AI Engineering

I build software wrapping LLM APIs. This requires me to monitor social media to understand what’s happening in the weird world of LLMs, build prototypes to check technical feasibility and finally build production ready features considering not just functionality, but cost, latency, monitoring and maintainability.

Below are some of my go to resources which I frequently visit at different phases of this LLM engineering life cycle.

• Chat Bots for daily use
  • ChatGPT, Gemini, Claude
• Playgrounds to try different models
  • Azure OpenAI, Google AI Studio
• LLM Leaderboards to review performance of models
  • Artificial Analysis
  • LMArena
  • Seal
• Development of code, prompt
  • OpenAI : Docs, Cookbook, Build hours Videos (Webinar, vimeo, academy) & Code
  • Anthropic: Courses, Cookbook, Developer Guide
  • Arize AI: Prompt templates
• AI Assisted Coding (as development tool)
  • Github Copilot, Roo Code
  • Leaderboard: Aider, LiveBench
  • Model Selection: Guide by Cursor, Github Copilot
• Newsletters
  • AINews
• Courses
  • Deeplearning.ai (Short Courses)
• Blogs
  • Anthropic Engineering
  • Hamel’s blog
  • Eugene’s blog
  • Simon Willison’ Weblog
• Videos
  • Anything by Andrej Karpathy (YouTube)
  • AI Engineer