AI-driven "Design"? An Article by Jorge Arango jarango.com Like a programming language interpreter, GPT-3 translates the designer’s intent from a language they’re already familiar with (English) to one they need to learn (Figma’s information architecture, as manifested in its UI.) This can be easier for a new/busy designer, much like Python is easier and faster to work with than assembly language. But that’s not “designing” — at least not any more than compiling Python code is “programming.” In both cases, all the system does is translate human intent into a lower level of abstraction. Sure, the process saves time — but the key is getting the intent part right. I’ll be convinced the system is “designing” when it can produce a meaningful output to a directive like “change the product page’s layout to increase conversions.” aidesignintentabstraction
Two types of work An Article by Jorge Arango jarango.com There are two types of work: growth work and maintenance work. Growth work involves making new things. It can be something big or small. In either case, growth work often follows a loose process. Maintenance work is different. Maintenance work involves caring for the resources and instruments that make growth work possible. This includes tools, but also body and mind. Maintenance is ultimately in service to growth. But effective growth can’t happen without maintenance. As with so many things, the ideal is a healthy balance — and it doesn’t come without struggle. organizationinformationmakingwork
Internal design teams and thought leadership An Article by Jorge Arango jarango.com The design industry is an ecosystem. External design teams provide critical functions beyond augmenting internal design resources. Thought leadership — pushing the field’s boundaries — is indeed one of them. Many practices and tools we take for granted — journey maps, personas, conceptual frameworks — were pioneered and/or popularized by ‘outies.’ Most of the field’s foundational books and blogs are by people outside ‘client’ organizations. This isn’t because internal designers aren’t as clever or dedicated as their external colleagues. (Many ‘innies’ are former ‘outies.’) It’s because internal design roles are structurally misaligned with public thought leadership. designux
Not Just a New Feature; a New Compact A Fragment by Jorge Arango jarango.com My sense is that Slack’s teams think of themselves as adding ‘features’ to a ‘product,’ instead of as stewards of a place where people work. featuresplace
Mediocratopia An Article by Venkatesh Rao www.ribbonfarm.com I once read a good definition of aptitude. Aptitude is how long it takes you to learn something. The idea is that everybody can learn anything, but if it takes you 200 years, you essentially have no aptitude for it. Useful aptitudes are in the <10 years range. Leveling up aptitude You need to make the step forward skill
Leveling up aptitude Your first short story takes 10 days to write. The next one 5 days, the next one 2.5 days, the next one 1.25 days. Then 0.625 days, at which point you’re probably hitting raw typing speed limits. In practice, improvement curves have more of a staircase quality to them. Rather than fix the obvious next bottleneck of typing speed (who cares if it took you 3 hours instead of 6 to write a story; the marginal value of more speed is low at that point), you might level up and decide to (say) write stories with better developed characters. Or illustrations. So you’re back at 10 days, but on a new level. This kind of improvement replaces quantitative improvement (optimization) with qualitative leveling up, or dimensionality increase. Each time you hit diminishing returns, you open up a new front. You’re never on the slow endzone of a learning curve. You self-disrupt before you get stuck. The interesting thing is, this is not purely a function not of raw prowess or innate talent, but of imagination and taste. learningcreativitytastepractice