It's easy to understand why some programmers love their AI assistants and others loathe them: the former group get to decide how and when they use AI tools, while the latter has AI forced upon them by bosses who hope to fire their colleagues and increase their workload.
Pluralistic: AI solipsists and AI cynics (24 Jul 2026) – Pluralistic: Daily links from Cory Doctorow
As a technology, AI isn't exceptional. It's not exceptionally wicked. It's not exceptionally good. Take away the accompanying, galactic-scale stock-swindle, and we'd call AI's applications "plug-ins" and we'd use them and abuse them in the same way that we've used every other technology:
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.
Pluralistic: Which jobs can be replaced with AI? (06 Aug 2025) – Pluralistic: Daily links from Cory Doctorow
I don't think AI can do your job (but I do think an AI salesman can convince your boss to fire you and replace you with an AI that can't do your job). However, there is a class of workers whose jobs can be performed perfectly by AI: workers with bullshit jobs:
Developers say AI coding tools work—and that's precisely what worries them
Ars spoke to several software devs about AI and found enthusiasm tempered by unease.
Pluralistic: AI turns Amazon coders into Amazon warehouse workers (27 May 2025) – Pluralistic: Daily links from Cory Doctorow
On a recent This Machine Kills episode, guest Hagen Blix described the ultimate form of "AI therapy" with a "human in the loop":
AI | 2025 Stack Overflow Developer Survey
84% of respondents are using or planning to use AI tools in their development process, an increase over last year (76%). This year we can see 51% of professional developers use AI tools daily.
Usage, Effects and Requirements for AI Coding Assistants in the Enterprise: An Empirical Study
The rise of large language models (LLMs) has accelerated the development of automated techniques and tools for supporting various software engineering tasks, e.g., program understanding, code generation, software testing, and program repair. As CodeLLMs are being employed toward automating these tasks, one question that arises, especially in enterprise settings, is whether these coding assistants and the code LLMs that power them are ready for real-world projects and enterprise use cases, and how do they impact the existing software engineering process and user experience. In this paper we survey 57 developers from different domains and with varying software engineering skill about their experience with AI coding assistants and CodeLLMs. We also reviewed 35 user surveys on the usage, experience and expectations of professionals and students using AI coding assistants and CodeLLMs. Based on our study findings and analysis of existing surveys, we discuss the requirements for AI-powered coding assistants.
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 Software Engineering Is Indispensable in the Age of Coding Agents
Can AI make Software Engineering (SE) -- the discipline -- obsolete? And can it make software engineers -- the professionals -- redundant? This paper argues that the rise of capable AI coding...
AI vs human code gen report: AI code creates 1.7x more issues
We analyzed 470 open-source GitHub pull requests, using CodeRabbit’s structured issue taxonomy and found that AI generated code creates 1.7x more issues.
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
AI Is a Waste of Time
The newest AI tools are accelerating basic research and scaring the general public. But many people are simply using them as toys.
Is AI ruining our skills? Early results are in — and they’re not good
Reliance on artificial-intelligence tools degrades the abilities of physicians and software engineers, studies show.
How teams build – Linear
AI usage patterns in software teams: who is adopting AI, how it reshapes where teams spend their time, and how much more they ship.
Nassim Nicholas Taleb on Twitter / X
The problem isn’t that AI is intelligent. It isn’t. The problem is that too many adults (but not all) are at once mechanistic, imitative, unimaginative, stupid, formulaic, influenceable, & gullible, arrogant beyond their skill set, & too expensive to maintain.— Nassim Nicholas Taleb (@nntaleb) October 24, 2026
How building software is changing at Anthropic
A deepdive on what’s changed in how the leading AI lab makes software. Ever more code review and testing is done by AI, two-pizza teams very much alive, and more. Details from inside of Anthropic
