Thoughts on slowing the fuck down
What happens when AI replaces the parts of work people love?
We’re using AI to move faster. I’m not yet convinced we’re using it to work better.
How to reclaim your attention from the distraction economy | Psyche Videos
Could you watch this video on full screen, 1x speed, with no distractions? Here are five steps to rebuild your attention span
Every layer of review makes you 10x slower
We’ve all heard of those network effect laws: the value of a network goes up with the square of the number of members. Or the cost of commun...
Games Done Quick's Long, Difficult Journey To A Better Gaming Future
Progress isn't linear, and there are no skips or shortcuts
My Modified Couch to 5K Running Program
I found the official program too aggressive, so I modified it to give a more gradual increase in duration.
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.
Software Acceleration and Desynchronization
A look at the ever-present drive to make software delivery faster and how it might break down various activity loops in organizations.
When AI builds itself
Our progress toward recursive self-improvement, and its implications.
Harnessing Frustration: Using LLMs to Overcome Activation Energy
One of my biggest weaknesses as a software engineer is procrastination when facing a new project. When the scope is unclear, I have a tendency to wait until I feel I’ve “felt out” the problem to start doing anything. I know I’ll feel better and work much faster when I get “stuck in” but I still struggle with that first step, overcoming the “activation energy” required to engage with the details. LLMs have been a game-changer for me in this respect: I can just throw a couple of sentences at them with the shape of the problem. This leads to one of two outcomes: The LLM comes up with a good solution, usually in a slightly different way than what I was thinking. I realize “oh wow the solution is much simpler than I thought”. Straight away I start thinking about the consequences of implementing and improving what the LLM suggested. The LLM comes up with a solution that I intuitively recognize as “wrong”. My immediate reaction is frustration (“How could it get it so wrong”) which leads me to go back and forth with the model, explaining to it why its solution could not possibly work. But in the process of arguing with the model, my brain is churning away and generating variations or different approaches that could work. After a while, even if the AI is still on the wrong track, the debate will trigger a moment of inspiration where suddenly the solution will come to me. I’ll excitedly start up a new conversation and start working through it with the model. The key is the emotional reaction I have immediately to the LLM’s response, either excitement or frustration. By harnessing this immediate feedback loop, I get my brain out of its passive, procrastination mode. It’s almost like a jolt: either I’m thrilled because it’s simpler than I thought, or I’m spurred to action by the urge to correct a perceived ‘wrong’ answer. This forces me to engage with the problem in a meaningful way.
The wandering mind: A gift we squander - Darius Foroux
Most people treat a wandering mind like a defect. They see it as a leak in their productivity bucket. We’ve been conditioned to believe that if we aren’t staring at a screen or checking off a to-do list, we are failing. But Daniel Goleman, the […]
Do not give up your brain
It's tempting to just let tools think for you, but you still need to be able to think for yourself and stay sharp.
AI Doesn’t Reduce Work—It Intensifies It
One of the promises of AI is that it can reduce workloads so employees can focus more on higher-value and more engaging tasks. But according to new research, AI tools don’t reduce work, they consistently intensify it: In the study, employees worked at a faster pace, took on a broader scope of tasks, and extended work into more hours of the day, often without being asked to do so. That may sound like a win, but it’s not quite so simple. These changes can be unsustainable, leading to workload creep, cognitive fatigue, burnout, and weakened decision-making. The productivity surge enjoyed at the beginning can give way to lower quality work, turnover, and other problems. To correct for this, companies need to adopt an “AI practice,” or a set of norms and standards around AI use that can include intentional pauses, sequencing work, and adding more human grounding.
Changes to our Contribution Policies – Godot Engine
Godot is growing fast, so here is how we are dealing with the huge increase in contributions.
Holdfast 0: Situating
This post introduces the written version of some optimistic and constructive thinking on knowledge in networks that I’ve been wrestling with since the end of last year.
The Friction I Don't Want to Lose
I love learning. And while the friction of solving new problems is increasingly traded for speed, the experience gained by overcoming that friction is as important as ever.
