PurePerformance

AI coding tools are everywhere, but how do you prove they're actually making engineers more productive?
In this episode of PurePerformance, hosts Brian Wilson and Andi Grabner welcome Michael Reichenbach, Platform Engineer at 1KOMMA5°, to discuss the company's journey toward more than 80% AI-written code. Rather than relying on anecdotes or hype, Michael shares how his team designed a real experiment to measure the impact of AI-assisted development.
We explore the metrics they chose, why traditional DORA metrics such as deployment frequency and change failure rate were not the right indicators, and how they instead focused on "Time to Code" from ticket creation and first commit to merged pull request. Michael also explains how AI lowered the barrier for contribution across the organization, enabling even non-engineering teams to prototype and build solutions faster.
The conversation also dives into the operational side of AI adoption, including AI observability dashboards, budget controls, Slack alerts, usage monitoring, and the surprising decision to intentionally limit AI spending during their proof of concept.
Whether you're evaluating Cursor, GitHub Copilot, or other AI coding tools, this episode offers practical lessons on measuring value, maintaining quality, and scaling AI adoption responsibly.

Links we discussed
Michael's LinkedIn: https://www.linkedin.com/in/michael-reichenbach/
Klaus's LinkedIn: https://www.linkedin.com/in/langenheldt/
Talk at Cloud Native Munich: https://www.youtube.com/watch?v=Ntf0h0vFuMQ
1Komm5 Website: https://1komma5.com/
Kenote from KubeCon: https://youtu.be/P1phxZHJGrA?t=570&is=9DYnbK8VGorMmaXo
Michael's YouTube Playlist: https://youtube.com/playlist?list=PLn-u2xOcMlXlVweZ0aB4pu6VM6Xv6895i&si=MZ6jzF-VwIAY3HFF

"There is no single way to deploy OpenTelemetry at scale—and that’s exactly the challenge."
As organizations adopt OTel across teams and environments, they face tough questions around standardization, configuration, and operating resilient observability pipelines.
To address these challenges, the OpenTelemetry community has introduced Blueprints and Reference Implementations—practical guidance on topics like data standards, consistent agent and collector configuration, pipeline resilience, and intelligent sampling.
In this episode, we’re joined by Dan Gomez Blanco, maintainer of the OpenTelemetry End-User SIG, to explore real-world reference architectures from organizations like Skyscanner, Adobe, and Mastodon.
Tune in to learn how the community is turning OTel complexity into shared best practices—and how you can contribute your own blueprint

I still hear people say, “OpenTelemetry is vendor-neutral, so you can switch any time!”
In this episode, Adriana Villela and Josh Lee (both active OpenTelemetry contributors) help bust that myth.
While OTel standardizes instrumentation and signal transport—and unlocks a rich ecosystem of tools—switching vendors isn’t as simple as it sounds. There’s real cost in retraining engineers, migrating dashboards, SLOs, and alerts, and reworking deep integrations across your delivery pipeline.
We also dive into a key challenge the community is tackling: helping engineers instrument by value, not by default—making it easier to capture the right signals with high quality instead of just collecting everything.

Here the links we discussed:
Adriana's LinkedIn: https://www.linkedin.com/in/adrianavillela/
Josh's LinkedIn: https://www.linkedin.com/in/joshuamlee/
The blog article: https://thenewstack.io/opentelemetry-vendor-neutrality-guide/
CND Austria Talk: https://www.youtube.com/watch?v=1gxLseuaTdM
KCD Prague Talk: https://www.youtube.com/watch?v=pPXG20CXKxQ
OpenTelemetry Project Website: https://opentelemetry.io/

In this episode, we explore how AI is transforming education, from classrooms to corporate training. What changes are needed in schools and universities? How does AI affect both students and educators? And how should companies rethink internal training and hiring to stay competitive?
To answer these questions, we’re joined by Rainer Stropek, CEO of Software Architects and Chairman of Coding Club Linz. With decades of experience teaching at high schools and universities—and helping organizations upskill their engineers—Rainer brings a unique perspective on how software engineering education is evolving.
While many view AI as a threat, Rainer sees it as a “Christmas gift”—opening up endless opportunities to learn, adapt, and innovate.
Tune in to hear why curiosity is more important than ever, how educational institutions can prepare future engineers, and why organizations must step up to ensure everyone has a fair chance to succeed in the age of AI.

Links we discussed
Rainer's LinkedIn Profile: https://www.linkedin.com/in/rainerstropek/
Rainer's Website: https://rainerstropek.me/
CodeClub: https://codeclub.org/en/
Coder DoJo Linz: https://linz.coderdojo.net/

Its rare - but it happens: A guest-free episode of PurePerformance, allowing Andi Grabner and Brian Wilson reconnect to share real-world insights from recent months in the cloud-native and observability space. From KubeCon Amsterdam experiences and the strength of open-source collaboration to emerging challenges like AI-generated contributions, they explore how the industry is evolving beyond the hype.
Your co-hosts of PurePerformance discuss the changing role of observability in the AI-native era—both as a foundation for understanding complex systems and as a tool to monitor AI itself. Brian shares his personal shift from AI skepticism to practical adoption, highlighting how AI can significantly improve productivity when used thoughtfully.
Hope you all enjoy this episode!