Why do solo game developers tend to get into fights with big tech engineers? Why do high-profile external hires to large companies often fizzle out? Why is AI-assisted development amazing for some engineers and completely useless for others?
AI makes weak engineers less harmful
Like other kinds of puzzle-solving, software engineering ability is strongly heavy-tailed. The strongest engineers produce way more useful output than the average, and the weakest engineers often are actively net-negative: instead of moving projects along, they create problems that their colleagues have to spend time solving. That’s why many tech companies try to build a small, ludicrously well-paid team instead of a large team of more average engineers, and why so far this seems to be a winning strategy.
Why AI Makes Things Worse for Enterprise Teams, by Paul Ford
Why are so few engineering teams reaping the benefits of AI? On this week’s episode, Paul presents Rich with the findings from a recent report from CircleCI and
Does AI Actually Boost Developer Productivity? (100k Devs Study) - Yegor Denisov-Blanch, Stanford
Why AI hasn’t replaced software engineers, and won’t
Coding agents as normal technology
The Real Reason We Still Need Software Developers in the World of AI
The dream of AI churning out perfect production-ready code doesn’t hold up against the reality of modern software development.
Why AI hasn’t replaced software engineers, and won’t
Arvind Narayanan and Sayash Kappor take on the question of AI job losses through the lens of a profession that is uniquely suited to AI disruption - software engineering. In …
What Actually Happens When Programmers Use AI Is Hilarious, According to a New Study
As AI takes the programming world by storm, experienced devs are still the gold standard — and they're better off without AI assistance, too.
Engineering managers have a new job description
Why engineering managers are expected to be hands-on again and how AI tools are making it possible to stay technically sharp while still leading.
Impressions from visiting OpenAI, Anthropic, & Cursor
A peek into where software engineering is headed from inside the sector’s leading AI labs. Agents running in the cloud are a major trend, while coding harnesses are spreading beyond the craft
Why so many game developers don't want to use generative AI
With credits ranging from Dispatch and Marvel Rivals to Uncharted and Dragon Age, over 30 devs share their thoughts on gen AI
AI is removing the middle class of software engineering
AI makes projects with weak engineering culture fail much faster.
The Productivity Is Real. The Scaling Isn't.
What running an AI agent team taught me about why organizations can't do what one person can.
Why the tech industry can't keep up with the AI backlash
AI's externalities are growing faster than the industry can address them
One Developer, Two Dozen Agents, Zero Alignment
Why we need collaborative AI engineering and a tour of Ace: the multiplayer coding workspace
"AI makes it cheaper to contribute to Open Source, but it's not making life easier for maintainers. More contributions are flowing in, but the burden of evaluating them still falls on the same small group of people. That asymmetric pressure risks breaking maintainers." also relevant to slop science
Economic incentives is a big problem with AI in open-source spaces. Finding is unevenly allocated, and AI leads to further disparity. Instead of spreading money around the dev community, it'll go to AI companies. Open source thrives on humans. We don't need rockstars, we need resources.
Lucca @ Northsky 💚💜
they should be giving out more of that to the community as grants and focusing on protocol governance and standards and bringing new people into atproto.
