The moat isn't going to be the model (short of AGI). The moat is going to be what surrounds it. The harness and, I have suggested elsewhere, memory. The more personalized the AI is to you the more valuable it will be.

Also, as tech companies grow, a significant portion of the dev body count is for internal tooling. I was always flabbergasted at Twitter's headcount growth back in the day when it seemed like the only innovation increasing the number of characters in a tweet.

Right now we are in a weird spot where a lot of people are flailing around inside corporate America trying to figure out how to leverage AI. Few have enough vision to see what the companies of the future will look like and work towards that.

I did RL and evals at Amazon for a bit on Nova Forge (laid off in July! :D). I would have to push several thousand lines of code a day in new evaluations that our applied scientists requested since new ones are always being made along with having to create custom ones for whatever new model they were working on. Also, in RL, adding new environments for the agents to actually complete activates was also a shit ton of lines of code. So if I had to guess, just adding new stuff around model training and testing alone accounts for a ton of these changes.

Probably lots of internal competitor apps ready to release to wipe out SaaS/Adobe/etc. companies.