.

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.

"Instead, we’re switching to this wrong-headed mindset that coding agents are like compilers. That mindset gives us permission to ship terribly written code. Agents aren’t compilers - they’re more like freshly onboarded interns."

I feel this statement these days during code reviews. I know some amazing engineers whose output lately just isn't the same.