u/Few_Film8907

Context: I am an eng at a startup that just raised a Series, where about 10 eng are doing a lot of work, and quickly. I have been asking around and monitoring my Cursor/Anthropic costs, and it seems that an eng spends between $1k and $4k a month on AI usage on their preferred platform. Since we raised and have money, it's not really a concern for us. Also, we are shipping a lot, so it seems to be worth it. But that's not the case for all startups.

Does your company monitor eng token spend on platforms like Codex, Claude Code, or Cursor? How are companies budgeting for it?

Created Simulation From LLM Output

Background: I studied EECS and I'm now getting into robotics, mostly working through the simulation side of things. While digging into the sim pipeline I came across this repo: https://github.com/AlexKaravaev/world-creator

It's a CLI that generates Gazebo and Mujoco simulation worlds from a text prompt. You type something like "warehouse with shelves and some obstacles for navigation testing" and it picks models from the Gazebo model database and places them for you. I think it's genuinely a great idea and ahead of its time. It's from ~2023, so it predates all the recent LLM progress, and the author was upfront that the model hallucinated a lot back then. With today's models this approach could work way better.

Curious about a few things:

1. Has anyone here used this or something like it in real work?
2. Is prompt-to-world something you'd actually want, or is scene setup not painful enough to matter? From what I've seen so far, people complain way more about getting the robot itself into sim (URDF, meshes, inertia values) than the environment around it. Is that right?
3. If someone built an upgraded version of this, what would the use cases be for you? Randomized scenes for RL training? Test scenarios in CI? Quick demos?

I'm exploring building in this space, so honest "nobody needs this" takes are just as useful as feature wishlists.

Created Simulation From LLM Output

Background: I studied EECS and I'm now getting into robotics, mostly working through the simulation side of things. While digging into the sim pipeline I came across this repo: https://github.com/AlexKaravaev/world-creator

It's a CLI that generates Gazebo and Mujoco simulation worlds from a text prompt. You type something like "warehouse with shelves and some obstacles for navigation testing" and it picks models from the Gazebo model database and places them for you. I think it's genuinely a great idea and ahead of its time. It's from ~2023, so it predates all the recent LLM progress, and the author was upfront that the model hallucinated a lot back then. With today's models this approach could work way better.

Curious about a few things:

1. Has anyone here used this or something like it in real work?
2. Is prompt-to-world something you'd actually want, or is scene setup not painful enough to matter? From what I've seen so far, people complain way more about getting the robot itself into sim (URDF, meshes, inertia values) than the environment around it. Is that right?
3. If someone built an upgraded version of this, what would the use cases be for you? Randomized scenes for RL training? Test scenarios in CI? Quick demos?

I'm exploring building in this space, so honest "nobody needs this" takes are just as useful as feature wishlists.