Impact of LLMs on the Tech Stack and Product Development - MLOps Podcast #188

Explore the impact of Large Language Models (LLMs) on tech stacks and product development in this insightful MLOps podcast episode featuring Anand Das, Co-founder and CTO of Bito. Discover how Anand's team developed the popular "explain code" Chrome extension and expanded it to other platforms. Learn about Anand's extensive background in tech, including his roles at Eyeota, PubMatic, and various engineering positions. Gain valuable insights into model evaluation, AI stacks for code understanding, prompt-driven development, and best practices for prompting and debugging code assistants. Delve into discussions on the cost-benefit analysis of GPU investments and the build vs. buy decision in machine learning. This 56-minute conversation covers a wide range of topics, from Anand's preferred coffee to the complexities of modern tech development, offering a comprehensive look at the evolving landscape of AI-driven software engineering.

[] Anand's preferred coffee
[] Takeaways
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[] Anand's tech background
[] Fun at Optimization Level
[] Trying all APIs
[] Models evaluation decision tree
[] Weights and Biases Ad
[] AI Stack that understands the code
[] Tools for the Guard Rails
[] Seeking solutions before presenting to LLM
[] Prompt-Driven Development Insights
[] Prompting best practices
[] Unneeded complexities
[] Cost-benefit analysis of buying GPUs
[] ML Build vs Buy
[] Best practices for debugging code assistant
[] Wrap up