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35 changes: 35 additions & 0 deletions src/routes/posts/whats_good_for_ai.mdx
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---
meta:
title: What's good for humans is good for AI and what's good for AI is good for AI
description: The same engineering practises that allow an AI to make effective use of a codebase, are the ones that allow humans to make effective use of the code base
dateCreated: 2026-06-25

tags:
- "ai"
- "software_engineering"

---

My software engineering approach as it relates to agnetic coding is that I'm not doing anything special to make the codebase AI-friendly.

Or rather, there's a whole bunch I'm doing, but these things aren't at any cost to humans, the things I'm doing make it easier for humans too.


Examples:

- Schema driven development
- Strong emphasis on static checks - linting
- Using code generators to create any code that can be inferred
- Having tests be the thing that helps me understand what a unit of code does
- Having a terminology.md file to create an explicit and unambiguous vocubulary for the project
- Creating decision trees


I think AI makes us _better_ programmers, because it forces developers to explicitly label assumptions.



I think as humans, we kind of kind of fuzz over gaps in context without realising.

If a human misunderstands something, we might correct the misunderstanding, but often it ends there, there isn't a corresponding update in the code base. Whereas an AI misunderstanding somethng will lead to an update in one of prompt files.

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