Resources: Many roads to Rome

No perfect path, just make a start.

Quick notes (make Toc):

LLMs

AI Engineering: Building with Foundation Models (Chip Huyan)

If I had to repeat my Gen Ai learning curve last year 2024:

  • I’d stop trying to read papers
  • I’d stop scrapping about on newsletters
  • I’d still watch YouTube videos, but less so
  • I’d read this “one place most things” book

.

Although when I asked, many people told me there aren’t books that are keeping up with the rapid expansion. Turns out I’m not on the bleeding edge either. I would have read this book at the beginning (with expectation of not understanding everything, and that I would read it a few times again later as I learnt more with practice). I’d even read it before I struggled on learning how to prompt and evaluate effectively. I would read it before building a play product, and ideally before having to be in a team that does.

More:

  • What we learnt from a year of developing with LLMs
  • GoDaddy in the trenches
 

Prompting

  • Anthropic conversation
  • YT video with Human in the Loop
  • Anthropics Github courses
 

ML Ops

 

Product

  • My best bible books + Rory Sutherland
  • Lenny’s two interviews on AI
  • Marty interview on the ridiculousness of “agile” roles
  • Claire Vo (LaunchDarkly) on the augmented PM
 

Courses I found useful

Before

After