AI image generation is essentially a truncated exercise in taste; a product of knowing which inputs and keywords to feed the image-mashup machine, and the eye to identify which outputs contain any semblance of artistry. All that is to say: AI itself can’t generate good taste for you.
Continuous partial ick …or perhaps continuous partial cringe.
Anyways, maybe we’ll eventually get to the point where AI has that human “spark”, who knows. Maybe it’ll happen next month and I’ll eat my words. Until then, as most of the content we experience online becomes more grey and sludgy, the personal will become far more valuable.
There’s no AI substitute for a human-produced drawing of someone on the subway, even if a similar-or-even-better result could be produced in seconds by AI. The artifact is often less important than the process — the human process — that made it. That’s why I suspect videos of creative processes are so attractive; we are captivated by seeing humans doing human things.
I love, love, love the deep thinking that Lea has put into this, really digging into the guts of what design does.
Overfitting happens when solutions don’t generalize sufficiently and is a hallmark of poor design. Eigensolutions are the opposite: solutions that generalize so much they expose links between seemingly unrelated use cases. Designing eigensolutions takes a mindset shift from linear design to composability.
Lea ties this into web standards too. It’s really helped clarify for me why I want more declarative options for common use cases (like a share button)—it’s about raising the ceiling without raising the floor.
A terrific piece from Aaron Sankin that goes from Waldsterben to software development via firefighting and the RAND corporation.
Bureaucracies use measurements to optimize and rearrange the world around them. For those measurements to be effective, they have to be conducted in units as relevant as possible to the conditions on the ground.
The value of design principles done right:
What I’ve learnt is that principles are not a luxury. Making explicit and conscious what drives your behaviour can be incredibly powerful as a means to critically shape a team and organisation to be who they want to be.
On leaving the company, Hixie compares the Google of old to what it has become today:
Google’s culture eroded. Decisions went from being made for the benefit of users, to the benefit of Google, to the benefit of whoever was making the decision. Transparency evaporated. Where previously I would eagerly attend every company-wide meeting to learn what was happening, I found myself now able to predict the answers executives would give word for word. Today, I don’t know anyone at Google who could explain what Google’s vision is. Morale is at an all-time low. If you talk to therapists in the bay area, they will tell you all their Google clients are unhappy with Google.
Don’t get me wrong, there are some features under the mislabeled bracket of AI that have made a huge impact and improvement to my process. Audio transcription has been an absolute game-changer to research analysis, reimbursing me hours of time to focus on the deep thinking work. This is a perfect example of a problem seeking a solution, not the other way around. The latest wave of features feel a lot like because we can rather than we should, because.
Here’s the transcript of a great talk by Amy on the realities of working on design systems.
This advice works both ways:
- Collaboration
- Communication
- Respect
- No shared (and contextual) sense of purpose
- Overbuilding, or scaling too early
- Inability to make decisions and move forward quickly
- Lack of clear ownership and dedicated resources
- Lack of cultural alignment
The common thread among these issues is that none are related to technical or tooling decisions —or even to the components themselves.
A good looking artifact too early in the process gains buy-in too quickly and kills discovery.
CSS is now the most powerful design tool for the Web.
I think this is now true. It’ll be interesting to see how this will affect tools and processes:
What I expect to see overall is that the perception and thus the role of CSS in the design process will change from being mainly a presentational styling tool at the end of the waterfall to a tool that is being used at the heart of making design decisions early on.
If we’re serious about creating a sustainable future, perhaps we should change this common phrase from “Form follows Function” to “Form – Function – Future”. While form and function are essential considerations, the future, represented by sustainability, should be at the forefront of our design thinking. And actually, if sustainability is truly at the forefront of the way we create new products, then maybe we should revise the phrase even further to “Future – Function – Form.” This revised approach would place our future, represented by sustainability, at the forefront of our design thinking. It would encourage us to first ask ourselves, “What is the most sustainable way to design X?” and then consider how the function of X can be met while ensuring it remains non-harmful to people and the planet.
AI is great anything quantity-related and bad and anything quality-related.
Sensible thinking from Dan here, that mirrors what we’re thinking at Clearleft.
In other words, it leans heavily on averages; the closer the training data matches an average, the higher degree of confidence that the result is more “correct,” or at least desirable.
The problem is that this is the polar opposite of what we consider creativity to be. Creativity isn’t about averages. It’s about the outliers, sometimes the one thing that’s different than all the rest.
- Start with mostly static HTML.
- Progressively enhance the dynamic parts.
- Pick small, focused tools.
I’ve been using Copilot for over a year now, and this is more or less how I use it: To help me quickly blast through boilerplate code so I can more quickly get to the tricky bits.
There’s a more subtle problem with ChatGPT’s code generation, which is that it suffers from ChatGPT’s general “bullshit” problem.
A very handy guide to considering privacy at all stages of digital product design:
This guidance is written for technology professionals such as product and UX designers, software engineers, QA testers, and product managers.
I’ve personally never really seen frontend as an assembly job. Lego is admittedly awesome, but for me the mental model of assembling Lego bricks in the required order until a Jira ticket can be marked as “done” feels too linear and too rigid for how I like to work. And that’s not to mention the pain that comes when you have to partially dismantle your bricks to correct some earlier misstep.
I like the pottery analogy.