PurePerformance

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!

In 2011 Heroku defined the 12 factor app to remove emerging bottlenecks as developers tried to scale their output when they moved from building monoliths to microservices. In Platform Engineer we see a repeating pattern called the "8 Factor Platform Producers".  AI allows engineering teams to speed up but they face bottlenecks as platform capabilities are not scaling with that demand as they are often depending on a central platform engineering team to be built and maintained.
To learn more about 8 Factor Platform Producers we invited Abby Bangser,  Founding Principal Engineer at Syntasso and CNCF Ambassador. She gave an amazing talk at KubeCon in Amsterdam and today walks us through the need of defining both consumers and producers for platforms to eliminate any emerging bottlenecks in Platform Engineering and allow an organization to reap the benefit of speeding up with AI

Links we discussed:
Abby's LinkedIn: https://www.linkedin.com/in/abbybangser/
Abby's Kubecon Keynote: https://www.youtube.com/watch?v=8t0-5cvvMGM&list=PLj6h78yzYM2MXCOWSN9CqqID6OOvF7wxL&index=30
12 Factor Apps: https://12factor.net/
CNCF Whitepaper: https://cloudnativeplatforms.com/whitepapers/platforms/

As the software world is transforming from cloud native to AI-native, observability must transform with it. But how exactly? How do we apply this in an existing enterprise with established processes and practices?
In this PurePerformance episode, Andi Grabner hosts Hilliary Lipsig and Rob Rati to discuss their new book, Observability in the AI‑Native Era. The conversation explores how AIOps, automation, and modern observability must evolve as systems become cloud‑native, data‑heavy, and AI‑driven.
We talk about why old alerting and SLO models no longer scale, how to balance AI with automation and human judgment, and why trust, security, and compliance matter more than ever when machines start making operational decisions. A must‑listen for SREs, platform engineers, and engineering leaders navigating the AI‑native future.
Links we discussed
Book on Amazon: https://www.amazon.com/Observability-AI-Native-Era-Artificial-Intelligence-ebook/dp/B0GHZH1YFL
Hilliary LinkedIn: https://www.linkedin.com/in/hilliary-lipsig-a5935245/
Rob LinkedIn: https://www.linkedin.com/in/roberthrati/
Andi LinkedIn: https://www.linkedin.com/in/grabnerandi/

AI coding agents are fast—but speed alone doesn’t guarantee quality. In this episode, Andi Grabner talks with Lukas Holzer (Straion) about why large context files and “almost right” AI code create new risks for engineering teams. You will learn about the "Lost in the Middle Syndrom" and why many organizations are not getting the promised 10x engineering boost right now!
Andi and Lukas also explore rule adherence, dynamic context generation, enterprise readiness for AI-first development, and how software engineering roles are evolving in the age of AI.
Tune in to learn more ...

Links we discussed
LinkedIn Profile: https://www.linkedin.com/in/lukas-holzer/
Straion Website: https://straion.com/
90 Percent Rule Blog: https://straion.com/blog/90-percent-rule-adherence-straion-coding-agents/
1million tokens Blog: https://straion.com/blog/1m-tokens-wont-save-your-engineering-standards/