I listen to a lot of music, it’s a constant accompaniment to my work and our evening relaxing. I don’t use streaming services, every couple of weeks I buy a bunch of digital albums and listen to them every day until we’re ready for a new batch. Here’s my favorite six from last year’s listening.
Anthropic report on how their AI is changing their own software development practice. Most usage is for debugging and helping understand existing code Notable increase in using it for implementing new features Developers using it for 59% of their work and getting 50% productivity increase 14% of developers are “power users” reporting much greater gains
If you’re a regular reader of my site, you’ll have noticed that in the last few months I’ve been making a number of “fragments” posts. Such a post is a short post with a bunch of little, unconnected segments. These are usually a reference to something I’ve found on the web, sometimes a small thought
Gitanjali Venkatraman does wonderful illustrations of complex subjects (which is why I was so happy to work with her on our Expert Generalists article). She has now published the latest in her series of illustrated guides: tackling the complex topic of Mainframe Modernization In it she illustrates the history and value of mainframes, why modernization
Why does AI write like… that (NYT, gift link). Sam Kriss delves into the quiet hum of AI writing. AI’s work is not compelling prose: it’s phantom text, ghostly scribblings, a spectre woven into our communal tapestry. ❄ ❄ ❄ ❄ ❄ Emily Bache has written a set of Test Desiderata, building on some earlier writing from Kent Beck.
Rob Bowley summarizes a study from Carnegie Mellon looking on the impact of AI on a bunch of open-source software projects. Like any such study, we shouldn’t take its results as definitive, but there seems enough there to make it a handy data point. The key point is that the AI code probably reduced the
I’ve been on the road in Europe for the last couple of weeks, and while I was there Thoughtworks released volume 33 of our Technology Radar. Again it’s dominated by the AI wave, with lots of blips capturing our explorations of how to use LLMs and similar technology. “Agents” are the big thing these days
I find most writing on software productivity to be twaddle, but Nicole and Abi are notable exceptions. Here is my foreword to their just-published book. I’m at lunch with a bunch of senior technology managers, and one is regaling the table with his latest initiative to improve his software development teams. He’s launching a metrics
Software development has always resisted the idea that it can be turned into an assembly line. Even as our tools become smarter, faster, and more capable, the essential act remains the same: we learn by doing. An Assembly Line is a poor metaphor for software development In most mature engineering disciplines, the process is clear:
I’m very concerned about the security dangers of LLM-enabled browsers, as it’s just too easy for them to contain the Lethal Trifecta. For up-to-date eyes on these issues, I follow the writings of coiner of that phrase: Simon Willison. Here he examines a post on how OpenAI is thinking about these issues. My takeaways from