DevSecOps Engineer, Author, and Mentor

This last part in the series of posts on my bootstrap project talks about making the project boring. In this case, boring is a very, very good thing.

Boring

The most important thing about this project was that it needed to be boring. Elegant over efficient and consistent over creative. It needed to be reliable.

Building boring meant lots of testing, lots of linting, lots of standards compliance verification. Each and every change required going through a battery of unit tests so that new changes were demonstrably safe with old code. If this project was to be documentation-first, then it would be testing-second. Each change was built by establishing tests first – tests designed to fail – that would only pass once the code was changed successfully.

After unit tests were built and verified, end-to-end testing needed to be included. To mimic a fresh, minimal environment as best possible, I used containerized end-to-end tests that started with only the slimmest of base functionality. It wasn’t sufficient to show that individual slices of logic worked as expected; the whole tool from start to finish needed to be verified.

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The first part of this series talked about not wanting to write code and how the deliverable for this project needed to be immediately useful on a fresh, minimal system. This next part talks about engineering practices and common AI problems.

Engineering Practices

There is a lot of AI-generated code out there, often called “slop.” It’s often sloppy, poorly-conceived, obtuse, and bordering on a level of design craft so as to resemble obfuscation. In many ways, a lot of it stands in opposition to the very principles I hold to be inviolate.

This experiment was to be something other than the hastily-generated code that has become a plague to modern development.

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Many of my recent posts have been about ethics and Generative Artificial Intelligence, particularly where Large Language Models (LLMs) are concerned. They’re about retaining humanity and ethics and personhood in a world that decreasingly values people, particularly when it comes to profit margins and returns on investment.

It might appear that I’m against AI. I am not. I am for respect and dignity and humanity. This post, therefore, will appear to be different from my latest writings.

This post talks about an experiment working with an AI to develop a well-engineered tool that is reliable, maintainable, understandable, and correct. This is about writing something that’s boring. Beyond the Principle of Least Surprise, my goal was to make this feel quiet and stable and honest.

This is not a demonstration of programming wizardry, excellence in Bash development, or fanciness. I’m not here to show any of that. I have a passion for Bash and script development because shell scripts are often seen as a list of commands to be executed in order of appearance. Bash is not associated with serious development. In fact, when I’ve taught classes on Bash development to senior, experienced engineers, the most common reaction is that they had no idea Bash could do the things I was demonstrating.

So, this is about my journey in building a tool that I needed using a language that I enjoy with the principles I use to shape my professional practices.

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