I am pretty sure they try to do it all the time between themselves. Most of the real sauce in AI coding comes from reinforcement learning, usually done by armies of third world outsourced developers tediously doing all kinds of tasks with instructions to detail their reasoning behind each chance. Things like: "to run this python test in a docker container with the python image we need to install the python package xyz, but then, as it has some native code, we also need to install build-essential..."

While those developers are not well paid (usually around 30/40 USD hour, no benefits), you need a lot of then, so, it is a big temptation to create also as much synthetic data sets from your more capable competitor.

Given the fact that AI companies have this Jihad zeal to achieve their goals no matter what (like, fuck copyright, fuck the environment, etc, etc), it would be naive to believe they don't at least try to do it.

And even if they don't do it directly, their outsourced developers will do it indirectly by using AI to help with their tasks.