The mandate from above is clear, just get it done! Avoid everything that's in the way: all advice, all expertise, all discovery efforts that detract from hitting the Date™!
What these organizations don't realize is that all software change can be modeled as three components: Value, Filler and Chaos. Chaos destroys Value and Filler is just functionality that nobody wants. When date pressure is applied to software projects, the work needed to remove Chaos is subtly placed on the chopping block. Work like error handling, clear logging, chaos & load testing and other quality work is quietly deferred in favor of hitting the Date™.
Finding value is the result of enabling individual and group-level discovery attempts. It's not the result of everyone following one leader's gut.
What just happened is a new software product/feature was created that no customer wanted. This happens way too often. In fact, most hyper important software projects that must be done by date certain or else, have deep flaws that cause some variation of this phenomenon, flaws that include:
Not wanted - Company specified a solution to a problem that customers don't actually have
No Rarity - Company is pursuing an iKnockoff of existing products. The market already has two scaled competitors with working solutions, customers naturally spend budget on products that are already successful to avoid risk
Incorrect Packaging - Customers need a website, but the company created an iOS app instead
Incorrect Pricing - Customers need SaaS pricing, but the company created a shrink wrapped, on-premise solution with CapEx and maintenance agreements instead
Like a programming language interpreter, GPT-3 translates the designer’s intent from a language they’re already familiar with (English) to one they need to learn (Figma’s information architecture, as manifested in its UI.) This can be easier for a new/busy designer, much like Python is easier and faster to work with than assembly language.
But that’s not “designing” — at least not any more than compiling Python code is “programming.” In both cases, all the system does is translate human intent into a lower level of abstraction. Sure, the process saves time — but the key is getting the intent part right. I’ll be convinced the system is “designing” when it can produce a meaningful output to a directive like “change the product page’s layout to increase conversions.”