81–90 of 90 posts
Earlier quoted context omitted.
Is there a reason you have two of each example in your post? Or did some tool produce literally exact designs from a single prompt? If so, what tool?
It's not two of each example. It's two screenshots. One from Lovable, one from v0 :)
LLMs are architected to aim toward the center of the bell curve of their training data. You shouldn't expect them to produce innovative ideas, but the upside is they also won't produce terrible ones. The same applies to design. Most of the time, you get something that "doesn't suck", which is perfectly fine for projects where using a designer isn't worth it, like internal corporate pages. But consumer-facing pages re…
But what LLMs do, in the absence of better instructions, is expect that the user WANTS the most middling innocuous output. Which is very reasonable! It's not a lack of capability; it's a strong capability to fill in the gaps in its instructions.
The person who has a good intuition for design (visual, narrative, conversational) but can't articulate that as instructions will find themselves stuck. And unsurprisingly this is common, because having that vision and being able to communicate that vision to an LLM is not a well practiced skill. Instructing an LLM is a little like instructing a person... but only a little. You have to learn it. And I don't think as LLMs get better that this will magically fix itself, because it's not exactly an error, there's no "right" answer.
Which is to say: I think applying design to one's work with AI is possible, important, and seldom done.
Design moves at the speed of culture; not technology. It took 3 years of people messing with mobile phones before it occurred to someone to implement "pull down to refresh" and much longer for it to be common practice that people just expect from UX. I think people are still learning what they want from an AI experience. I do think you have to be pretty targeted with your predictions, though. Consumer product design…
One of the bigger design battles at a prior company was designers insisting on pull to refresh, and the researchers insisting on removing it due to customer feedback.
LLMs are architected to aim toward the center of the bell curve of their training data. You shouldn't expect them to produce innovative ideas, but the upside is they also won't produce terrible ones. The same applies to design. Most of the time, you get something that "doesn't suck", which is perfectly fine for projects where using a designer isn't worth it, like internal corporate pages. But consumer-facing pages re…
LLMs don't produce ideas they implement them, anyone who is relying on LLM produced ideas basically doesn't matter the whole point is they make people who want to design interesting stuff have a lower barrier to entry of actually producing stuff.
LLMs are architected to aim toward the center of the bell curve of their training data. You shouldn't expect them to produce innovative ideas, but the upside is they also won't produce terrible ones. The same applies to design. Most of the time, you get something that "doesn't suck", which is perfectly fine for projects where using a designer isn't worth it, like internal corporate pages. But consumer-facing pages re…
LLMs don't produce ideas they implement them, anyone who is relying on LLM produced ideas basically doesn't matter the whole point is they make people who want to design interesting stuff have a lower barrier to entry of actually producing stuff.
And ideas born without knowledge about their "implementation" are, by definition, quite low resolution.
Lots of these discussions are simplifying design to 'making things look pretty'. That's just not true for even the more visual-based design disciplines like graphic design. And the 'regular' product design (ux/ui/ixd) happening in most tech companies has very little of this compared to the rest of the scope of what a designer really does. Product design isn't a layer that you apply. It's not an output of some prompt.…
I’m a product designer and this is what I’ve noticed: - When I use AI to vibe-code, it gives me a usable result but I personally have no idea if the output is “correct”. I am not sure if there are security vulnerabilities, I don’t know what is actually happening under the hood to make it work, etc. - When my engineering friends use AI to vibe-design, I notice the same pattern. It looks “designed” but there are obviou…
"After 2.5 years of insane hype, there’s no evidence that current AI is making the design process faster" This is antidotally untrue. I work for a small startup. We don't have the money / aren't willing to pay for a full-time designer. So, let's just say, our UI design has always been pretty terrible. With AI, using claude, to generate design and HTML / CSS based on requirements, the design that has been generated ha…
AI can definitely help bootstrap from Terrible -> Okay. But provides little/negative guidance on going from Okay -> Exceptional.
The current AI and design is in a honeymoon period, focused more on experimentation and functional components, using working design patterns, philosophies, templates, and components in abundance. I trust that it is indeed a good thing to accept “Good Enough Design” and layer in the better and best ones later. Right now, we have good enough designs everywhere.
Earlier quoted context omitted.
One of the bigger design battles at a prior company was designers insisting on pull to refresh, and the researchers insisting on removing it due to customer feedback.
what did they want to do with pull down instead?
Earlier quoted context omitted.
Could you expand on your criticism? OP stated that: > Developers who use AI think they're quicker and better, but they're actually slower and worse. You responded that this is a "gross overgeneralization of the content of the actual study", but the study appears to back up the original statement. To quote the summary: > When developers are allowed to use AI tools, they take 19% longer to complete issues—a significant…
> Could you expand on your criticism? Sure! The study focused on experienced devs working in complex codebases they already knew thoroughly. This was and is the worst case for using AI tooling from a cold start, _particularly_ AI tooling as it existed at the time. There were also only 16 developers involved in the study. Time has passed since the study and we've had an entirely new class of tool introduced (the agent…