Build the shittiest thing possible. Build out of trash because all i have is trash. Trash materials, trash bodies, trash brain syndrome. Build in the gaps between storms of chronic pain. Build insi…
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Dependency cooldowns turn you into a free-rider
Against dependency cooldowns as a response to supply chain attacks
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.
How creatives and devs can all finally escape the control of the silicon valley of evil and make a trillion dollars · Multi-hyphenate
ft. ATprotocol (the remix)
How the hypercuriosity of ADHD may have helped humans thrive | Aeon Essays
ADHD isn’t merely a dysfunction. It’s best understood as an impulsive motivational drive for novel information
The flat-pack skyscraper: how wood can shape the cities of the future
The long read: Our buildings are monuments to extraction and extreme emissions. But what if we turned from destructive concrete to timber?
You don’t have to enjoy everything - some things aren’t for you | Respec
If that new game announcement has left you feeling cold, so what?
AI fatigue is real and nobody talks about it | Siddhant Khare
You're using AI to be more productive. So why are you more exhausted than ever? The paradox every engineer needs to confront.
Shape Up: Stop Running in Circles and Ship Work that Matters
Shape Up will help you break free of “best practices” that aren’t really working, think deeper about the right problems, and start shipping meaningful projects your team can celebrate.
Reducing the cognitive load of AI changes
When reviewing large amounts of AI-generated code, I often find that the LLM chooses terms for abstractions that do not always map to my own choices. For instance, what it may call a MutationIntent might personally be more natural to me as an EditRequest. Because the LLM's choice of words is not my ideal choice, I have to do a mental lookup of what it means every time I see it, which adds cognitive load.
How creatives and devs can all finally escape the control of the silicon valley of evil and make a trillion dollars - Multi-hyphenate
ft. ATprotocol (the remix)
in progress works
lightweight accountability community and journal for your side projects
‘Shut up and focus on the mission’: Tech workers are frustrated by their companies’ silence about ICE
“I’ve hit my limit of what I’m willing to tolerate”
The future is low-tech: lessons from the early 2000s ft. Jésabel DC | Config 2026