High Agency: The Podcast for AI Builders

Sourcegraph have built the most popular open source AI coding tool in both the dev community and the Fortune 500. I sat down with Beyang Liu their CTO and cofounder to find out how they did it.We dive into the technical details of Cody's architecture, discussing how Sourcegraph handles the challenges of limited context windows in LLMs, why they don't use embeddings in their RAG system, and the importance of starting with the simplest approach before adding complexity.We also touch on the future of software engineering, open-source vs closed LLM models and what areas of AI are overhyped vs underhypedI hope you enjoy the conversation!Chapters- 00:00:00 - Introduction- 00:02:30 - What is Cody, and how does it help developers?- 00:04:15 - Challenges of building AI for large, legacy codebases- 00:07:30 - The importance of starting with the simplest approach- 00:11:00 - Sourcegraph's multi-layered context retrieval architecture using RAG- 00:15:30 - Adapting to the evolving landscape of LLMs and model selection- 00:19:00 - The future of software engineering in the age of AI- [00:23:00 - Advice for individuals navigating the AI wave- 00:26:00 - Predictions for the future of AI in software development- 00:30:00 - Is AI overhyped, underhyped, or both?- 00:33:00 - Exciting AI startups to watch--------------------------------------------------------------------------------------------------------------------------------------------------Humanloop is an Integrated Development Environment for Large Language Models. It enables product teams to develop LLM-based applications that are reliable and scalable. To find out more go to  https://hubs.ly/Q02yV72D0

Bryan Bischof, AI lead at Hex, shares insights on evaluating LLMs for reliable AI agents. Hex's unique framework enabled them to ship with confidence. Key ingredients to Hex's success include choosing the right tools, using a reactive DAG for course-correction, building user-centric evaluators, gating releases on meaningful metrics, and scrutinizing model inputs & outputs. The podcast discusses data analysis in AI engineering, agent capabilities development, efficiency in using agents at Hex, prompt engineering with GPT-4 Turbo, challenges in evaluating Language Models, and empowering non-technical experts in AI product building.

CTO of Ironclad, Cai GoGwilt, talks about using generative AI in contract negotiation. Ironclad's success in deploying AI agents in sensitive industries. Building a visual programming language for reliable agents. Advice for AI leaders starting product development.

Welcome to very first episode of the High Agency podcast! High Agency is a new podcast from Humanloop.Every week, I (Raza Habib) will interview leaders from companies, who have already succeeded with AI in production.  We'll share their stories, lessons and playbooks to help you build with LLMs more quickly and with confidence.To get notified of the first episodes with Cai Gogwilt or Ironclad, Bryan Bishof of Hex, Beyang Liu of Sourcegraph and Wade Foster of Zapier please subscribe on youtube, spotify or apple podcasts! (just search for High Agency podcast)----------------------------------------------------------------------------------------------------------------------------------------Humanloop is an Integrated Development Environment for Large Language Models.It enables product teams to develop LLM-based applications that are reliable and scalable.Principally, it lets you rigorously measure and improve LLM performance during development and in production. The evalutation tools are. combiined with a collaborative workspace where engineers, PMs and subject matter experts improve prompts, tools and agents together.By adopting Humanloop, teams save 6-8 engineering hours each week through better workflows and they feel confident that their AI is reliable.To find out more go to https://hubs.ly/Q02z2J6v0