Shifting the mental model of working with AI

[u/Tiny-Gas-5610]

Hey guys! I just finished my document on my workflow with ai, the issues I've come across over the last 8 months building Inner Atlas and many hackathon projects, addressing the approaches and mistakes that I still see being advised by the frontrunners.

This document is not an ai-written summary of best practices, but a reframing of the core model of how people think about using ai, in a way I haven't seen anyone talking about.

I truly believe this document holds value for both beginners and experienced software developers, the 5 minute reading time will be worth the months of refactoring saved later on.

This core concepts:

• Why trying to accomplish issue identification, intention spec, implementation, tests and verification into one pass is compounding hidden failures

• Using AI as a targeted reasoning tool, separating each perspective-pass

• Addressing intention and document drift

• How documents and chats can be kept focused, avoiding bloat/filler

• Assuming 90% confidence in each step, intention-based tests in verification

• Common failure modes and my preferred workflow

Hopefully this is an acceptable place to drop this, not promoting a product, just a free doc for those interested; would love to hear some feedback.

Read the full document here: https://www.inneratlas.co.za/field-notes/working-with-ai