Uploaded April 2026 | Updated September 2026, 2 weeks ago
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As more AI systems move into production, ensuring models are responsible, ethical, and sustainable becomes critical. This talk explores how observability can help teams build AI systems they can actually trust.
For the last few years, I’ve been driven by the question: what responsibility do we have for the software we put into the world? That question originally led me to focus on reducing the environmental impact of software. Now, as teams deploy inference-heavy LLM workloads into production, it’s become even more pressing.
Using LLMs at scale raises serious questions around energy usage, cost, and ethics. A Gartner report predicts that 40% of agentic AI projects will be canceled by the end of 2027 due to escalating costs and unclear business value. How much of that comes down to a lack of visibility into how these systems behave once they’re live?
So how do you build trust in AI systems? How do you detect drift toward bias or toxicity? How do you understand the real resource cost and carbon footprint of inference at scale? And once you do have visibility, how do you turn it into meaningful guardrails?
In this talk, we’ll look at
Why traditional monitoring falls short for AI,
Which signals actually matter for responsible systems,
How to instrument AI workloads with OpenTelemetry,
How to use telemetry data to implement guardrails that improve trust, sustainability, and reliability in production AI.
Please subscribe to our YouTube channel @ youtube.com/@DevoxxForever
Subscribe to LinkedIn @ linkedin.com/company/voxxed-days-amsterdam
Follow us on Twitter @ twitter.com/voxxedamsterdam
As more AI systems move into production, ensuring models are responsible, ethical, and sustainable becomes critical. This talk explores how observability can help teams build AI systems they can actually trust.
For the last few years, I’ve been driven by the question: what responsibility do we have for the software we put into the world? That question originally led me to focus on reducing the environmental impact of software. Now, as teams deploy inference-heavy LLM workloads into production, it’s become even more pressing.
Using LLMs at scale raises serious questions around energy usage, cost, and ethics. A Gartner report predicts that 40% of agentic AI projects will be canceled by the end of 2027 due to escalating costs and unclear business value. How much of that comes down to a lack of visibility into how these systems behave once they’re live?
So how do you build trust in AI systems? How do you detect drift toward bias or toxicity? How do you understand the real resource cost and carbon footprint of inference at scale? And once you do have visibility, how do you turn it into meaningful guardrails?
In this talk, we’ll look at
Why traditional monitoring falls short for AI,
Which signals actually matter for responsible systems,
How to instrument AI workloads with OpenTelemetry,
How to use telemetry data to implement guardrails that improve trust, sustainability, and reliability in production AI.
![[VDBUH2026] Andrei Mihai & Bianca Bulbuc - How Agentic AI Empowers Creative Thinking](https://i.ytimg.com/vi/Tl1uqW8RSAo/mqdefault.jpg "[VDBUH2026] Andrei Mihai & Bianca Bulbuc - How Agentic AI Empowers Creative Thinking
As AI systems evolve from reactive tools into autonomous agents, UX Design must adapt to a new paradigm, one where interfaces don’t just respond, but reason, plan, and act.
In this talk, we’ll explore how Agentic AI is reshaping the future of UX, transforming AI from an assistant into a creative and operational partner. Designers will no longer design only screens and flows, but intent, delegation, and collaboration between humans and agents.
We’ll look at how agent-driven interactions change:
how users express goals instead of commands
how interfaces shift from control surfaces to orchestration layers
how designers move from execution to creative direction
The session will also introduce the role of Model Context Protocol (MCP) in enabling agent-based systems to understand context, connect tools, and act consistently across experiences, bridging design intent and autonomous execution.
This is a talk for designers, developers, and product leaders who want to understand what it means to design with agents, for humans.")
![[VDBUH2026] George Patrașcu - Ports, Adapters, and Other Ways to Stop Breaking Your Business Logic](https://i.ytimg.com/vi/UIlFFBZKSaA/mqdefault.jpg "[VDBUH2026] George Patrașcu - Ports, Adapters, and Other Ways to Stop Breaking Your Business Logic
Your business logic shouldn’t care whether it’s talking to a SQL database, a Kafka topic, or a REST API — but in most codebases, it does. In a microservice architecture, this coupling becomes especially painful: as services evolve and API versions change, you end up touching business logic just to keep up with infrastructure churn.
In this talk, we’ll explore Hexagonal Architecture (Ports & Adapters) as a practical answer to this problem.
We’ll start with the “why”: not to dismiss traditional layered architectures — they solve real problems, and it’s the model we use across many of our own services — but to examine the specific caveats that emerge as systems grow.
Where does coupling infrastructure concerns to business logic start to hurt? Hexagonal Architecture doesn’t throw layering out the window; it refines it, offering targeted solutions to those exact pain points. From there, we’ll walk through the core concepts of the pattern — ports, adapters, and the application core.
But this won’t be a textbook walkthrough. Everything you’ll see is grounded in real production experience. We’ll share the challenges we ran into, the mistakes we made, and the tradeoffs we had to navigate — including the pragmatic vs. dogmatic decisions that come up constantly in practice (should your ORM bleed into your domain model? It depends).
You’ll leave with:
– A clear mental model of Hexagonal Architecture and when it’s worth reaching for
– Concrete code examples of ports and adapters in action, written in C#
– Different approaches to structuring your project (and when to choose each)
– An honest look at the tradeoffs — including when not to use this pattern
Whether you’re building a new service or wrestling with an existing one, this talk will give you practical tools to make your business logic more resilient, testable, and independent of the infrastructure around it.")
