Join tech industry veterans Scott Hanselman and Mark Russinovich as they dive into the challenges and innovations of today’s fast-paced world. Whether you’re an experienced developer or simply curious about technology, each episode offers a fresh perspective on emerging trends, familiar topics, and insights that go beyond the strictly technical. From the latest in AI to effective ways to influence without authority, Scott and Mark set out to 'learn' something new in every episode, and they’re bringing you along for the ride. Join Scott and Mark for engaging discussions, expert advice, and a shared journey of learning and discovery. There's always something new to learn!
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In this episode, Scott Hanselman and Mark Russinovich dive into a growing issue in AI-driven research: hallucinated references in academic papers. After scanning thousands of conference submissions, Mark uncovers widespread citation inaccuracies, sparking a broader conversation about accountability, cognitive surrender, and the risks of over-relying on AI tools. They explore where AI adds value versus where it erodes critical thinking, from academic writing to everyday coding and content creatio...
This episode delves into the nature of "taste" in product design, distinguishing between subjective preference and objective usability derived from deep experience. Scott and Mark argue that strong product instincts come from sustained exposure and a holistic system view, not innate talent, and highlight the critical role of human judgment and specificity, especially when working with AI-assisted coding and navigating the evolving landscape of education.
In this episode, Scott Hanselman and Mark Russinovich dive into the evolution of ZoomIt, exploring new features like panoramic screen capture, webcam overlays, and lightweight video editing tools. They discuss the technical challenges behind building these capabilities, especially stitching images across any application and how AI-assisted coding is accelerating development while introducing new edge cases. Along the way, the conversation blends deep technical insight with candid, behind-the-s...
In this episode, Scott Hanselman and Mark Russinovich explore how software development is evolving in the age of AI, challenging the idea that everything should start with a fully defined spec. They highlight a more iterative, sculpting approach to building, where continuous refinement, testing, and human judgment are essential and discuss the realities of AI-assisted coding, including edge cases, maintenance, and the limits of productivity gains. Takeaways: AI-assisted coding works best as an...
In this episode, Scott Hanselman and Mark Russinovich unpack how AI systems actually behave beneath the surface, pushing past hype into the messy reality of how models are trained, aligned, and deployed. They explore whether AI systems are inherently benevolent or simply shaped by incentives, training data, and reinforcement learning, and why behaviors like deception can emerge under certain conditions. The conversation moves from philosophical questions about human nature versus machine behav...
Scott Hanselman and Mark Russinovich delve into Mark's experience implementing a shared-memory transport for gRPC across Go and .NET using AI models. They explore the significant productivity gains that reduce months of work to days, alongside the frequent frustrations of AI agents hallucinating, misinterpreting instructions, and requiring intensive human guidance. The episode also touches on solving other hard engineering problems, like a panorama screenshot stitcher, and discusses the future of developer tooling.
Scott Hanselman and Mark Russinovich delve into their ACM paper, addressing the critical challenge of fostering new engineering talent. They explore the concept of preceptorship programs within companies for early-career developers, lamenting the industry's reluctance to invest in junior hires due to poaching risks. The discussion highlights how universities could be crucial in creating a scalable pipeline, bridging the gap between academic learning and real-world experience, and proposing models to incentivize both companies and students.
This episode dives into the debate about whether traditional apps are being replaced by AI agents and chat interfaces. Scott Hanselman and Mark Russinovich argue that while text-based UIs are resurging and dynamic interfaces blur boundaries, reliable, secure, and repeatable workflows still demand well-built applications. They emphasize that AI is best suited for reasoning and ambiguity, not as a substitute for fixing poor UX or replacing robust SaaS platforms.
This episode explores the transformative impact of AI-assisted "vibe coding" on building and refining complex software. Scott Hanselman and Mark Russinovich discuss real-world experiments, from tackling challenging GRPC shared memory issues to rapidly developing new Win32 UI features for ZoomIt. They honestly examine where AI significantly boosts productivity, where it still falls short, and how multimodal feedback (screenshots, debug output) is essential for effective AI collaboration, emphasizing the evolving role of human judgment.
In this episode, Scott Hanselman and Mark Russinovich pull back the curtain on what really goes into a large-scale conference talk, using their recent Ignite session as a case study. They reflect on the balance between educational and soft talks, the importance of credibility and audience expectations, and why not every talk needs a rigid takeaway to be valuable. The conversation traces a playful but technically deep journey through computing history, from early machine code and Altair systems t...
In this episode, Scott Hanselman and Mark Russinovich dive into where they get their tech news and how their habits have evolved from the early days of blogging and RSS to today’s AI-focused email newsletters. They reminisce about the heyday of blogs, the rise and fall of Google Reader, and Mark’s old NT Internals mailing list, which once had nearly 90,000 subscribers. They compare curated sources like Techmeme, The Verge, and The Information, and discuss how AI-driven newsletters have replaced ...
Scott Hanselman and Mark Russinovich share how they tackle the daily deluge of information and tasks. They explore various methods, from Mark's informal spiral notebook and "productive procrastination" to Scott's use of digital tools like the Remarkable and geofenced reminders. The conversation delves into the psychological benefits of offloading tasks, the role of shared calendars, and whether AI can truly serve as a comprehensive "second brain."
This episode explores the "AI productivity trap," where experienced engineers gain significant efficiency from AI, while early-career professionals risk falling behind without proper guidance. The hosts advocate for a fundamental shift in software development, proposing that senior engineers primarily focus on teaching and formal knowledge transfer, moving beyond traditional internships to a multi-year mentorship model. They also delve into the implications for company hiring strategies and university education, highlighting the importance of fostering critical thinking amidst pervasive AI tools.
Scott and Mark delve into the promises and pitfalls of AI-assisted coding, particularly its limitations in managing complex software projects and synchronization. They explore the debate around AI's capacity for true general intelligence, contrasting machine pattern-matching with human learning and world models. The discussion also highlights the dangers of anthropomorphizing AI, the true nature of “thinking tokens,” and the implications for junior developers learning the craft in an AI-dominated landscape.
Scott and Mark delve into career growth at Microsoft, discussing diverse paths for engineers, including management and deep technical expertise. They highlight the significant role of scope, impact, and even luck in promotions, stressing that measurable business outcomes are key. The conversation also covers the importance of communication, the challenges of leveling up, and special distinguished titles for individual contributors who drive innovation.
In this episode, Scott Hanselman and Mark Russinovich dive into the technical side of modern AI research and development workflows. They discuss the power of remote development with VS Code, building custom chatbot tools for jailbreak testing, and exploring token probabilities with log probes. Mark also shares how he leveraged AI to generate a working UX in one shot, why temperature settings matter for model outputs, and his plans to open source his custom chatbot client. Takeaways: Discover how...
In this episode, Scott Hanselman and Mark Russinovich explore the challenges and opportunities of coding with AI assistants. They compare different models, discuss the quirks of “vibe coding,” and share insights on building tools that bridge LLMs and APIs. Mark walks through his experience developing an academic reference checker, highlighting how AI can help structure messy data, uncover edge cases, and speed up complex development work. The conversation also touches on the evolving joy of codi...
This episode delves into strategies for maximizing the effectiveness of one-on-one meetings. Scott Hanselman and Mark Russinovich discuss the importance of understanding individual communication preferences, the value of setting agendas to prioritize crucial topics, and the manager's role in removing team obstacles. They also explore nuanced aspects of professional recognition, differentiating between credit and "lift," and the art of giving constructive feedback while balancing trust with accountability.
In this episode of Scott and Mark Learn To , Scott Hanselman and Mark Russinovich explore vibe coding with AI, testing how Copilot Agent Mode can analyze their transcripts to see who talks more on the show. They discuss coding with AI as a collaborative sculpting process, debate crediting AI for its contributions, and reflect on the human judgment still needed for prompting and refining outputs. Along the way, they generate graphs, poke fun at each other’s talk time, and share insights on how AI...
Scott and Mark discuss AI-assisted tools they built, including a smart directory navigator and a study guide website. They explore challenges like AI hallucination and the need to 'babysit' agents during development. The conversation also touches on computer science history, the evolving cycles of UI design from minimalist to flashy, and the perceived value versus cost of features like 'liquid glass'.
Scott and Mark delve into managing stress in high-pressure roles. Scott shares the rigorous 54-repetition process for his memorized TED talk, comparing it to stand-up comedy. Mark discusses his stress triggers, emphasizing the need for processing time and breaks. Both highlight the critical roles of trusted colleagues ("work besties"), consistent exercise, mindfulness, and simple routines like writing tasks down and maintaining physical space in staying grounded.
Scott Hanselman and Mark Russinovich discuss the nuances of self-promotion and visibility, exploring how to balance personal brand with company representation. They share insights on dealing with online criticism, staying authentic, and how visibility can be a natural side effect of being passionate and sharing useful information. The episode delves into the perceived "grossness" of strategic personal branding versus organic growth and the benefits of thought leadership for both individuals and organizations.
In this episode of Scott and Mark Learn To , Scott Hanselman and Mark Russinovich dive into the chaotic world of large language models, hallucinations, and grounded AI. Through hilarious personal stories, they explore the difference between jailbreaks, induced hallucinations, and factual grounding in AI systems. With live prompts and screen shares, they test the limits of AI's reasoning and reflect on the evolving challenges of trust, creativity, and accuracy in today's tools. Takeaways: AI is g...
In this episode of Scott and Mark Learn To , Scott Hanselman and Mark Russinovich dive into the emotional complexity of receiving feedback—especially when it’s tough to hear. They explore the difference between constructive critique and personal opinion, the impact of timing and context, and how motivation behind feedback can shape how it's received. Sharing real stories about presentation flops, speaker coaching, and surprising reactions to their ideas, they reflect on how experience builds res...
Scott and Mark discuss the implications of using AI for coding in real-world projects, highlighting the differences between greenfield and brownfield development. They explore the limitations of AI models when dealing with large, complex codebases, and the importance of understanding licensing and attribution. They also touch on the challenges of maintaining state and adapting to evolving requirements, emphasizing the need for human expertise.
Scott and Mark explore retro shaders and AI-assisted code generation. Scott demonstrates ShaderGlass, then they dive into applying HLSL shaders within Windows Terminal, using AI to create a fractal shader. They also tackle code attribution, licensing implications, and the concept of "vibe coding."
Scott and Mark discuss Microsoft's internal conference TechReady, where unfiltered discussions about strategy and future technologies take place. They reflect on the challenges of public communication, Microsoft's open culture, and past social media lessons. Mark recounts his advocacy for Rust, while Scott shares printer woes and memories of early printing technology.
In this episode of Scott & Mark Learn To , Scott Hanselman and Mark Russinovich dive into the art of building reputations throughout the careers. Scott shares a story about directly messaging a distinguished engineer with a technical question, sparking a discussion about when it's appropriate to contact someone you don't know. Mark acknowledges that his title and reputation give him confidence to reach out to others but emphasizes not bothering people with "randomness." They explore when it'...
Scott and Mark delve into systems thinking, exploring its meaning, importance, and application beyond coding. They discuss how understanding broader systems enhances decision-making, the challenges of AI integration, and AI-generated code's limitations. They also debate balancing in-depth analysis with swift action.
In this episode of Scott & Mark Learn To , Scott Hanselman and Mark Russinovich dive into the history and evolution of ZoomIt, a popular screen annotation and zooming tool Mark created over 25 years ago. Originally built to enhance technical demos, ZoomIt has become an essential utility for countless users, including Scott, who calls it second nature. Mark shares how the tool's intuitive, keystroke-driven design surpasses alternatives like Windows Magnifier, making it a favorite for presenta...
