I think the real world improvements will plateau and it'll take awhile for current enterprise just to adopt what is possible today but that is still going to cause quite a bit of change. You can imagine us going from AI Chat Bots with RAG on traditional datastores, to AI-enhanced but still human-engineered SaaS Products, to bespoke AI-generated and maintained products, to fully E2E AI Agentic products.
An example is do you tell the app to generate a python application to manage customer records or do you tell it "remember this customer record so other humans or agents can ask for it" and it knows how to efficiently and securely do that.
We'll probably see more 'AI Reliability Engineer' type roles which will likely be around building and maintain evaluation datasets, tracking and stomping out edge cases, figuring out human intervention/escalation, model routing, model distillation, Context-window vs Fine-tuning, and overall intelligence-cost management.
An example is do you tell the app to generate a python application to manage customer records or do you tell it "remember this customer record so other humans or agents can ask for it" and it knows how to efficiently and securely do that.
We'll probably see more 'AI Reliability Engineer' type roles which will likely be around building and maintain evaluation datasets, tracking and stomping out edge cases, figuring out human intervention/escalation, model routing, model distillation, Context-window vs Fine-tuning, and overall intelligence-cost management.