I just read a good piece by the Nilenso crew on AI-assisted coding for teams that can’t get away with vibes.
Blog post title aside, it helped me synthesize my own thoughts better on a question that keeps coming up: will AI replace all software engineers?".
Not only won’t it replace us, it’ll make the best engineers even more valuable.
Here’s why.
AI amplifies what you already have
To make AI good, get good yourself. AI is a multiplier. If you are a small coefficient, you won’t see much gain. If you are a negative coefficient, expect negative gains.
🎯. The best engineers extract far more value from AI tools. Why? Because they already have the fundamentals that AI needs to work with:
- They communicate technical ideas clearly - AI responds to good prompts, and good prompts require clear thinking.
- They have “the mechanic’s touch” - that intuitive sense for what makes good systems work. They steer AI toward better solutions.
- They have strong fundamentals - they can quickly evaluate AI suggestions and know when something’s off.
- They have taste - AI mirrors your sensibilities. Experienced engineers get better results because they ask for better things.
I’ve seen this repeatedly. Give the same AI tool to a junior and senior engineer. The senior gets dramatically better results. Not because they’re smarter, but because they know what questions to ask.
What helps humans helps AI
Here’s where it gets interesting. From the article:
Our AI coding assistant struggled to complete a task of equal difficulty on the latter codebase when compared to the former! This is likely because the messier codebase was as confusing for the AI as it would be for a human.
Clean architecture, good naming, clear patterns - everything that makes codebases maintainable for humans also makes them effective for AI.
So if you want to be more effective with AI, you still need all the craftsmanship skills that good software engineers have always needed. The fundamentals matter more now, not less.
The craftsmen still matter.
Software engineering was never just about coding
Software engineering is not about writing code. Or at least, that’s not the defining characteristic, much like how writing is not wrist exercises with ink on paper.
The real value has always been in the decisions: what to build, how to architect it, when to make tradeoffs, why a particular approach makes sense. The actual typing? That’s just execution.
AI is getting scary good at execution. But judgment calls (understanding context, business requirements, user needs, system constraints) — that’s still very much human territory.
See also Rakhim’s post breaking down coding vs. programming vs. software engineering.
and by this definition I think LLM AIs will systematically replace coding first, programming next (😢) and software engineering last.
so to remain relevant in this new world, imho become a stronger software engineer.
I’ll leave you with quote from an article that Simon Willison[^sw] wrote:
I’ve spent enough time with GitHub Actions that I know what LLMs are no replacement for human intuition and experience. kind of things to look for, and in this case it was faster for me to step in and finish the project rather than keep on trying to get there with prompts.
Simon maintains the llm cli project and a voice you should be following to keep abreast of all the AI news around software engineering.
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