Tom Segura jokes about supermodels in his Netflix special, "Sledgehammer".
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תוכן מסופק על ידי Dean Bodart. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Dean Bodart או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
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According to Yahoo, AI Forces Software Testers to Shift Left into Extinction
Manage episode 484231745 series 3645872
תוכן מסופק על ידי Dean Bodart. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Dean Bodart או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
The world of software development is rapidly changing, driven by "Shift Left" methodologies and the powerful influence of Artificial Intelligence. Are traditional software testers becoming obsolete? In this episode, we explore the provocative idea that the core job of a software tester is indeed on a path to extinction, as developers and analysts, empowered by AI, increasingly take on testing responsibilities.
Join us as we unpack:
- The "Shift Left" imperative: how moving testing earlier in the SDLC has reshaped team dynamics and why companies like Yahoo and Microsoft began moving away from traditional QA teams years ago.
- AI as the ultimate accelerant: how generative AI is revolutionizing test case generation, enabling self-healing tests, and driving predictive defect detection, leading to unprecedented efficiency.
- Real-world examples: discover how platforms like Functionize, SQAI Suite, and Momentic.ai are enabling organizations to operate with minimal or no dedicated QA teams, shifting quality ownership across the board.
- The evolution, not extinction, of the tester: learn about the rise of the Software Development Engineer in Test (SDET) and the new, highly technical profile of modern QA professionals.
- The indispensable human element: despite AI's advancements, we discuss its inherent limitations, particularly with subtle edge cases, creativity, and human judgment, underscoring why human expertise remains crucial.
Tune in to understand the profound transformation of the software quality landscape and what it means for the future of testing careers.
Check out the content on LinkedIn 👉
Connect with Dean on LinkedIn 👉
17 פרקים
שתפוManage episode 484231745 series 3645872
תוכן מסופק על ידי Dean Bodart. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Dean Bodart או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
The world of software development is rapidly changing, driven by "Shift Left" methodologies and the powerful influence of Artificial Intelligence. Are traditional software testers becoming obsolete? In this episode, we explore the provocative idea that the core job of a software tester is indeed on a path to extinction, as developers and analysts, empowered by AI, increasingly take on testing responsibilities.
Join us as we unpack:
- The "Shift Left" imperative: how moving testing earlier in the SDLC has reshaped team dynamics and why companies like Yahoo and Microsoft began moving away from traditional QA teams years ago.
- AI as the ultimate accelerant: how generative AI is revolutionizing test case generation, enabling self-healing tests, and driving predictive defect detection, leading to unprecedented efficiency.
- Real-world examples: discover how platforms like Functionize, SQAI Suite, and Momentic.ai are enabling organizations to operate with minimal or no dedicated QA teams, shifting quality ownership across the board.
- The evolution, not extinction, of the tester: learn about the rise of the Software Development Engineer in Test (SDET) and the new, highly technical profile of modern QA professionals.
- The indispensable human element: despite AI's advancements, we discuss its inherent limitations, particularly with subtle edge cases, creativity, and human judgment, underscoring why human expertise remains crucial.
Tune in to understand the profound transformation of the software quality landscape and what it means for the future of testing careers.
Check out the content on LinkedIn 👉
Connect with Dean on LinkedIn 👉
17 פרקים
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1 What Amazon Knows About MCP That You Don’t: 3 Game-Changing AI Techniques for DevOps 40:22
40:22 
הפעל מאוחר יותר 
הפעל מאוחר יותר 
רשימות 
לייק 
אהבתי40:22
הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתיHave you ever encountered the acronym "MCP" in the context of AI for DevOps and felt a little lost? You're not alone! While seemingly ambiguous, MCP actually refers to three distinct, yet equally critical, techniques that are revolutionizing how we develop, test, and deploy software with AI. In this episode, we'll demystify MCP, breaking down its three powerful interpretations: Model Compression and Pruning (MCP): The Efficiency Imperative. Discover how optimizing AI models, particularly large language models (LLMs), for size and computational demand is making AI in DevOps economically viable and operationally agile. We'll explore real-world examples from Amazon Web Services (AWS) and Red Hat, showcasing how MCP leads to significant cost savings and performance boosts. Model Context Protocol (MCP): The Interoperability Standard. Learn how this standardized framework empowers AI models to seamlessly and securely interact with external tools, data sources, and APIs. We'll look at how companies like Twilio and Block are using MCP to transform AI from a passive assistant into an active participant in complex DevOps workflows. Model Context Performance (MCP): The Intelligence Multiplier. Understand how effectively an AI model processes and acts upon contextual information directly impacts its accuracy and relevance. We'll share insights from Microsoft DeepSpeed and IBM Granite, demonstrating how strong Model Context Performance leads to smarter AI-assisted coding, faster regression analysis, and more reliable test generation. Join us as we uncover what pioneers like Amazon deeply understand about these three pillars of AI in DevOps. By grasping all facets of MCP, engineering teams can unlock unprecedented levels of efficiency, cost-effectiveness, and automation, moving beyond basic AI integrations towards truly intelligent and autonomous software development. If you're an engineering leader, DevOps practitioner, or AI enthusiast, this episode is a must-listen to understand the future of intelligent, context-aware, and resource-optimized automation. Check out the content on LinkedIn 👉 Connect with Dean on LinkedIn 👉…
1 Your SDLC is Dead, How Outbrain & UiPath are Building Flawless Software, Faster with Agentic AI 21:21
21:21 הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתי21:21
הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתיWe dive deep into the world of Agentic AI and its radical impact on software development. We uncover how leading companies like Outbrain and UiPath are already leveraging autonomous AI systems to build flawless software, faster , fundamentally transforming their QA and CI/CD pipelines. Forget old-school automation. This episode explores the shift to proactive, goal-driven AI that can generate tests, self-heal scripts, and even detect complex defects before they become costly problems. Discover tangible results, from drastically reduced test authoring times to accelerated release cycles. If you're in software development, engineering, or QA, and you want to understand how Agentic AI is redefining quality and efficiency, this is a must-listen. Check out the content on LinkedIn 👉 Connect with Dean on LinkedIn 👉…
1 According to Yahoo, AI Forces Software Testers to Shift Left into Extinction 18:09
18:09 הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתי18:09
הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתיThe world of software development is rapidly changing, driven by "Shift Left" methodologies and the powerful influence of Artificial Intelligence. Are traditional software testers becoming obsolete? In this episode, we explore the provocative idea that the core job of a software tester is indeed on a path to extinction, as developers and analysts, empowered by AI, increasingly take on testing responsibilities. Join us as we unpack: The "Shift Left" imperative: how moving testing earlier in the SDLC has reshaped team dynamics and why companies like Yahoo and Microsoft began moving away from traditional QA teams years ago. AI as the ultimate accelerant: how generative AI is revolutionizing test case generation, enabling self-healing tests, and driving predictive defect detection, leading to unprecedented efficiency. Real-world examples: discover how platforms like Functionize , SQAI Suite , and Momentic.ai are enabling organizations to operate with minimal or no dedicated QA teams, shifting quality ownership across the board. The evolution, not extinction, of the tester: learn about the rise of the Software Development Engineer in Test (SDET) and the new, highly technical profile of modern QA professionals. The indispensable human element: despite AI's advancements, we discuss its inherent limitations, particularly with subtle edge cases, creativity, and human judgment, underscoring why human expertise remains crucial. Tune in to understand the profound transformation of the software quality landscape and what it means for the future of testing careers. Check out the content on LinkedIn 👉 Connect with Dean on LinkedIn 👉…
1 Meta Proves the Testing Pyramid Is Dead with Sapienz AI 21:18
21:18 הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתי21:18
הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתיIn this episode, we examine how Meta's autonomous testing agent, Sapienz, is redefining software testing strategy and rendering the classic Testing Pyramid increasingly irrelevant. Once a foundational model in agile and DevOps environments, the pyramid prioritized a heavy reliance on unit tests with fewer integration and end-to-end tests. That hierarchy no longer reflects the capabilities or constraints of modern AI-powered testing. We explore the academic rationale behind the original model and analyze how tools like Sapienz, SQAI Suite, Applitools, Mabl, Functionize, and WireMock are shifting testing priorities. These platforms use intelligent test generation, self-healing automation, visual regression analysis, and knowledge graphs to reshape the economics and logic of quality assurance. We also discuss the trade-offs of moving away from unit test-centric strategies, and how organizations can build scalable, resilient, and AI-augmented test architectures that adapt to change and complexity. This episode is for QA professionals, test architects, engineering leads, and anyone involved in modern software delivery who wants to understand the future of testing beyond the pyramid. Check out the content on LinkedIn 👉 Connect with Dean on LinkedIn 👉…
1 Goldman Sachs Boosts Test Coverage by 40% Using RAG AI. Is Your QA Next? 19:44
19:44 הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתי19:44
הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתיIn this episode, we dive deep into how cutting-edge AI techniques — Self-RAG (Self-Reflective Retrieval-Augmented Generation) and Agentic RAG — are fundamentally transforming the software testing landscape. From increasing test coverage by 40% at Goldman Sachs to enabling autonomous exploratory agents that simulate users in real-time, AI is no longer a futuristic idea in QA — it’s here and it's powerful. Join us as we explore: What RAG, Self-RAG, and Agentic RAG really are How they reduce testing time, cost, and maintenance effort Real-world results from companies like Goldman Sachs, Swisscom, and Vodafone Where AI-driven QA is heading next Why your current testing strategy might already be obsolete Whether you're a QA professional, test manager, or curious technologist, this episode delivers essential insights into the tools and strategies defining the future of quality engineering. 🎧 Tune in to find out if your testing strategy is ready for what’s next. Check out the content on LinkedIn 👉 Connect with Dean on LinkedIn 👉…
1 AI-powered Software Testing: Lessons from Siemens & Shopify 26:57
26:57 הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתי26:57
הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתיIn this episode, we explore how artificial intelligence is fundamentally reshaping the software testing landscape. We start with Shopify’s 2025 directive requiring teams to prove that AI cannot handle a task before hiring a new employee. We then examine how Siemens Digital Industries Software is embedding AI into its Tessent testing tools, using analytical, predictive, and generative AI to optimize chip and software testing. Topics covered include the current pace of AI adoption in testing, practical examples of AI-powered quality engineering, and the skills QA professionals will need in the coming years. Whether you are a software engineer, QA lead, or tech executive, this episode offers actionable insights into the future of AI-augmented software testing. Check out the content on LinkedIn 👉 Connect with Dean on LinkedIn 👉…
1 Will AI Kill or Create Jobs in Software Testing? 18:03
18:03 הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתי18:03
הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתיAI is changing everything, including the world of software testing. In this episode, we break down the real impact of AI on testing careers: Will it eliminate jobs or create better ones? We explore global trends, short- and long-term forecasts, emerging QA roles, essential new skills, and expert insights from WEF, Gartner, McKinsey, and more. Whether you're a manual tester, SDET, or team lead, this one's for you. 🔍 Learn how to future-proof your testing career and thrive in the age of AI. Check out the content on LinkedIn 👉 Connect with Dean on LinkedIn 👉…
1 Digital Twins in Software Testing and the Elusive Replica of Human Expertise 24:36
24:36 הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתי24:36
הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתיIn this episode, we dive deep into one of the most provocative questions in the world of digital transformation: can AI-powered digital twins ever replicate the mind of a human software tester? Digital twins have transformed industries like aerospace, manufacturing, and healthcare. Now, the software world is asking whether we can virtualize not only the systems under test but the testers themselves. But behind the hype lies a set of cognitive, ethical, and technical challenges that most conversations avoid. From the promise of predictive QA environments to the failures of autonomous testing agents, this episode explores: What digital twins are and how they’re being applied in software testing Why replicating human intuition, doubt, and risk awareness is so difficult Lessons from other industries that have implemented digital twin technology The cognitive blind spots AI still can’t see Real-world data points, ethical dilemmas, and a grounded vision for the future If you work in quality assurance, AI, software development, or digital strategy, this episode will challenge your assumptions and offer a fresh lens on where digital twins truly fit in—and where they do not. Check out the content on LinkedIn 👉 Connect with Dean on LinkedIn 👉…
1 The Silent Collapse of SaaS: How AI Agents Are Rewriting the Software Playbook 32:41
32:41 הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתי32:41
הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתיIn this episode of Dean Does QA , I walk through the research and analysis behind my latest article on the dismantling of the SaaS model. From AI copilots to fully autonomous operators, I break down the three phases of this transformation, how traditional SaaS metrics are becoming misleading, and why the next generation of software may not look like software at all. We explore: How AI agents are bypassing user interfaces Why workflows and expertise are being unbundled from software The implications for pricing, APIs, and product design Startup opportunities in vertical AI and agent orchestration How SaaS incumbents can pivot before the ground disappears beneath them Whether you are a founder, product leader, investor, or tester, this is not a trend to watch. It is a paradigm to respond to. Check out the content on LinkedIn 👉 Connect with Dean on LinkedIn 👉…
1 Generative AI’s Growing Pains in Historical Perspective 19:31
19:31 הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתי19:31
הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתיAre generative AI’s skeptics right to question its cost, energy use, and unclear business model? In this episode, we dig into the historical parallels between today’s AI challenges and the rocky beginnings of railroads, electricity, and the internet. We examine how previous breakthrough technologies also faced hype, bubbles, and early doubts before reshaping entire industries. If you are curious whether generative AI’s current setbacks are a sign of failure or a natural phase in a larger transformation, this discussion is for you. Check out the content on LinkedIn 👉 Connect with Dean on LinkedIn 👉…
1 AI Advancements Revolutionizing Software Testing: GPT-4.5 and Multi-LLM 26:24
26:24 הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתי26:24
הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתיIs GPT-4.5 poised to revolutionize your testing pipeline? Join us in this episode as we delve into the latest multi-LLM advancements boosting QA automation, code analysis, and defect detection. We break down the real-world performance gains, highlight how tools like GPT-4.5 integrate with open-source models, and explore the competitive landscape reshaping software quality. If you’re curious about AI-driven testing—and the cutting-edge multi-LLM platforms propelling it—this is a conversation you won’t want to miss. Check out the content on LinkedIn 👉 Connect with Dean on LinkedIn 👉…
1 AI-Driven Software Testing, What Companies Get Wrong! 24:20
24:20 הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתי24:20
הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתיWhy do so many ambitious AI-driven testing initiatives fail to deliver real ROI? In this episode, we explore the seven most common pitfalls—from over-reliance on a single AI model to ignoring the importance of data quality and manual oversight. Learn how to integrate AI seamlessly into your CI/CD pipeline, reduce false positives, and focus your QA team where it counts. If you’re looking to streamline your testing process and adopt AI the right way, this episode is for you. Check out the content on LinkedIn 👉 Connect with Dean on LinkedIn 👉…
1 Could Grok 3 Be the Future of AI-Driven Software Testing? 24:22
24:22 הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתי24:22
הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתיJoin us on Dean Does QA as I explore Elon Musk’s newly released Grok 3 and its potential to rival established LLM heavyweights like GPT-4o and Gemini. We’ll talk about Multi-LLM RAG (and what it means for QA), Grok 3’s real-time capabilities, and whether 10x compute power truly translates to better testing performance. Tune in for a candid look at the strengths, pitfalls, and untapped potential of this next-gen AI model. Check out the content on LinkedIn 👉 Connect with Dean on LinkedIn 👉…
1 Enterprise-Ready or AI-First? The Two Paths of QA Evolution 22:00
22:00 הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתי22:00
הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתיCurious whether you should prioritize airtight compliance or cutting-edge AI in your testing strategy? In this episode, we dissect the pros and cons of both approaches—exploring how enterprise-grade security stacks up against rapid, AI-driven innovation. Whether you’re a seasoned QA leader or just diving into AI-powered testing, this conversation will help you chart the right path forward. Check out the content on LinkedIn 👉 Connect with Dean on LinkedIn 👉…
1 The AI Maturity Gap in Software Testing: Who’s Leading? 18:02
18:02 הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתי18:02
הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתיIn this episode of Dean Does QA , our AI hosts Dwane and Rachel tackle the question that’s on everyone’s mind: Who’s actually winning the race in AI-powered software testing? Building on our previous discussion about why AI is the future of QA, we examine the growing “AI maturity gap” among testing platforms. Discover the standout leaders dominating the market, the innovative newcomers aiming for the top, and the reasons some legacy players are falling behind. We’ll discuss game-changing features like self-healing test automation, AI-driven test generation, and predictive analytics—plus the hurdles preventing widespread AI adoption. If you’re interested in staying competitive in the rapidly evolving QA landscape, tune in to find out which platforms are shaping the future and how you can stay ahead of the curve! Check out the content on LinkedIn 👉 Connect with Dean on LinkedIn 👉…
D
Dean does QA
1 The Impact of the EU’s €200B AI Investment on Software Testing 18:01
18:01 הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתי18:01
הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתיIn this special episode of Dean Does QA , we unpack the European Union’s groundbreaking €200 billion investment in AI and what it means for the future of software testing. Join our AI hosts Dwane and Rachel as they examine how new funding, emerging European AI models, and high-performance computing resources could help EU-based QA platforms compete with global heavyweights like Functionize and Testim. You’ll also hear insights on how Europe’s ethics-focused regulations could shape the evolution of AI-driven testing—creating both opportunities and hurdles for startups and enterprises alike. If you’re curious about how this massive investment might spark a new era of responsible AI innovation in QA, you won’t want to miss this episode! Check out the content on LinkedIn 👉 Connect with Dean on LinkedIn 👉…
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Dean does QA
1 Why AI in Software Testing is the Future 17:17
17:17 הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתי17:17
הפעל מאוחר יותר הפעל מאוחר יותר רשימות לייק אהבתיIn this very first episode of Dean Does QA , our AI-hosts Dwane and Rachel represent Dean to explore why AI is quickly becoming the new standard in software testing. As release cycles speed up and applications grow more complex, traditional methods can no longer keep pace. Discover how AI-driven testing addresses common QA challenges—like time-consuming manual checks, fragile automation scripts, and limited coverage—by introducing intelligence, self-healing capabilities, and predictive insights. We’ll discuss the real-world benefits of embracing AI in your QA processes, from self-healing test automation to proactive defect prevention. Whether you’re a seasoned QA engineer, a test automation pro, or simply curious about the future of software quality, this episode offers a practical look at how AI is poised to transform the entire testing landscape. Tune in and learn how to stay ahead in the ever-evolving world of software development! Check out the content on LinkedIn 👉 Connect with Dean on LinkedIn 👉…
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