The tl;dr is that ๐ฉ๐ซ๐จ๐ฆ๐จ๐ญ๐ข๐จ๐ง and ๐ ๐ซ๐จ๐ฐ๐ญ๐ก are two different things. - straight to the point. Growth is
The tl;dr is that ๐ฉ๐ซ๐จ๐ฆ๐จ๐ญ๐ข๐จ๐ง and ๐ ๐ซ๐จ๐ฐ๐ญ๐ก are two different things." - straight to the point. Growth is something which is owned by individuals - you own your own career (aka growth) and must be supported by your manager/company.
What often is missing is recognition and incentive to grow within a level without the necessary target of a future promotion. This creates then a promotion culture in which individual and managers alike are incentivized to promotion as 1st class citizen. Growth should be 1st class citizen while promotion is a possible effect.
๐ฃ๐ฒ๐ฟ๐ณ๐ฒ๐ฐ๐ ๐๐ถ๐บ๐ถ๐ป๐ด ๐ณ๐ผ๐ฟ ๐ฎ๐ฌ๐ฎ๐ฒ ๐ฐ๐ฎ๐ฟ๐ฒ๐ฒ๐ฟ ๐ฝ๐น๐ฎ๐ป๐ป๐ถ๐ป๐ด! ๐ฏ
๐ฃ๐ฒ๐ฟ๐ณ๐ฒ๐ฐ๐ ๐๐ถ๐บ๐ถ๐ป๐ด ๐ณ๐ผ๐ฟ ๐ฎ๐ฌ๐ฎ๐ฒ ๐ฐ๐ฎ๐ฟ๐ฒ๐ฒ๐ฟ ๐ฝ๐น๐ฎ๐ป๐ป๐ถ๐ป๐ด! ๐ฏ
I just dived deep into the book “Solutions Architect Interview: Winning strategies and effective tactics for interview success” by Saurabh Shrivastava, ย Neelanjali Srivastav, Dhiraj Thakur and Sanjeet Sahay and as someone who has led 200+ Solutions Architect interviews, I can say this is a genuinely valuable resource.
๐ฏ ๐๐ผ๐ฟ๐ฒ ๐๐ผ๐ฐ๐๐: ๐ ๐ฎ๐๐๐ฒ๐ฟ๐ถ๐ป๐ด ๐๐ต๐ฒ ๐ฆ๐ ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐
This book is laser-focused on helping you ace Solutions Architect interviewsโbut it goes beyond typical interview prep by also explaining:
Dennis Kieselhorst is #hiring. Know anyone who might be interested?
Dennis Kieselhorst is #hiring. Know anyone who might be interested?
If you don’t know Dennis Kieselhorst, you should get to know him.
If you do know him, you already know one reason why this job is worth looking at.
Anyways, take a good look!
I find this very insightful.
I find this very insightful.
I remember my early days at my current company. Coming from roles with relative high degree of freedom but embedded in “ask for approval” culture, it was hard for me to understand that I can do most of the things just based on my own judgement. No approval needed.
Another tool we use at Amazon to assist in making high-quality, high velocity decisions is a mental model we call one-way and two-way doors. A one-way door decision is one that has significant and often irrevocable consequencesโbuilding a fulfillment or data center is an example of a decision that requires a lot of capital expenditure, planning, resources, and thus requires deep and careful analysis. A two-way door decision, on the other hand, is one that has limited and reversible consequences: A/B testing a feature on a site detail page or a mobile app is a basic but elegant example of a reversible decision.
๐ท ๐ข๐น๐ฑ๐ฒ๐ฟ == ๐๐ฒ๐๐๐ฒ๐ฟ?! ๐ข๐ฟ ๐ฑ๐ผ ๐๐ป๐ฑ๐ถ๐๐ถ๐ฑ๐๐ฎ๐น ๐๐ผ๐ป๐๐ฟ๐ถ๐ฏ๐๐๐ผ๐ฟ๐ ๐๐๐ฟ๐ป ๐ถ๐ป๐๐ผ ๐๐ถ๐ป๐ฒ๐ด๐ฎ๐ฟ?
๐ท ๐ข๐น๐ฑ๐ฒ๐ฟ == ๐๐ฒ๐๐๐ฒ๐ฟ?! ๐ข๐ฟ ๐ฑ๐ผ ๐๐ป๐ฑ๐ถ๐๐ถ๐ฑ๐๐ฎ๐น ๐๐ผ๐ป๐๐ฟ๐ถ๐ฏ๐๐๐ผ๐ฟ๐ ๐๐๐ฟ๐ป ๐ถ๐ป๐๐ผ ๐๐ถ๐ป๐ฒ๐ด๐ฎ๐ฟ?
๐ The sun is setting in Germany, and I’m commuting home. Perfect time to dive into Werner Vogels’ latest post “๐๐ฒ๐๐ฒ๐น๐ผ๐ฝ๐บ๐ฒ๐ป๐ ๐ด๐ฒ๐๐ ๐ฏ๐ฒ๐๐๐ฒ๐ฟ ๐๐ถ๐๐ต ๐๐ด๐ฒ” [1] on AllThingsDistributed.
๐ Pretty sure people around me noticed my smiling and nodding while reading. It resonates deeply. Highly recommend this read - refreshing and reassuring!
๐ค But here’s the controversial part: In reality, we don’t encounter infinities regularly. Everything tends to be finite. It’s like aging red wine…
๐ช ๐๐ ๐๐ผ๐๐ฟ ๐๐ฎ๐ ๐ฏ๐น๐๐ป๐? ๐๐ณ ๐ป๐ผ๐, ๐ต๐ผ๐ ๐ฑ๐ผ ๐๐ผ๐ ๐ธ๐ฒ๐ฒ๐ฝ ๐ถ๐ ๐๐ต๐ฎ๐ฟ๐ฝ?
๐ช ๐๐ ๐๐ผ๐๐ฟ ๐๐ฎ๐ ๐ฏ๐น๐๐ป๐? ๐๐ณ ๐ป๐ผ๐, ๐ต๐ผ๐ ๐ฑ๐ผ ๐๐ผ๐ ๐ธ๐ฒ๐ฒ๐ฝ ๐ถ๐ ๐๐ต๐ฎ๐ฟ๐ฝ?
The phrase “sharpening the saw” originates from a parable popularized by Stephen Covey in his 1989 book, The 7 Habits of Highly Effective People, where it represents the practice of self-renewal and personal improvement.
๐ Covey begins his chapter on this habit with a story of a man struggling to cut down a tree with a dull saw and refusing to stop and sharpen it because he’s “too busy sawing” โ illustrating the need to regularly invest in growth to remain effective.
๐ฅ CONTROVERSIAL TAKE: Data Scientists are becoming extinct. GenAI killed them.
๐ฅ CONTROVERSIAL TAKE: Data Scientists are becoming extinct. GenAI killed them.
Just 3 years ago, data scientists were the unicorns of tech. Companies fought over them, projects crawled at snail pace, and most ML models never saw production.
The reality was brutal:ย โข Custom models took months to buildย โข Jupyter notebooks couldn’t scale to productionย โข Engineering teams had to rebuild everything from scratch to hit production
Then GenAI changed everything.
Being in the industry for many years in different roles, this resonates deeply with me. Expert versu
Being in the industry for many years in different roles, this resonates deeply with me. Expert versus Generalist. Highly recommend to have a read of Constantin’s article and a deep dive on the blog post by Martin Fowler, @gitanjalivenkatram and Unmesh Joshi. Super valuable. What are your thoughts on this? Join the discussion in the comments of Constantin’s article!
Stefan, why are you still with AWS after already being there for so long - curre
Stefan, why are you still with AWS after already being there for so long - currently 8 years?
I get this question constantly, in countless variations. My honest answer is always the same: it’s the people around me who hold a high bar while continuously creating opportunities for me to grow and learn.
Last week provided another perfect example of this. During one of our account team meetings my colleague Cameron brought a lightning talk on the topic of high-performing teams, which is another indication of how we constantly strive to improve the way we work. The outstanding point in the talk was about psychological safety being the most important characteristic of a high-performance team. Psychological safety is fundamental to creating a workplace that fosters inclusion, learning, and innovation.
Yesterday I tookโafter a long break of 5 yearsโan AWS Certification: The AWS Cer
Yesterday I tookโafter a long break of 5 yearsโan AWS Certification: The AWS Certified AI Practitioner[4]. I wanted to take a moment to share my thoughts on the exam and help you determine if this would be a good learning objective for you. ย To be honest, all of us should be active AI practitioners given the current state of AIโthat’s a first indication of whether this could be something for you. That said, it’s not easy to stay on top of all the new AI tools that emerge literally every day. Obtaining and maintaining mastery seems to be a full-time job. That’s exactly where a curated and fixed learning scope provided by a certification exam can be helpful. ย What I particularly appreciate about the AWS AI Practitioner Exam scope is its focus on creating a foundation of AI concepts and understanding their applicability to certain classes of use cases. Acquiring this knowledge helps tremendously in understanding how to apply AI tools to our own work and how to identify and shape possible use cases for AI. ย Note that up to this point, this post hasn’t used the term “GenAI.” The certification scope is broader as it starts from the AI foundation but also covers many GenAI aspects. This approach helps you build a healthy foundation and design frugal and effective solutionsโnot every aspect of every use case needs GenAI. Not even in 2025 ๐ ย The certification is an AWS certification, so it doesn’t stop at foundational knowledge but also requires you to establish a foundational understanding of the AWS service offering to help you design and implement use cases. Many hidden gems well beyond “just” Amazon Bedrock are covered in the scope. That’s another refreshing and quite helpful aspect. If I’ve sparked your interest, have a look at the exam landing page [1] and exam guide [3], which contain valuable information about the exam. ย Most importantly, in my opinion, is the learning journeyโunless you’re just after a shiny cert. Plenty of training content can be found at AWS Skill Builder [2], which also includes sample exams to verify your learning progress.