Took a bit of a break to energize! I’ve been back in conversations with product and design leaders through my sales conversations.
Two things have really stuck out:
Design teams building in vacuums created by a production mindset
Engineering storming ahead with new AI tools that make creating outputs easy
This is creating problems
Stakeholders want results faster, so they look to engineering to help them get things done. It’s kinda a funny reversal, since engineering used to provide resistance by pushing back. That’s changing with all these new AI tools. When engineers are empowered to drive agents that do the work, the conversation shifts to “why not.” And a lot is starting to get built.
I will say that the outputs create a lot of things that look like everything else (it’s the average of using LLM systems). In some cases, that may not be bad. But over time, it erodes the brand and the story companies are trying to tell.
What this means for design is that it has to shift.
Either design expresses a clear point of view that supports the business and justifies its value, or it gets faster at producing the same outputs in a way the business understands. In both cases, the problems start to show up if customers aren’t at the center.
So we need to think about what different actually means in design. Wrote a quick post:
Truth. I feel like I can pretty much do anything at this point (even though I’ve always been a “hell yes” guy), but now it feels like the pain and time-cost of getting something built has shrunk significantly.
Very true! We’ve seen this in our own work, where @ben is charging ahead on five tools at a time, but our design decisions are playing catch-up instead of driving the development based on data.
If development can move 5x faster now, then design decisions and the data insights they’re based off of need to do the same. However, design isn’t just throwing together a layout for a page that can hold all the necessary features. It involves understanding the decisions that solve problems for the user and the business, and data is key in that understanding.
This means designers need to shift to designing the output goals and decisions that go into building good products, and UX advocates need constant access to feedback loops that can quickly validate or invalidate those decisions.
