Does the painter die?
With generative AI now embedded directly into modern IDEs, We’re no longer limited to just getting code that runs.
It helps with completion, refactoring, testing, and documentation,not as separate tools, but as part of the development environment itself.
And sometimes, the result feels surprisingly coherent.
Naming conventions are followed. Structure is maintained. Even the tone of comments can align with the rest of the codebase.
Of course, it’s not perfect — context gets lost, abstractions drift, intent misfires.
But the trajectory is clear, and these gaps feel less like roadblocks and more like temporary frictions.
Given the pace, their resolution seems less a question of “if” and more of “when.”
So we ask:
Does this flow mark the end of the craftspeople once called painters?
From Painter to Artist
The painter is not dead. Let’s be clear about that.
If anything, they’re about to accelerate.
The center of gravity is shifting — away from the detailed mechanics of coding, towards the earlier questions of what to build, why to build it, and how best to approach it.
Even these foundational questions often aren’t tackled alone.
Through conversations with AI, our thought process itself is sharpened, clarified, accelerated.
This isn’t just an upgrade in tools.
It’s a shift in the nature of creation itself.
Not just a painter. A true artist.
And no—this isn’t yet another “review the AI’s code and call it a day” sermon.
We’re headed somewhere more concrete—far deeper.
Turn the page and watch how the questions themselves transform in Chapter 3.
Where Thought Meets Execution
Among the many AI tools emerging in development workflows today,
two practical roles have become especially distinct in how we use them:
The coders:
fast pattern-matching assistants (often integrated into IDEs) that shine in implementation tasks like naming, scaffolding, and syntax completion.The thinkers:
dialog-based models that help clarify vague ideas, structure requirements, and shape overall direction.
Of course, there’s no hard technical divide — most coding tools rely on lightweight reasoning, and many reasoning models can also generate code.
But in practice, their strengths and interfaces remain distinct.
Each is powerful. But they remain separate.
What if they weren’t — and worked as one seamless integration?
What if a vague idea could become a concept refined through AI dialogue, then implemented as coherent, intentional code?
The code goes beyond just working, its structure, naming, and comments all reflect a deep alignment with the spec and design thinking.
This is how code begins to carry meaning — not just logic, but direction.
Not just correctness, but character.
Some tools already claim to generate apps from a single prompt.
These tools are excellent for quickly prototyping ideas,
but their outputs often come with unclear internal logic, making them harder to extend or explain in production contexts.
What I’m proposing isn’t automation. It’s co-creation.
The role of the developer is evolving, from operator of tools to conductor of intent.
Run — Before the Canvas Dries
The ground for creation is ready.
Coding AIs handle implementation; reasoning AIs are already part of our daily back‑and‑forth.
If your idea still feels hazy, you might start by asking things like:
- Why do I want to build this?
- Why am I so attached to this design?
- What problem does it actually solve?
At first the AI may just agree with everything.
But keep pushing the dialogue with weight, with conviction, with real intent and something shifts.
Suddenly it responds as if a spark has landed on dry tinder; it’s no longer a tool but a creative partner.
Those who treat it that way are already sprinting ahead.
The question is no longer “can” you — it’s “will” you.
It’s not about finding the answer inside the AI.
It’s about exploring the answer “together”, through ongoing dialogue.
This is your cue, Artist‑coders
P.S. If you want to see how I’m exploring these ideas in code, the repo is here
mofron
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