3D Printers span from ‘make a blob’ through to ‘print a rocket engine nozzle out of exotic metals’. They’re powerful tools encompassing a range of capability levels across a broad spectrum of different use cases. There is hope that one day you’ll be able to 3D print everything — from meat to homes to limbs.

How effective they are is dependent on the inputs (materials, model) and the skill of the operator. You have to model the entire shape of your output(s) to be successful. But the operator has to understand how to ensure a successful print with the appropriate level of intervention that matches your needs & expectations.

At the low end, you have Creality producing affordable, powerful — but limited — 3D printing accessible to anyone. At the high end you have LPBF machines from EOS that will print you a metal component for a plane or rocket in highly complex shapes.

LLM coding tools such as Codex, Claude Code, OpenCode, and GitHub Copilot CLI are the 3D printers of the software world, and they’ve already transformed what is possible, and the way that the possible is achieved. The hope is they will produce from fixes to features to entire products.

And, just like 3D printing, their adoption & usage is unevenly distributed.

Your coding agent output is dependent on your input materials (specs, details, guidance) how you operate it (follow on prompts, skills, reference materials, validation).

It’s the difference between a useful print, and a pile of plastic goo.