What happens when crypto collides with real-world regulation? In this episode, we unpack how stablecoins work, why they matter, and how they’re poised to disrupt everything from cross-border payments to brand loyalty programs. We also explore what developers and businesses should be thinking about as the lines between traditional finance and DeFi continue to blur.

Everyone’s talking about AI, but are you overlooking the real driver of developer productivity? On this episode of The Forward Slash, Dillon Courts, Callibrity’s Director of Platform Engineering, shares what he’s learned about building high-performing platforms, the real limits of the “everyone does everything” DevOps model, and why self-service tools are changing the game for software teams. He also explains why leaders who focus on eliminating inefficiency are pulling ahead of those who just follow tech trends.

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.

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.

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.

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.

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.

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.

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.

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.