What are your thoughts on running AI agents and local models? What happened with Fable could happen to any model — big companies with money can just buy hardware, but how does a regular person or someone just starting out in AI protect themselves if a model they depend on for client work suddenly becomes unavailable?

You want to wrestle a little control back from the big monolithic AI companies, and I can help with that. There are two kinds of improvement happening right now: hardware (massive data centers letting labs train bigger, and per the bitter lesson, generally smarter, models) and software/algorithmic improvements (inference optimizations, quantization, and other hacks that let you run faster or smaller models at similar intelligence). The hardware path isn't very accessible if you're not capital-rich — big models just cost more to run and labs will charge accordingly. But the algorithmic path doesn't require massive hardware. China, rate-limited on compute compared to the US's roughly 50-100x compute advantage, has poured its effort into this path — models like GLM 5.2 and Kimi K2 have gotten almost an order of magnitude more efficient purely from software optimization. As a result, you can run a model like GLM 5.2 locally right now, 1-bit quantized, on a MacBook with 256GB of memory. It's not unreasonable to expect that within about 6 months we'll be running something similar (or a bit dumber) on our phones. So while the fear of big model companies taking over is understandable, it seems very likely everyone will soon be able to run models much smarter than what we have today on compute as modest as a phone — you won't get the frontier models doing galaxy-scale planning, but you'll have genuinely capable local assistants you don't depend on any one company for.