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 discussedRainer'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/

Chaos Engineering is the practice to introduced controlled failures into a system with the goal to improve the overall resiliency! What started with "lets see what happens when we unplug that server" to "lets simulate network latency issues" or "lets kill critical pods and see if the system recovers gracefully" is now seeing new experiments being conducted that are identified by a new companion: AI In this episode we have invited Bartek Pisulak, Dir of Cloud Quality Engineering at Pegasystems, who has been educating quality engineers on AI-Augmented Chaos Testing in Practice. Tune in and learn about the how AI can improve efficiency in the 5 critical phases of a chaos experiment: Steady State, Hypothesis, Run Experiment, Verify, Improve!To learn more about the foundational principles make sure to watch some of the conference talks from Bartek listed below:Links discussedBartek's LinkedIn: https://www.linkedin.com/in/bart%C5%82omiej-pisulak-82b94036/Talk at Cloud Native Days Austria: https://www.youtube.com/watch?v=xUVCKNpMEz8&list=PLtLBTEzR4SqU9GwgWiaDt10-yOVIN0nzM&index=10Talk at Porto Tech Hub: https://www.youtube.com/watch?v=-ZuEaA2PoToKraken: https://github.com/krkn-chaos/krknChasoEater: https://github.com/ntt-dkiku/chaos-eater

Don't get stuck using AI to build faster horses. Instead, find the opportunities and rethink your software delivery processes! That, and only that, will help you increase Developer Experience and Efficiency!This episode is all about how to measure and improve DevEx in the age of Artificial Intelligence. And with Laura Tacho, CTO at DX, we think we found a perfect guest!Laura has been working in the dev tooling space for the past 15 years. In her current role at DX she is working on the evolution of DORA and SPACE into DX Core 4 and the DXI Measurement Framework.In our episode we learn about those frameworks but also how tech leaders need to rethink where and how to apply AI to improve overall efficiency, quality and effectiveness! The key takeaways from this conversation areDevEx is all about the identifying and reducing friction in the end-2-end development processTech Leaders need to become better in articulating technical change requirements to businessAs of today only 22% of code in git is really AI generated. Don't get fooled into believing AI is already betterBack to Basics makes companies successful with AI. That is: proper CI/CD, testing, documentation, observability!Here the links we discussedLaura's LinkedIn: https://www.linkedin.com/in/lauratacho/DX: https://getdx.com/Cloud Native Days Austria Talk: https://www.youtube.com/watch?v=kZ1F0-XS1l4Engineering Leadership Community: https://www.engineeringleaders.io/

While Artificial Intelligence seems to have just popped up when OpenAI brought ChatGPT to the consumer market it has its roots in the mids of the 20th century. But what is it that all of a sudden made it into every conversation we seem to have?Thomas Natschlaeger, Principal Data Scientist at Dynatrace, who has been working in the AI and Machine Learning space for the past 30 years gives us a brief historical overview and describes the critical evolutionary steps and compelling events in that technology that made it to what it is today. Tune in and hear about how AIs are trained, how they are optimized and most importantly: how their outputs can be tested and validated!In our conversation we discuss current trends towards small language models that will help model digital twins of our existing roles and how AIs are used to Validate other AIs like we humans do when a senior engineer does pair programming with a junior and with that provides essential feedback on current accuracy and input to improve the outcome of future tasks.Links we discussedLinkedIn Profile from Thomas: https://www.linkedin.com/in/thomas-natschlaeger/Ask Me Anything Session on Davis CoPilot: https://www.linkedin.com/posts/grabnerandi_llm-copilot-activity-7373837743971393536-QgxV?utm_source=share&utm_medium=member_desktop&rcm=ACoAAABLhVQBbh8Jkn_K8din5tsQlMCpXRNzlKUVoxxed Conference Talk: https://amsterdam.voxxeddays.com/talk/?id=39801Attention is all you need paper: https://en.wikipedia.org/wiki/Attention_Is_All_You_Need

Defining AI-Native in 2025 is like trying to define Cloud Native back in 2014! We are in the early stages of understanding what AI really means to us. The ecosystem is just evolving, and many organizations are still struggling with re-architecting their digital systems to cloud native patterns!To learn more about the current transformational wave—the AI-Native Wave—we have invited Pini Reznik, CEO and Co-Founder of re:cinq. We will discuss what we can learn from previous "waves of innovation," why the business must care, and why the primary AI use case should not be just cost-cutting! Make sure to get a copy of his book or catch his talk from Cloud Native Munich. All links we discussed here:Pini's LinkedIn: https://www.linkedin.com/in/pinireznik/The Next Transformation Mini Book: https://re-cinq.com/mini-bookCloud Native Munich Talk: https://www.youtube.com/watch?v=CHb3TLEV8ZU

Did you know that the average salary for a Platform Engineer is 42.5% more than a DevOps engineer? But why is that?We sat down with Artem Lajko, CNCF Kubestronaut and Ambassador as well as Author of the book Implementing GitOps with Kubernetes. We dive into the role of a platform engineer, the common pitfalls in implementing IDPs and why Backstage and AI won't solve all your problems. And we touch upon a topic hot off the press around Terraform: Its not dead!Links we discussedArtem's LinkedIn: https://www.linkedin.com/in/lajko/Talk slides from Cloud Land: https://lajko10-my.sharepoint.com/personal/artem_lajko_dev/_layouts/15/onedrive.aspx?id=%2Fpersonal%2Fartem%5Flajko%5Fdev%2FDocuments%2FAttachments%2Fcloud%20land%2D2025%5F%2Epdf&parent=%2Fpersonal%2Fartem%5Flajko%5Fdev%2FDocuments%2FAttachments&ga=1State of Platform Engineering Report: https://platformengineering.org/reports/state-of-platform-engineering-vol-3Upjet GitHub Project: https://github.com/crossplane/upjet

More than 50% of platform engineering leads don't know how to measure the impact of their platform! Many platform projects fall into common anti-pattern traps that make the platform look great on Day 1 but fail to scale and excite on Day 2!Daniel Bryant - who's profile tagline is "Helping you build better platforms" - is sharing his thoughts on how to measure the value of your platform, how to avoid common anti-patterns and why he believes that the future of platform engineering is in Platform Democracy!And of course, we wrap everything up with a discussion around the impact of Agentic AI towards platform engineering. So - tune in! Here the links we discussedDaniel's LinkedIn Profile: https://www.linkedin.com/in/danielbryantuk/Platform Engineering Book for Technical Product Leaders: https://www.amazon.de/Platform-Engineering-Technical-Product-Leaders/dp/1098153642/ref=asc_df_1098153642Platform Engineering Day Talk: https://www.syntasso.io/post/syntasso-at-platengday-london-presentation-recapKratix Website: https://www.kratix.io/Ai-Driven Platform Engineering Blog: https://www.syntasso.io/post/what-we-learned-building-a-prototype-ai-driven-dev-interface-for-kratixPlatform Democracy: https://www.syntasso.io/post/platform-democracy-rethinking-who-builds-and-consumes-your-internal-platformPlatform Anti Patterns: https://www.syntasso.io/post/platform-building-antipatterns-slow-low-and-just-for-showSlide Deck on Platform Engineering for Devs and Architects: https://speakerdeck.com/danielbryantuk/platform-engineering-for-software-developers-and-architects-redux