Vibe coding is building a software application by prompting an LLM, telling it what to build, trying it out, prompting for changes – but without looking at any of the code that the LLM generates. This technique can be used by people without any knowledge of programming. However the resulting software often shows problems with
There are multiple dimensions we usually want to achieve and monitor in our codebases: Functional correctness (works as intended), architectural fitness (is fast/secure/usable enough), and maintainability. I define maintainability here as making it easy and low risk to change the codebase over time – also known as “internal quality”. So I don’t only want to
There are multiple dimensions we usually want to achieve and monitor in our codebases: Functional correctness (works as intended), architectural fitness (is fast/secure/usable enough), and maintainability. I define maintainability here as making it easy and low risk to change the codebase over time – also known as “internal quality”. So I don’t only want to
Last week I spent a day at a retreat that brought together several people working in software development to talk about the profession’s future with the rise of agentic programming. The event was help under the Chatham House Rule, so I can’t attribute the comments and stories I heard. (If anyone recognizes themselves, and would
When we need an LLM to perform a complex task, we often need to feed it a lot of context. Coming up with a design for a new feature requires descriptions of how we want the feature to appear to the user, guidelines on how it should be implemented, information on external systems to consult,
What is code? At a high level, the answer to this question seems obvious. Code is what developers write: instructions expressed in a programming language that tells machines what to do. For years, writing code meant typing it out, word by word. Progress is measured by how efficiently code can be produced, compiled, tested and
In the early 1960s, Fred Brooks managed the development of IBM’s System/360 computer systems. After it was done he penned his thoughts in the book The Mythical Man-Month which became one of the most influential books on software development after its publication in 1975. Reading it in 2026, we’ll find some of it outdated, but
Over the last couple of months Rahul Garg published a series of posts here on how to reduce the friction in AI-assisted programming. To make it easier to put these ideas into practice he’s now built an open-source framework to operationalize these patterns. AI coding assistants jump straight to code, silently make design decisions, forget
Chris Parsons has updated his guide on using AI to code. This is his third update, what I like about it is that he gives a lot of concrete information about how he uses AI, with sufficient detail that we can learn from him. His advice also resonates with the better advice I’ve seen out
Once a team adopts AI coding assistants, the first gains show up at the individual level: one developer can draft, modify, and refactor code much faster than before. But delivery speed is rarely limited by typing. When you look at the full delivery lifecycle, from requirements through release, new friction appears: Ambiguous requirements become code