In many software companies the percentage of AI generated code is increasing at a fast pace. The code churn is accelerating due to both developer-led features and fully automated ‘AI cleanups and codemods’. Many developers feel much more productive and their number of landed changes has gone up significantly. The shipped code seems to work ok, if not the AI agent can root cause and fix bugs quickly.

AI makes it much easier to outpace shared understanding of the codebase. What is happening now in many large codebases is that teams keep shipping while quietly losing the plot.

AI tooling impact on the software industry is not uniform. The ‘YC startup bubble’ gets most attention and the commentary distorts the picture. Move fast and break things is simply not viable in many parts of the industry.

Take heavily regulated industries like finance. It’s easy to mischaracterize these companies as slow moving and even lazy, when in fact they are solving a harder problem. Generating plausible code faster is clearly useful. But a bank is not being asked to optimize for plausible code. It is being asked to produce changes that can be explained, reviewed, approved, operated, and defended later. Regulation does not make that pressure disappear. It changes the terms on which you are allowed to respond to it.

If you ever tried the recent slate of AI agents (post Opus 4.5) you probably went through a mental journey that is remarkably similar for all of us:

OMG, this thing is incredibly powerful, I can’t believe it managed to fix that bug / implement that feature / create this tool that I’ve been meaning to write for years

Quickly followed by:

OMG, we (software developers) are all cooked

If you carry on down that path, the next insight is more interesting. Yes, the cost/effort of plausible code generation has collapsed. But, the cost of delivering high quality, well tested and compliant software has not. Corporations rely on their software passing certain quality and legal bars, and none of these have fundamentally changed.

Think back to when you got your first computer and started writing code. That sense of wonder when “Hello World” appeared on your screen. The dizzying feeling that you could make this strange machine do what you told it to. This feeling is useful again. It’s much better to mess around with these new AI tools and get your hands dirty building stuff than to sit there having opinions about them.

Some of the readers of my Beyond Clojure blog series have asked about my opinion on clojure.spec, and if it solves Clojure’s ’type problem’. Implying whether its presence makes me look more favorably on Clojure. Here are some of my thoughts.

This is a post in the Beyond Clojure blog series, in which a Clojure developer looks at typed languages for web app development. In this episode we look at front-end development in the language Elm.

Front end development targeting web browsers is a ghetto, everybody seems to agree. The core tools at our disposal are the amalgamation of ideas and accidents thrown together without much overall strategy. One positive development in recent years has been the drastic improvement of the JavaScript (JS) engines in popular browsers. They have now gotten so good that it’s a valid option to treat JS as a compilation target. This fact is one of the drivers behind the explosion of JS transpilers, there are now literally hundreds of languages that (either primarily or as an after-though) can compile to JS. These languages range from light syntax improvements (ala CoffeScript) to full blown languages with big runtimes and everything in between.

This is a post in the Beyond Clojure blog series, in which a Clojure developer looks at typed languages for web app development. This is by no means a complete survey of the Haskell web development landscape, rather a random collection of thoughts.

If you are interested in typed functional languages one stands taller than the rest. It’s impossible not to get sucked into the Haskell vortex, but why fight it? In spite of its reputation of being extremely hard to learn and even harder to master, there are several excellent resources out there and you are guaranteed to learn lots of very valuable lessons.

Here we are, after five years of learning and later doing Clojure full time, I’ve come to the point where I am seriously looking around for alternatives. I’ve gotten very comfortable working in Clojure, and it has and will continue to serve me very well. But getting comfortable has a flip-side, you stop caring.

I recently tried to use Datomic in anger in a project. Here are some things I learned.