I don't think it makes sense from a business perspective to hold off on details as a new lab. OpenAI will not implement new architectural changes unless they've tested the changes themselves internally. Even if someone claims some great innovation, they'd need to do scaling experiments to somewhere between the size of GPT-4 to GPT-5 before they'd decide it is worth it to implement themselves. Plenty of mechanisms that seem to work at one scale do not translate to the next.

Because the cost to OpenAI to make an architectural shift is far greater than the cost to a new lab to try something different, providing details is usually a net benefit for recruiting, building trust, getting acquired, etc. The lack of details is a poor business decision because it makes them seem untrustworthy.

I'm not advocating that they should open source their model, but there is already so much noise in the space and many bad papers that being cagey is a poor strategy for winning over talent, developers, etc.