Writing tests with AI, but not LLMs

Ryan sits down with Galen Wolfe-Pauly, CEO of Tlon, to chat about calm computing and how humans can take back ownership of their data and digital world. They discuss the early internet’s evolution from individual creativity into today’s internet that turns users into products, Ga ...  Show more

Ryan hosts SmartBear’s VP of AI and Architecture Fitz Nowlan to explore how we’re moving away from old assumptions about software development, the challenges of testing MCP servers as LLM-driven agents introduce non-determinism that breaks tradition, and how data locality and dat ...  Show more

This episode is for complete beginners. I walk you through how to build your very first coding project using AI tools—even if you’ve never written a line of code. Together, we’ll create a personal project hub that automatically generates documentation and lets you build interacti ...  Show more

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Machine learning pipeline orchestration tools, such as SageMaker and Kubeflow, streamline the end-to-end process of data ingestion, model training, deployment, and monitoring, with Kubeflow providing an open-source, cross-cloud platform built atop Kubernetes. Organizatio ...

Machine learning models need updating - what's the reliable way to do it? While in Romania, Richard sat down with Annie Talvasto to talk about her work helping to build DevOps practices around machine learning: Building repeatable processes for data ingestions, cleaning, organ ...

Agentic engineering shifts the developer role from manual coding to orchestrating AI agents that automate the full software lifecycle from ticket to deployment. Using Claude Code with MCP servers and git worktrees allows a single person to manage the output and quality of an enti ...  Show more