GoKawiilMartin Fowler: 14 Apr 2026
I attended the first Pragmatic Summit early this year, and while there host Gergely Orosz interviewed Kent Beck and myself on stage. The video runs for about half-an-hour.
I always enjoy nattering with Kent like this, and Gergely pushed into some worthwhile topics. Given the timing, AI dominated the conversation - we compared it to earlier technology shifts, the experience of agile methods, the role of TDD, the danger of unhealthy performance metrics, and how to thrive in an AI-native industry.
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Perl is a language I used a little, but never loved. However the definitive book on it, by its designer Larry Wall, contains a wonderful gem. The three virtues of a programmer: hubris, impatience - and above all - laziness.
Bryan Cantrill also loves this virtue:
Of these virtues, I have always found laziness to be the most profound: packed within its tongue-in-cheek self-deprecation is a commentary on not just the need for abstraction, but the aesthetics of it. Laziness drives us to make the system as simple as possible (but no simpler!) — to develop the powerful abstractions that then allow us to do much more, much more easily. Of course, the implicit wink here is that it takes a lot of work to be lazy
Understanding how to think about a problem domain by building abstractions (models) is my favorite part of programming. I love it because I think it’s what gives me a deeper understanding of a problem domain, and because once I find a good set of abstractions, I get a buzz from the way they make difficulties melt away, allowing me to achieve much more functionality with less lines of code.
Cantrill worries that AI is so good at writing code, we risk losing that virtue, something that’s reinforced by brogrammers bragging about how they produce thirty-seven thousand lines of code a day.
The problem is that LLMs inherently lack the virtue of laziness. Work costs nothing to an LLM. LLMs do not feel a need to optimize for their own (or anyone’s) future time, and will happily dump more and more onto a layercake of garbage. Left unchecked, LLMs will make systems larger, not better — appealing to perverse vanity metrics, perhaps, but at the cost of everything that matters. As such, LLMs highlight how essential our human laziness is: our finite time forces us to develop crisp abstractions in part because we don’t want to waste our (human!) time on the consequences of clunky ones. The best engineering is always borne of constraints, and the constraint of our time places limits on the cognitive load of the system that we’re willing to accept. This is what drives us to make the system simpler, despite its essential complexity.
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