Generated code is rather a lot like fast fashion: it looks all right at first glance but it doesn’t hold up over time, and when you look closer it’s full of holes. Just like fast fashion, it’s often ripped off other people’s designs. And it’s a scourge on the environment.
I’ve seen so many times how 10 lines of code can end up being worth £millions, and 10,000 ends up being worthless.
A clear explanation of how image dithering works, illustrated along the way.
Every engineer eventually overbuilds something. You think you’re being smart. You’re thinking ahead, building for growth and before you know it, you’ve created a system ten times heavier than your actual problem. That’s the trap. We keep designing for imaginary futures for scale that may never come and call it engineering. But it’s not engineering. It’s over-engineering.
The industry rewards it too. Nobody gets promoted for keeping things small and sane. You get promoted for complexity.
Stick with this. It’s worth it.
- Install Stuff Indiscriminately From npm
- Pick a Framework Before You Know You Need One
- Always, Always Require a Compilation Step
The joy came flooding back to me! It turns out browser APIs are really good now.
It seems like the misguided perception of needing to use complex tools and frameworks to build a website comes from a thinking that web browsers are inherently limited. When, in fact, browsers have evolved to a tremendous degree
Thoughtful analysis from Ben (as always).
So, let’s start with a simple premise: how can we make design less opaque and encourage teams to make small changes more efficiently? Not every product decision needs to be a big, complicated design process.
This checklist, in four parts, is meant to be a simple, lightweight way for the team to get the ‘gist’ of the issue and make a shared decision quickly. It’s a starting point, a way to get the critical information in once place so the entire team can understand and discuss. The four parts are:
- Gather: Bring the right info together into a single place
- Impact: List the size of the problem and possible risks
- Sketch: Create a preliminary sketch of a solution
- Team Huddle: Get the product team to discuss and agree on a solution.
This is a really thoughtful piece by Rich, who’s got conflicted feelings about large language models in the design process. I suspect a lot of people can relate to this.
What I do know is that I find LLMs useful on occasion, but every time I use one I die a little inside.
This describes how I like to work too.
The power of prototyping:
Most of my work is a set of disposables rather than deliverables, and I celebrate this.
I like the three questions that Chris asks himself:
- What’s the quickest, cheapest thing I can create to help make the next design decision?
- What can I create to best demonstrate the essence of the concept?
- How can I most effectively share the thinking behind the design with decision-makers?
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.