What did we actually learn about AI this year?
To close out 2025, James interviews an unexpected guest: ChatGPT. They talk honestly about what teams got wrong, what actually improved, and why AI’s biggest wins came from small workflow shifts — not sweeping transformation. They also dig into software engineering, documentation, onboarding, junior engineers, and what tech leaders will need to operationalize in 2026 as AI becomes a system, not a tool.

What if the systems we rely on every day fail because they were never designed for how work actually happens? This week, we sit down with product design leader and founder Sharmeen Aqeel to explore how human-centered design and AI are reshaping how products get built, decisions get made, and businesses move forward. Sharmeen shares how deep user research exposes where traditional processes break down, how simplifying workflows creates speed without sacrificing trust, and why AI is becoming a true partner in modern product design and entrepreneurship. 

What happens when shipping software is no longer limited by human hours? This week, Max Heckel — CTO of Ariso and creator of the open-source AI orchestrator “Ivan” — breaks down how his team literally codes while they sleep. Max shares how AI coding agents can tackle tasks overnight, open PRs by morning, double development velocity, and redefine what engineering teams focus on. This conversation is a roadmap to what’s coming next.

What if the real key to transformation isn’t more technology, but more humanity?
This week, Nora Osman joins James to explore why simplicity, trust, and human experience are the real engines of organizational change. From zero-to-hero moments to the “red carpet in, red carpet out” philosophy, Nora shows how better leadership—not bigger tech stacks—drives lasting results.

Can your AI agents survive production AND your budget? In this episode, Yaron Schneider, CTO and co-founder of Diagrid and creator of the foundational open-source tools Dapr and KEDA, joins James to unpack what it takes to build AI agents that are durable, cost-aware and enterprise-ready.

In this episode of The Forward Slash, James talks with Michael Pompey, AI Evangelist at Arrow Electronics, about the messy middle between innovation and impact. They discuss lessons from mission-driven organizations, the danger of chasing hype, and why the next evolution of transformation will be adaptive, not architectural. From AI to governance to leadership trust, this conversation is a candid look at what actually drives change in organizations.

What if your transformation plan is the thing holding you back?

This week, James welcomes Carol Houle, CEO of Inspire Digital Consulting, to dive into the mindset shift from rigid planning to adaptive execution. They explore how to connect OKRs to customer value, replace feature wish lists with measurable outcomes, and finally move from building more to building what matters.

Has AI finally met its moment of truth?
This week, James sits down with Jim Spignardo, Director of Cloud Strategy & AI Enablement at ProArch, to explore how enterprises are moving from curiosity to competence with AI. They talk data, security, productivity, and the shift from “let’s try AI” to “let’s solve real problems with it.”

What if AI could hear what doctors can’t?

This week James welcomes, Dr. Morris Nguyen, founder and CEO of Predicate, to explore how AI is transforming healthcare by combining patient voice and vital signs to detect critical illness early. Morris shares his journey from critical care physician to tech founder, what it takes to bridge medicine and machine learning, and why empathy may be AI’s most powerful feature. Together, they unpack what it means to build predictive, equitable healthcare technology, and the surprising challenges of scaling real-world innovation.

Is platform engineering the missing link in real AI adoption?

This week, we welcome Matan Grady, lead AI PM at Port, to unpack why platform engineering is the control plane for AI adoption. We cover the move from chat UIs to agentic workflows, what it takes to trust AI in production (secrets, permissions, guardrails, human-in-the-loop), and how MCP servers connect agents to calendars, docs, and code. Matan explains why AI evals should measure outcomes—not outputs—and shares a real win: turning a manual changelog into an AI agent PMs simply review. Its a pragmatic look at developer portals, coding agents, and the evolving role of engineers as orchestrators who architect, observe, and ship faster.