Most people think of budgeting as restrictive, tedious, or something they’ll “get around to.” But what if it didn’t have to be that way? In this episode, we explore how technology, AI, and a little human coaching are reshaping not only how we manage money—but how modern platforms are blending automation with personal connection to drive real, lasting change. From building better financial habits to scaling a startup, it all comes down to aligning your tools—and your spending—with what matters most.

/tech meets money: a new way to budget

How did coding go from something niche and isolating to one of the most valuable skills in the modern workforce?
In this episode of Forward Slash, we look at how the role of the developer has evolved—from outsider status to essential strategist. Drawing on decades of experience, Mark Stahl shares how the culture around coding has changed, and why understanding systems, context, and collaboration now matters more than syntax. We also explore the often-overlooked power of clear requirements—how they bridge the gap between business needs and code, and why they’ll matter even more in an AI-driven future.

/coding culture: from nerd to necessary

How do you build user-centered digital products in a world obsessed with trends and AI hype?
In this episode, UX researcher and digital psychologist Dr. Nick Fine joins James to share expert insights on human-centered design, behavioral science, and the real meaning of user experience. Learn how to apply UX research methods that drive product success, avoid common pitfalls in agile teams, and use AI tools without sacrificing product integrity.

/design culture: too many cooks

Wrangling APIs? Dreaming about AI agents that actually get your specs? This episode delivers. We chat with Dave Shanley (aka quobix)—a musician-turned-engineer with a sci-fi streak—about cutting through the noise of OpenAPI standards, building tools developers actually want to use, and how to stay grounded while navigating the fast-moving world of agentic AI.

/API sprawl: herding the chaos

Curious how AI can turn messy, unstructured data into something actually useful? This episode, we dive into a real-world project that explores just that. Senior developer Azriel Alvarado shares how building a song recommendation tool based on lyrics led to deeper insights into embeddings, vector search, and working with natural language data. Whether you're in search, content tagging, knowledge management, or building smarter user interfaces—this episode is packed with takeaways for applying AI in meaningful. ways.

/ML basics: learning by doing

What separates teams that build features from those that solve problems? Ryan Donnelly, product leader and proud Callibrity alum, shares how his engineering roots shaped his approach to driving impact at scale. He unpacks the mindset behind modernizing in-house payments, building with empathy, and leading through storytelling. If you're navigating tech, product, or leadership—this one's for you.

/technical storytelling: speak so they listen

Can you build a working AI chatbot without any prior AI knowledge? Rachel did—and here’s how. In this episode, senior software developer, Rachel Clifton joins James to share how she tackled her very first AI project—building a Retrieval-Augmented Generation (RAG) chatbot from scratch. Rachel breaks down the beginner-friendly tools that made it possible, including Spring AI, Apache Tika, and PGVector, and opens up about the challenges of chunking, hallucinations, and missing metadata. If you’ve been curious about AI but don’t know where to start, this episode is a practical, encouraging place to begin.

/generative AI: beginner's guide

What do toddlers learning to walk and robots learning to cook soup have in common? In this episode, data scientist Steven Nord joins James to explore the fundamentals of reinforcement learning (RL)—a key concept in machine learning and artificial intelligence (AI)—and its real-world applications in predictive maintenance, automation, robotics, and AI-powered systems. They explain the differences between supervised learning, unsupervised learning, and reinforcement learning, and how models like ChatGPT use Reinforcement Learning from Human Feedback (RLHF) to improve performance and accuracy.

/reinforcement learning: feedback is fuel

Can your software handle failure—or write its own test code? In this episode, we dive into temporal workflows, agentic AI, and no-code automation tools like N8N to explore how developers can build resilient, scalable applications faster. Learn how to navigate unreliable APIs, implement AI-powered code generation, and prototype with no-code platforms to supercharge your software development process.

/resilient systems: fail-proof by design

Is QA slowing you down? We unpack why traditional, siloed QA creates friction—and how a player-coach approach to test automation can embed quality across your team. Learn how shifting the mindset from “quality as a function” to “quality as a culture” leads to faster feedback, stronger collaboration, and better software.
Perfect for CTOs, tech leads, and teams ready to level up their delivery.

James Carman

Shows