This is an interesting comparison: design systems as APIs. It makes sense. A design system—like an API—is a contract. Also, an API without documentation is of little use …much like a design system without documentation.
An interesting project that will research and document the language used across different design systems to name similar components.
The video of a talk in which Mark discusses pace layers, dogs, and design systems. He concludes:
- Current design systems thinking limits free, playful expression.
- Design systems uncover organisational disfunction.
- Continual design improvement and delivery is a lie.
- Component-focussed design is siloed thinking.
It’s true many design systems are the blueprints for manufacturing and large scale application. But in almost every instance I can think of, once you move from design to manufacturing the horse has bolted. It’s very difficult to move back into design because the results of the system are in the wild. The more strict the system, the less able you are to change it. That’s why broad principles, just enough governance, and directional examples are far superior to locked-down cookie cutters.
This is a really interesting distinction:
An intentional design system. The flavour and framework may vary, but the approach generally consists of: design system first → design/build solutions.
An emergent design system. This approach is much closer to the user needs end of the scale by beginning with creative solutions before deriving patterns and systems (i.e the system emerges from real, coded scenarios).
It’s certainly true that intentional design systems will invariably bake in a number of (unproven?) assumptions.
The good folks at Sparkbox ran a survey on design systems. Here are the results, presented in a flagrantly anti-Tufte manner.
A case study from Twitter on the benefits of using a design system:
With component-based design, development becomes an act of composition, rather than constantly reinventing the wheel.
I think that could be boiled down to this:
Component-based design favours composition over invention.
I’m not saying that’s good. I’m not saying that’s bad. I’m also not saying it’s neutral.
Rachel makes the case for integrating content design patterns into component libraries:
Instead of content design systems and visual design systems existing in isolation, the ideal is one design system that accommodates everything, marrying the content and design together in the way it will actually be used and experienced.
Amy’s talk at Patterns Day was absolutely brilliant! Here’s an account of the day from her perspective.
The evident care Jeremy put into assembling the lineup meant an incredible mix of talks, covering the big picture stuff right down to the nitty gritty, and plenty in between.
Her observation about pre-talk nerves is spot-on:
I say all of this because it’s important for me and I think anyone who suffers with anxiety about public speaking, or in general, to recognise that having a sense of impending doom doesn’t mean that doom is actually impending.
Here’s a nice little round-up of Friday’s Patterns Day.
Just look at these fantastic pictures that Trys took (very unobstrusively) at Patterns Day—so rock’n’roll!
Stuart took copious notes during every single talk at Patterns Day—what a star!
A very thoughtful post by Hidde that draws a useful distinction between the “internals” of a component (the inner workings of a React component, Vue component, or web component) and the code that wires those components together (the business logic):
I really like working on the detailed stuff that affects users: useful keyboard navigation, sensible focus management, good semantics. But I appreciate not every developer does. I have started to think this may be a helpful separation: some people work on good internals and user experience, others on code that just uses those components and deals with data and caching and solid architecture. Both are valid things, both need love. Maybe we can use the divide for good?
What would Wiener think of the current human use of human beings? He would be amazed by the power of computers and the internet. He would be happy that the early neural nets in which he played a role have spawned powerful deep-learning systems that exhibit the perceptual ability he demanded of them—although he might not be impressed that one of the most prominent examples of such computerized Gestalt is the ability to recognize photos of kittens on the World Wide Web.
Chris ponders the motivations behind companies sharing their design systems publicly. Personally, I’ve always seen it as a nice way of sharing work and saying “here’s what worked for us” without necessarily saying that anyone else should use the same system.
That said, I think Chris makes a good poin here:
My parting advice is actually to the makers of public design systems: clearly identify who this design system is for and what they are able to do with it.
Wouldn’t it be great if every component in your design system had accessibility acceptance criteria? Paul has some good advice for putting those together:
- Start with accessibility needs
- Don’t be too generic
- Don’t define the solution
- Iterate criteria
Some useful lessons here for strengthening a culture of sustained work on a design system.
Creating and maintaining a design system is like planting a tree—it has to be nurtured and cared for to reap the benefits. The seed of our design system has been planted, and now our teams are working together to maintain and grow it. Our new way of working supports gives people recognition, facilitates trust, and creates strong partnerships.
Honestly, cryptocurrencies are useless. They’re only used by speculators looking for quick riches, people who don’t like government-backed currencies, and criminals who want a black-market way to exchange money.
Bruce Schneier on the blockchain:
What blockchain does is shift some of the trust in people and institutions to trust in technology. You need to trust the cryptography, the protocols, the software, the computers and the network. And you need to trust them absolutely, because they’re often single points of failure.
We assume that complex problems always require complex solutions. We try to solve complexity by inventing tools and technologies to address a problem; but in the process we create another layer of complexity that, in turn, causes its own set of issues.
The Principle of Least Power looms large over this:
Some of the most important things in the world are intentionally designed “stupid”. In any system, the potential for error directly increases with its complexity - that’s why most elections still work by putting pieces of paper in a box.