I wrote an AI assistant which generates working spreadsheets with formulas and working presentations with neatly laid out elements and styles. It's a huge produ

I wrote an AI assistant which generates working spreadsheets with formulas and working presentations with neatly laid out elements and styles. It's a huge productivity gain relative to starting from a blank page. I think LLMs work best when they are used as a "creative" tool. They're good for the brainstorming part of a task, not for the finishing touches. They are too unreliable to be put in front of your users. People don't want to talk to unpredictable chatbots. Yes, they can be useful in customer service chats because you can put them on rails and map natural language to predetermined actions. But generally speaking I think LLMs are most effective when used _by_ someone who's piloting them instead of wrapped in a service offered _to_ someone. I do think we've squeezed 90%+ of what we could from current models. Throwing more dollars of compute at training or inference won't make much difference. The next "GPT moment" will come from some sufficiently novel approach.