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.
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.
AI Isn’t Lightening Workloads. It’s Making Them More Intense.
The technology is increasing the speed, density and complexity of work rather than reducing it, a new analysis of 164,000 people’s work activity shows.
Run Workers for up to 5 minutes of CPU-time
Workers now support up to 5 minutes of CPU time per request. Allowing more CPU-intensive workloads.
You can code only 4 hours per day. Here’s why.
Most of us have felt it: after a few solid hours of coding, your brain starts shutting down.
In 2026, I’m no longer interested in ‘working on myself’
We think of ourselves as full-time projects, but what if doing so much inner work does more harm than good?
AI Is Forcing Employees to Work Harder Than Ever
Another new study adds to the understanding that AI is actually making work more demanding for employees instead of making it easier.
Do AI-enabled companies need fewer people? | Seldo.com
AI-native startups are doing more with less — 40% smaller teams, 6x higher revenue per employee — and the data confirms it's not just hype. But the wave of new jobs I predicted hasn't materialized so far. Compute is replacing labor. Will that change?
Why developers using AI are working longer hours
Studies find AI helps developers release more software—while logging longer hours and fixing problems after the code goes live
AI tools are 'deskilling' workers, philosophy professor says
A philosophy professor warns that AI reliance is weakening workers' judgment, creativity, and problem-solving.
Less is more, more or less
In the age of AI, knowing what not to build might be the most important skill of all.
Super Productivity – Open-Source Deep Work Task Manager
The open-source deep work task manager for developers. Plan tasks, track time & notes in a privacy-first workspace for Windows, macOS, Linux, Android & iOS.
Anarchy and modern convenience
A major part of anarchy and socialism is the concept of anti-work. An obsession with work is a colonial, patriarchal, and capitalist construct. As such, the anti-work movement—a focus on working less overall and sharing labor more equally—is an important part of decolonization, feminism, and anti-capitalism. A common criticism of this is that reducing the amount everyone works to something like 20 hours a week instead of 40+ means we would have to give up a lot of conveniences.
AI Doesn’t Reduce Work—It Intensifies It
Aruna Ranganathan and Xingqi Maggie Ye from Berkeley Haas School of Business report initial findings in the HBR from their April to December 2025 study of 200 employees at a …
It's getting harder to focus every day
I’m feeling it right now. I had to set a timer for 15 minute on my computer and block all distractions to write this. If I didn’t force myself to focus I would easily get distracted by something after few minutes. Even when I’m doing things that I’ve been waiting to do it, I still feel the urge to do something else. I don’t know how and when this happened. During the last few years I was always studying, working, and doing open source. And actually got stuff done. Doing all of those at the same time requires paying attention to what I wanted to do and ignore the noise.
Intelligence Per Watt
From 1946 to 2009, computing efficiency—performance per watt—doubled every 1.5 years. This trend, documented by Koomey and colleagues, transformed where computing could happen. Workloads migrated from mainframe rooms to desktops, then laptops, then pockets. The transition from centralized time-sharing to personal computing didn't occur because PCs surpassed mainframes in raw performance. It occurred when efficiency gains made computing capable enough within the power constraints of personal devices.