PurePerformance

What does it take to truly observe an AI application? In this episode, we sit down with Giovanni Lima — Open Source Contributor to OpenTelemetry, OpenFeature, and Keptn, and Principal Software Engineer at Dynatrace working on AI Observability.

We explore how to instrument AI apps with frameworks like OpenInference, what distributed traces reveal about agent topology, model cost, performance, and accuracy, and why prompt engineering and observability go hand in hand.

We also look at emerging trends: internal agentic platforms for back-office automation, and how organizations self-hosting models use observability to optimize hardware, inference, and caching.

Links
Giovanni's LinkedIn: https://www.linkedin.com/in/giovanni-liva-101a1532/
OpenTelemetry: https://opentelemetry.io/
OTel AI Semantic Conventions: https://github.com/open-telemetry/semantic-conventions-genai
OpenInference: https://github.com/Arize-ai/openinference

In the second part of our conversation with Todd, Maintainer of OpenFeature, we learn about why implementing feature flagging is not as easy as at looks at first glance. As a framework developer you need to think about where feature flag evaluations are done. Ideally as close as possible to where your confidential data is you use for making a decision. But that comes with other challenges such as propagating your rule engine potentially to millions of mobile devices.
If you think you know all the edge cases then think again and tune in to this episode. Learn about how to not leak any confidential data, how to avoid propagating rules with PII data to millions of devices, and how to build a framework that can evaluate within flags within milliseconds regardless of where your end users execute your code to avoid any impact on end user experience.
Links
Todd’s LinkedIn: https://www.linkedin.com/in/toddbaert/
OpenFeature: https://openfeature.dev/
Introducing OpenFeature Podcast: https://www.spreaker.com/episode/introducing-openfeature-stepping-into-the-footsteps-of-opentelemetry-with-mike-beemer-and-todd-baert--50043067

Feature flagging is almost as old as software engineering – but only since the increased adoption of AIDLC (AI- Delivery Life Cycle) it has really taking off like AI has taken off as the default way to generate code!
In this episode we welcome back Todd Baert, Maintainer of OpenFeature, and learn about the many different use cases of Feature Flagging. Todd explains how feature flagging evolved from simple variables that pivot code execution towards dynamic evaluations that are supported by modern frameworks like OpenFeature and feature flag management systems that are based on that cloud native standard.
Tune in and learn what the biggest competitors of OpenFeature are, why feature flagging requires less thinking during development than you think and how it mitigates the risk of AI generated code having negative impact on your systems resiliency!
Links
Todd’s LinkedIn: https://www.linkedin.com/in/toddbaert/
OpenFeature: https://openfeature.dev/
Introducing OpenFeature Podcast: https://www.spreaker.com/episode/introducing-openfeature-stepping-into-the-footsteps-of-opentelemetry-with-mike-beemer-and-todd-baert--50043067

What happens when your AI coding tools outpace your delivery platform? Andi Grabner and Brian Wilson find out with Michael Binz, DevRel for Juno - the Internal Developer Platform (IDP) at Dynatrace. Together they walk through the full journey of building an IDP that keeps up with AI-speed engineering. Juno serves as a knowledge base, automation hub, and organizational memory across the entire software delivery lifecycle. If your platform can't scale with your AI ambitions, your 10x engineers are working on a 0.1x foundation. This episode shows you what to do about it.

Links we discussed:
Michaels LinkedIn: https://www.linkedin.com/in/michael-binz-a1307a111/
YouTube Video of their talk: https://www.youtube.com/watch?v=3Ow9rIdv-x8
Bluebox: https://www.bluebox.ai 
Max Headroom: https://www.youtube.com/watch?v=egCOO7Zzq0U

Three years ago, Roman Ferstl — entrepreneur, founder, and returning PurePerformance guest — found himself experiencing something he struggled to explain to anyone who hadn't lived it. In this episode, he joins Andi Grabner and Brian Wilson to talk openly about burnout, anxiety, and depression: how they overlap, how they build on each other, and what the science of sleep, the nervous system, and neuroplasticity reveals about why recovery is genuinely possible. Honest about therapy, medication, and mindfulness — what worked and what didn't — Roman's goal is simple: if even one person listening takes one sentence away that changes something for them, the conversation was worth having. You are not broken. And it can get better.