Building with Ash, Before & After AI

It’s been almost two years since I built something with Ash, and LLMs have significantly changed my workflow since then. After trying it on a new side project this month, I have some new thoughts on Ash.

LLMs have made the task of generating working code much easier. This means that the human programmer spends a larger portion of their coding time reviewing code. I think the benefits of Ash shine brighter in this scenario. I wrote a longer form version of this here.

I’d be curious to hear other opinions on a thought experiment:

If LLMs got 5x better than they are today at quality, speed & cost. Assuming you can very quickly be presented with working code that at least achieves a reasonable interpretation of the initial prompt.

If in this new reality, your responsibilities as a software engineer is:

  1. Ensure that the resulting code does what the business needs.
  2. Ensure that it’s built in a way that when the stakeholders change their minds, the resulting changes will be made in a reasonable timeframe.
  3. Ensure that when other engineers or LLMs come to work on the project, they can copy the existing patterns without making you sad.
  4. Ensure that we can either handle the “ilities” (reliability, observability, usability, maintainability, operability, etc.) now, or can make reasonable changes (no re-writes) to handle them if we run into massive success & scale in the future.

In that utopian/dystopian future, would you rather be reviewing Ash code or something else?

In my opinion, Ash wins here because I would have so much less code to review and because different dimensions of the same functionality (auth, code interface, relationships, persistence) are all organized in a way that I can review one of those dimensions at a time without having to load all the others into my brain.

What would you choose?

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