In my own projects I actually front-load a lot of the planning. The pipeline behind codn.dev is a good example of that — the planning phase was longer than the actual prompting.
I started with a very simple Astro project and then gradually designed the publishing workflow around it: content schema, frontmatter structure, SEO generation, deployment pipeline, etc. Only after that foundation existed did I start using LLMs to help with parts of the implementation.
The pattern I describe in the article is less about "one prompt shipping", and more about what happens once the feedback loop becomes very fast. Even with a plan in place, the prompt → result → tweak cycle can become surprisingly sticky.
I've been experimenting a lot with AI-assisted development lately and noticed a strange pattern.
The feedback loop becomes extremely fast: prompt → result → tweak → repeat.
That speed creates a kind of variable reward system where near-misses keep you iterating longer than planned. I also started noticing things like thinking about prompts late at night or waking up early wanting to try "just one more idea".
This post is an attempt to describe some of the psychological effects behind that experience.
Curious if other developers noticed similar patterns when using LLM coding tools.
In my own projects I actually front-load a lot of the planning. The pipeline behind codn.dev is a good example of that — the planning phase was longer than the actual prompting.
I started with a very simple Astro project and then gradually designed the publishing workflow around it: content schema, frontmatter structure, SEO generation, deployment pipeline, etc. Only after that foundation existed did I start using LLMs to help with parts of the implementation.
The pattern I describe in the article is less about "one prompt shipping", and more about what happens once the feedback loop becomes very fast. Even with a plan in place, the prompt → result → tweak cycle can become surprisingly sticky.