Original Summary

Video if you're interested: https://youtu.be/1riq26VTZd8 Hey r/SaaS , sharing something that made a big difference to our costs, in case it's useful to anyone building on top of LLMs. We're building Graphyti, a tool that generates 3D worlds (terrain, cities, buildings) from a text prompt. Our first approach was the obvious one: let the model write all the 3D code from scratch. It worked, but it was slow and expensive. One complex building took about 15 minutes and ~4.5M tokens, and results changed every run. So we flipped it. Now the model only makes decisions: what kind of building, how tall, what style, where the roads go. It hands those off to generators we wrote ourselves, which do the heavy lifting. The same building now takes about 7 minutes and ~1.6M tokens, and the same inputs always give the same result. A few things we learned: LLMs are expensive at repetitive, precise work. Anything you can turn into a function call, do. Deterministic output made debugging and support much easier. When a customer reports a problem, we can reproduce it exactly. Costs became predictable, which makes pricing much less scary. The tradeoff is that we had to build and maintain all those generators, which is a lot of upfront work. It only pays off if your domain has structure you can encode. Curious whether others have done something similar. Did you move work away from the LLM, and where did you draw the line? Pm me if you're interested in joining the waitlist!   submitted by   /u/ExtensionPhoto7991 [link]   [comments]

  • 情报分类：商业与市场研究
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  • 信息来源：Reddit · SaaS
  • 发布时间：2026/9/24 10:21:41