does it make a mistakes? yes sometimes but you can verify with tests or with lean.

The public discourse about LLM assisted coding is often driven by front end developers or rather non-professionals trying to build web apps, but the value it brings to prototyping system concepts across hardware/software domains can hardly be understated.

Instead of trying to find suitable simulation environments and trying to couple them, I can simply whip up a gui based tool to play around with whatever signal chain/optimization problem/control I want to investigate. Usually I would have to find/hire people to do this, but using LLMs I can iterate ideas at a crazy cadence.

Later, implementation does of course require proper engineering.

That said, it is often confusing how different models are hyped. As mentioned, there is an overt focus on front end design etc. For the work I am doing, I found Claude 4.5 (both models) to be absolutely unchallenged. Gemini 3 Pro is also getting there, but long term agentic capability still needs to catch up. GPT 5.1/codex is excellent for brainstorming in the UX, but I found it too unresponsive and intransparent as a code assistant. It does not even matter if it can solve bugs other llms cannot find, because you should not put yourself into a situation where you don't understand the system you are building.