> if anything, by most traditional forms of evaluating software quality, the projects I work on are better than what they were 5, 10 years ago, using the same metrics as back then.
In this side sentence you're introducing so much vagueness. Can you share insights to get some validation on your claim? What metrics are you using and how is your code from 10, 5, 0 years performing?
I feel throwing in a vague claim like that unnecessarily dilutes your message and distracts from the point. But, if you do have more to share I'd be curious to learn more.
- 40x speed improvement
- Painless env setup
- 20 Second deploy
- 90+% test coverage
- Ability to quickly refactor
- Documentation
(The original system that I wrote with one other programmer 20 years ago took 1.5+ years to write. Modern rewrite: 2 days)
Not to be too negative but a lot of modern software complexity is a prison of our own making, that we had time to build because our programs are actually pretty boring CRUD apps with little complex business logic.
I'm a proponent of architectural styles like MVC, SOLID, hexagonal architecture, etc, and in pre-LLM workflows, "human laziness" often led to technical debt: a developer might lazily leak domain logic into a controller or skip writing an interface just to save time.
The code I get the LLM to emit is a lot more compliant with those BUT there is a caveat that the LLMs do have a habit of "forgetting" the specific concerns of the given file/package/etc, and I frequently have to remind it.
The "metric" improvement isn't that the LLM is a better architect than a senior dev; it's that it reduces the cost of doing things the right way. The delta between "quick and dirty" and "cleanly architected" has shrunk to near zero, so the "clean" version becomes the path of least resistance.
I'm seeing less "temporary" kludges because the LLM almost blindly follows my requests
It mostly works. CC's plan mode creates a plan by cleaning up first, then defining narrow, integrated steps. Mentioning "subtractive" and "yagni" appears to be a reliable enough way for an LLM to choose a minimal path.
To my mind these instructions remain incantations and I feel like an alchemist of old.
I’m trying out another, what I call the principle of path independence. It’s the idea that the code should reflect only the current requirements, and not the order in which functionality was added — in other words, if you should decide to rebuild the system again from scratch tomorrow, the code should look broadly similar to its current state. It sort of works even though this isn’t a real thing that’s in its training data.
It works relatively well but not always.
works for me.
Practical LLM Coding
