It's not about the spending of AI tokens, it's about the potential of prototyping.
I like to build things in my free time.
Not necessarily produc...
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The reframe from "token costs" to "prototyping velocity" is the right lens. The calculation isn't cost-per-token, it's cost-per-prototype, and what AI does to that number is dramatic. A prototype that would have taken a weekend now takes an evening, which means you can run more experiments, kill bad ideas faster, and arrive at something worth investing in with much less sunk cost.
The "things I want to exist" motivation is also underappreciated in how it produces different outcomes than "building for a market." When you're building something you personally want, you have a much cleaner signal on whether it's working — does it do the thing you needed? That's a harder question to answer honestly when you're building for a hypothetical user.
The iteration model you're describing (MVP fast, then iterate on what you actually discover vs what you assumed) is the practical benefit AI unlocks most reliably — not better code, but faster feedback loops.
Thanks so much, this is one of the most insightful comments I've gotten on the article. You nailed exactly what I was trying to get across.
Totally agree on the "things I want to exist" motivation too. When I'm building for myself, the feedback loop is brutally honest, either it scratches the itch or it doesn't. No hand-waving about "user personas" or "maybe they'll like it." It's been a game-changer for actually shipping stuff.
Appreciate you taking the time to write this out. Comments like yours make writing these pieces worth it. Have you noticed similar shifts in your own prototyping workflow with AI?
This really resonates. The shift from "write perfect code" to "get a working prototype fast and iterate" has been a game-changer for me too.
I've been running a similar workflow on a large-scale Astro site — using AI to generate content for thousands of pages, then iterating based on real data from Search Console and analytics. The feedback loop is so much tighter now. What used to take weeks of planning and spec-writing turns into a weekend prototype you can actually test against real users.
Your point about accountability is important though. I've seen AI-generated code that looks clean but has subtle data issues — things like wrong calculations that pass a quick glance but fail when you look closer. Iteration has to include validation, not just feature velocity.
Curious about the 60 FPS constraint for browser games — are you using canvas or WebGL for rendering?
Thanks! Glad it resonates.
For the 60 FPS constraint: All my games are 3D. I mainly use Three.js or Phaser.js with backend-authoritative rendering, and I try to disable frontend re-renders / state manipulation entirely to keep consistent performance.
I've actually recently made the sync part public, here: github.com/AncientiCe/realtime-syn...
This is the magic that syncs at 60 fps.
Of course this really fits my type of projects, might not fit yours.
Oh nice, 60 fps sync is no joke — that's way beyond what most prototyping setups handle. I'll definitely check out the repo. My projects are more on the static site / data pipeline side (thousands of pages generated from structured data), so real-time sync isn't my core use case, but I can see how that changes the prototyping feedback loop completely. Appreciate you sharing it!
Love this, your “prototype first, own what you ship” mindset feels refreshingly honest, and I think a lot more builders needed to hear that today.
nice
💯
token costs come up in every retro. but nobody asks how many ideas died before they could be validated because prototyping was too slow. the real leverage is earlier in the loop.
Exactly.
Token costs show up in every retro because they're easy to measure. But the silent killer is all the ideas that never even got prototyped because the friction was too high. AI moves the bottleneck earlier in the loop, and that's where the real leverage hides.
Appreciate you putting it so cleanly
yeah the bottleneck shift is the part that is hard to explain until you have actually lived it. when prototyping is cheap the question stops being can we afford to try this and becomes why didnt we try this sooner
Yup, same here, in a different way
Best wishes to your projects!
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