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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.
+