Michael Carducci
Software Architect & Magician
Michael Carducci spent years learning to see things as they actually are; first as a magician, then as a software architect, now as both simultaneously. And somehow that’s not even the whole story.
He’s the author of Mastering Software Architecture (Apress, 2025) and is currently writing The Semantic Layer. He has spent over 25 years following interesting problems; through roles from individual contributor to CTO and back again, across industries and continents.
As a speaker, he applies the same toolkit he uses in close-up magic: attention, misdirection, timing, storytelling, and the instinct to take the long way around when that’s where the truth lives. Audiences at hundreds of conferences across four continents have described his talks as the kind that change how you think about a problem rather than just what you know about it.
He also makes YouTube videos about technology and curiosity with his wife Kate, because some ideas are too important (or too interesting!) to leave only in conference rooms.
Presentations
In tech teams it's a constant firefight. We react. Then we react to the reaction… the cycle continues. In all this noise, in all this chaos, how do we move forward. How do we remain proactive?
A great leader must be an enabler for the team. At times this means insulating the team from the noise. At other times it means improving the environment for the team. At all times, however, it requires setting clear priorities and conditions for success.
This session is focused on the art of moving forward in even the noisiest environments.
The age of hypermedia-driven APIs is finally upon us, and it’s unlocking a radical new future for AI agents. By combining the power of the Hydra linked-data vocabulary with semantic payloads, APIs can become fully self-describing and consumable by intelligent agents, paving the way for a new class of autonomous systems. In this session, we’ll explore how mature REST APIs (level 3) open up groundbreaking possibilities for agentic systems, where AI agents can perform complex tasks without human intervention.
You’ll learn how language models can understand and interact with hypermedia-driven APIs, and how linked data can power autonomous decision-making. We’ll also examine real-world use cases where AI agents use these advanced APIs to transform industries—from e-commerce to enterprise software. If you’re ready to explore the future of AI-driven systems and how hypermedia APIs are the key to unlocking it, this session will give you the knowledge and tools to get started.
REST APIs often fall into a cycle of constant refactoring and rewrites, leading to wasted time, technical debt, and endless rework. This is especially difficult when you don't control the API clients.
But what if this could be your last major API refactor? In this session, we’ll dive into strategies for designing and refactoring REST APIs with long-term sustainability in mind—ensuring that your next refactor sets you up for the future.
You’ll learn how to design APIs that can adapt to changing business requirements and scale effectively without requiring constant rewrites. We’ll explore principles like extensibility, versioning, and decoupling, all aimed at future-proofing your API while keeping backward compatibility intact. Along the way, we’ll examine real-world examples of incremental API refactoring, where breaking the cycle of endless rewrites is possible.
This session is perfect for API developers, architects, and tech leads who are ready to stop chasing their tails and want to invest in designing APIs that will stand the test of time—so they can focus on building great features instead of constantly rewriting code.
AI is accelerating software development at an unprecedented pace, but many teams are discovering a frustrating reality: faster coding isn’t translating into faster delivery.
The reason is counterintuitive. When you accelerate one part of a system, you don’t improve the system… you stress it. More code becomes more review, more coordination, more cognitive load, and ultimately, less flow.
This talk connects that modern failure mode to a foundational systems insight from The Goal: local optimization usually degrades overall performance. From there, Michael Carducci shows how to apply the Theory of Constraints to modern software delivery.
Using concrete examples, you’ll see how practices like XP, DevOps, Domain-Driven Design, and Team Topologies act as targeted interventions on specific bottlenecks—and how misapplying them can make things worse.
You’ll leave with a practical mental model for identifying constraints in your system, reasoning about trade-offs, and designing for flow in an AI-accelerated world.
Gartner just declared the semantic layer a non-negotiable foundation for AI. Most of the industry responded with a blank stare.
This presentation is the answer to that blank stare.
Your AI has a dirty secret: there is no mechanism in its architecture for truth. Only probability. Every response is a hallucination — most just happen to overlap with the facts. The philosophers figured out why 2,500 years ago, and they also gave us the solution. Plato defined knowledge as justified true belief. RAG is our architecture for justification. But there's a problem — your structured data is wholly inaccessible to it, because your JSON is full of magic strings that mean nothing outside the system that generated them.
This presentation shows you how to fix that. Not with a new framework, a bigger model, or an enterprise triple store. With a discipline — the discipline of making meaning explicit. JSON-LD, RDFS, OWL, and Schema.org form a standards stack that has been quietly solving this problem for 30 years. Your AI is already fluent in it. Half the web already speaks it. Google built an empire on it.
You'll leave with a concrete understanding of what the semantic layer actually is, why it matters, and — most importantly — how to start building it this week with the APIs you already have.
Your data isn't worthless. AI just doesn't know what it means yet.