We think of ourselves as full-time projects, but what if doing so much inner work does more harm than good?
Chasing life goals is a recipe for disaster – so try these tiny experiments instead
Whether its our careers, health or relationships, we often set the bar too high and end up feeling disappointed when it doesn’t work out. Try this new way of thinking … and you may just see some real results
I'm addicted to being useful
When I get together with my friends in the industry, I feel a little guilty about how much I love my job. This is a tough time to be a software engineer. The job was less stressful in the late 2010s than it is now, and I sympathize with anyone who is upset about the change. There are a lot of objective reasons to feel bad about work. But despite all that, I’m still having a blast. I enjoy pulling together projects, figuring out difficult bugs, and writing code in general. I like spending time with computers. But what I really love is being useful.
Doing nothing at work
Many engineers should be doing less work. I don’t necessarily mean producing less code or fewer changes, but literally working fewer hours in the day. When they do work, they should be working at a slower pace. I like to aim to be running at 80% utilization by default: unless I have a high-pressure project going on, I spend 20% of my workday away from the computer.
On Making
TLDR: I gain a lot of fulfillment by making things. I don't consider things built by others at my request to be made by me, and are therefore much less fulfilling. And then I feel sad. This article starts strong and then heads off into the weeds.
Are we offloading too much of our thinking to AI?
Reflections on autonomy and the value of thinking for ourselves
Selective Optimism: a critique of AI 2040
Some context for this post: I’ve been working part-time as a consultant for the AI Futures Project over the last year.
Work is a cult, here's how to escape
When AI builds itself
Our progress toward recursive self-improvement, and its implications.
‘Find Your Passion’ Is Awful Advice
A major new study questions the common wisdom about how we should choose our careers.
Notes on going solo: celebrating 6 years of Studio Self
Since roughly // broadly 2020, I’ve been running a solo-powered minor empire. I have no employees, and my only office is my home office…
I lost my UX career to AI (I'm done)
AI, I tried to love you – Writings and rehearsals by Nathan Schneider
Among my peers who study the cultures and economies surrounding technology, I often find myself more tech-positive than most. On the whole I like computers, like the internet, and like in general the emergent human creativity that these things have enabled and revealed. A source of my appreciation is that I expend a lot of effort on the practice of “slow computing,” which is to say, choosing tools and technical communities that I can feel in right relationship with. I tend to approach new socio-technologies (like gig economies, blockchains, and social media) not from a perspective of why is this so bad? so much as asking how could we do this right?
Arvind Narayanan (@aisnakeoil)
There’s a big, under-appreciated reason why people may have very different experiences and opinions about using AI for work — are they using it for tasks they’re already an expert at, or tasks they can’t do themselves? The former leads to a growth cycle and the latter leads to a dependence spiral. When I use AI to do something I’m an expert at, like coding, I treat it as a tool. I can build quickly, maintaining an understanding of the code, knowing that if necessary, I can fix the code myself. It feels empowering. It frees up my time to think about the complex, judgment-oriented parts of software engineering that I can’t or won’t delegate to AI. That means my own skills improve rapidly, and I get to climb the ladder of complexity and develop higher-level skills, much more so than when I write the code myself. I feel in control. I can lock in and achieve a flow state — when AI is working, I’m reviewing, building understanding, and planning the next steps. I never get the feeling that the tool is about to replace me. This is the growth cycle. (Of course, the growth cycle is not automatic. I still need to exercise agency to use AI responsibly. But it’s the same challenge with any productivity-enhancing technology, and those who’ve navigated such transitions before are well-equipped to navigate it with AI as well.) On the other hand, if I use it for tasks I don’t understand and haven’t learned to perform myself, I have no choice but to treat it as a superintelligence. If something breaks, the best I can do is ask AI to fix it and hope for the best. I generally can’t evaluate the quality of the output myself. The only way to find out if it's any good is if and when the work is ultimately reviewed by an actual expert. The experience is confusing, unsettling and disempowering. And forget about flow state. By over-relying on AI, I risk losing whatever skill I had at the task in the first place, even if it boosts productivity in the short term. This is the dependence spiral. It’s no wonder that entry-level workers and students preparing to enter the workforce find themselves in a bind. To compete with the AI-enabled productivity of more seasoned workers, they must adopt AI themselves, but doing so risks the dependence spiral. I have some thoughts on solutions that I will share in later posts, but I think having a clear diagnosis of the problem is a useful first step.
Maybe you should learn something
You can learn new things. Pixel art, touch typing, 3d modelling, music, calligraphy, wood working, knitting, a language. Whatever is practical and calls to you, you can learn. In the long term, learning new things is fun and makes life richer in ways you can’t even imagine, and it’s a time investment that will pay dividends for life as these skills never really go away. There are even social aspects, as you’ll quite literally become a more interesting person to talk to.
The AI productivity myth is more harmful than you think
Perceived productivity may be up thanks to AI, but there's debt collecting in the shadows.
