Loading…

The Stack Overflow Podcast

A peek behind the curtain with Stack Overflow’s sales engineers

In this episode, Alexa Montelibano and Tiago Torre, sales engineers at Stack Overflow, take you behind the scenes to show how customer feedback shapes our products, including OverflowAI. Alexa and Tiago have been working with clients to explore the three features of OverflowAI—Enhanced Search, an Auto-answer App for Slack and Microsoft Teams, and an IDE extension.

This startup uses a team of AI agents to write and review their pull requests

In this episode we chat with Saumil Patel, co-founder and CEO of Squire AI. The company uses an agentic workflow to automatically review your code, write your pull requests, and even review and provide opinions on other people’s PRs. Different AI systems with specific capabilities work together as a mixture of experts, following a chain of thought approach to provide recommendations on security, code quality, error handling, performance, scalability, and more.

Can software startups that need $$$ avoid venture capital?

Today's episode is a chat with Benjamin Shestakofsky, an assistant professor of sociology at the University of Pennsylvania with a focus on the ways in which digital technologies are affecting work and employment, organizations, and economic exchange. We discuss research from his new book which dives into the venture capital business and explores the cooperative model that some software startups are taking instead.

OverflowAI and the holy grail of search

Product manager Ash Zade joins the home team to talk about the journey to OverflowAI, a GenAI-powered add-on for Stack Overflow for Teams that’s available now. Ash describes how his team built Enhanced Search, the problems they set out to solve, how they ensured data quality and accuracy, the role of metadata and prompt engineering, and the feedback they’ve gotten from users so far.

The reverse mullet model of software engineering

Ben and Ryan are joined by software developer and listener Patrick Carlile for a conversation about how the job market for software engineers has changed since the dot-com days, navigating boom-and-bust hiring cycles, and the developers finding work at Walmart and In-N-Out. Plus: “Party in the front, business in the back” isn’t just for haircuts anymore.

Why configuration is so complicated

Ben and Ryan explore why configuration is so complicated, the right to repair, the best programming languages for beginners, how AI is grading exams in Texas, Automattic’s $125M acquisition of Beeper, and why a major US city’s train system still relies on floppy disks. Plus: The unique challenge of keeping up with a field that’s changing as rapidly as GenAI.

If everyone is building AI, why aren't more projects in production?

Ben talks with Shane McAllister, lead developer advocate at MongoDB, Stanimira Vlaeva, senior developer advocate at MongoDB, and Miku Jha, director, AI/ML and generative AI at Google Cloud, about the challenges and opportunities of operationalizing and scaling generative AI models in enterprise organizations.

How do you evaluate an LLM? Try an LLM.

On this episode: Stack Overflow senior data scientist Michael Geden tells Ryan and Ben about how data scientists evaluate large language models (LLMs) and their output. They cover the challenges involved in evaluating LLMs, how LLMs are being used to evaluate other LLMs, the importance of data validating, the need for human raters, and more needs and tradeoffs involved in selecting and fine-tuning LLMs.