I believe they introduced a sort of rate limiting where the expectation will be that the user is doing more thinking and due diligence and asking more precise questions, so that they're not just attempting to get a lot of hand holding with very broad prompts when they can otherwise think about what code they're being given back from more specific and structured questioning. This is useful because it will preserve the value proposition of AI while avoiding a machine just being milked for code by people who want to just throw code at the wall and see what sticks. Milking a model for code is fun in some ways but it won't scale from a cost-to-run point of view, and it also will incentivize no longer thinking deeply and critically about what is being built.

If you are incorporating machine models into your development process very heavily, make sure you're still building deep knowledge and deep context of your codebase. Otherwise you'll atrophy in that department because you falsely believe the machine maintains the context for you.

That isn't feasible right now because the cost of maintaining huge context per user to enable milking rather than enhanced-thinking is too high.

Also consider that we don't want to enable milking. People who have no idea what they're doing will just throw a lot of code at the wall and then when there's a huge mess they'll be asking engineers to fix it. We need to be careful with who has this kind of access on our teams in general. Someone who is non-technical should not be given a firecracker before they've ever even just turned on a microwave or a stove.