Scott & Mark Learn To...

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 creation. The conversation shifts into the realities of vibe coding, the tradeoffs of speed versus quality, and what it means to maintain taste and expertise in an AI-accelerated world, ultimately asking: if AI lowers the barrier to create, does it also lower the standard?   LLM Writing in Tech: Blogs and Articles   Takeaways:    AI hallucinations are already impacting academic research quality The future challenge isn’t using AI; it’s maintaining standards while using it There’s a growing tension between efficiency and craftsmanship   Who are they?     View Scott Hanselman on LinkedIn  View Mark Russinovich on LinkedIn    Watch Scott and Mark Learn on YouTube        Listen to other episodes at scottandmarklearn.to           Discover and follow other Microsoft podcasts at microsoft.com/podcasts    Hosted on Acast. See acast.com/privacy for more information.

In this episode, Scott Hanselman and Mark Russinovich explore how artificial intelligence is reshaping software engineering and the career paths of developers. They discuss the emerging “AI boost” for experienced engineers versus the “AI slowdown” that can hinder those early in their careers, emphasizing the need for companies to create structured learning environments rather than rely solely on AI-driven productivity. The conversation dives into mentorship, apprenticeship models, and how senior engineers must evolve into teachers to ensure vital knowledge transfer. Together, Scott and Mark challenge the industry to rethink how it trains, supports, and measures success for the next generation of software professionals.   Takeaways:    Companies should reward senior engineers who invest time in developing junior talent Critical thinking and troubleshooting skills can’t be automated or shortcut through AI tools Senior developers gain efficiency, while newcomers risk falling behind without proper guidance   Who are they?     View Scott Hanselman on LinkedIn  View Mark Russinovich on LinkedIn    Watch Scott and Mark Learn on YouTube        Listen to other episodes at scottandmarklearn.to           Discover and follow other Microsoft podcasts at microsoft.com/podcasts    Hosted on Acast. See acast.com/privacy for more information.

In this episode, Scott Hanselman and Mark Russinovich dive into the realities of career progression at Microsoft and in tech more broadly. They discuss the different paths engineers can take, whether through management, deep technical expertise, or individual innovation and the role that scope, impact, and even luck plays in promotions. Along the way, they reflect on the challenges of leveling, the importance of communication, and the balance between recognition, influence, and personal fulfillment in a long-term career.   Takeaways:    Engineers can advance without becoming managers through individual contributions Communication and influence are critical for advancing to senior levels Promotions hinge on measurable business outcomes, not just effort or shipped work   Who are they?     View Scott Hanselman on LinkedIn  View Mark Russinovich on LinkedIn    Watch Scott and Mark Learn on YouTube        Listen to other episodes at scottandmarklearn.to           Discover and follow other Microsoft podcasts at microsoft.com/podcasts    Hosted on Acast. See acast.com/privacy for more information.

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 coding, from puzzle-solving by hand to managing AI-driven workflows, and how these shifts are reshaping both productivity and creativity.Takeaways:   Mark’s journey building an academic reference checker with AIHow AI assistants are changing the way developers find joy in codingRefChecker source code: https://github.com/markrussinovich/refchecker Who are they?    View Scott Hanselman on LinkedIn View Mark Russinovich on LinkedIn  Watch Scott and Mark Learn on YouTube      Listen to other episodes at scottandmarklearn.to         Discover and follow other Microsoft podcasts at microsoft.com/podcasts   Hosted on Acast. See acast.com/privacy for more information.

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 is changing coding and creative work.   Takeaways:    See how Copilot Agent Mode can generate graphs from transcripts Learn the difference between vibe coding and spec-driven development Explore the potential for interactive charts using D3.js for podcast data   Who are they?     View Scott Hanselman on LinkedIn  View Mark Russinovich on LinkedIn    Watch Scott and Mark Learn on YouTube        Listen to other episodes at scottandmarklearn.to           Discover and follow other Microsoft podcasts at microsoft.com/podcasts    Hosted on Acast. See acast.com/privacy for more information.

In this episode of Scott and Mark Learn To, Scott Hanselman and Mark Russinovich Scott shares the behind-the-scenes stress and preparation that went into his recent TEDx talk, which required memorizing a 12-minute script and performing it without a teleprompter. Mark Russinovich opens up about how he experiences stress when his schedule gets out of control, and both hosts discuss the importance of mindfulness, exercise, having work besties, and managing social energy. The episode is packed with practical tips, vulnerable moments, and reflections on what it really takes to perform at a high level, whether it’s on stage, at work, or in life.   Takeaways:    Trusted colleagues make high-pressure jobs sustainable Skill is built through reps, not just raw ability Repetition, feedback, and coaching turned Scott’s talk into something powerful      Who are they?     View Scott Hanselman on LinkedIn  View Mark Russinovich on LinkedIn    Watch Scott and Mark Learn on YouTube        Listen to other episodes at scottandmarklearn.to           Discover and follow other Microsoft podcasts at microsoft.com/podcasts    Hosted on Acast. See acast.com/privacy for more information.

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 getting better, but we still need to be careful and double check our work AI sometimes gives wrong answers confidently Jailbreaks break the rules on purpose, while hallucinations are just AI making stuff up    Who are they?     View Scott Hanselman on LinkedIn  View Mark Russinovich on LinkedIn    Watch Scott and Mark Learn on YouTube        Listen to other episodes at scottandmarklearn.to           Discover and follow other Microsoft podcasts at microsoft.com/podcasts    Hosted on Acast. See acast.com/privacy for more information.

In this episode of Scott & Mark Learn To, Scott Hanselman and Mark Russinovich discuss using AI to build a fractal shader in just 15 minutes—something that would normally take hours of manual coding. They explore the challenges and limitations of AI in real-world projects, particularly with large, complex codebases. The conversation covers the importance of understanding licensing and tools like GitHub Copilot for sourcing and attributing code. Mark shares his experiences with AI-assisted coding, particularly the frustrations of models that "fix" issues but miss the mark. They highlight how AI struggles with complex projects, maintaining state, and adapting to evolving requirements. Ultimately, they agree that while AI can assist with certain tasks, human expertise is essential for ensuring the right context and specification in development.  Takeaways:    Despite initial skepticism, the first attempt at creating the shader worked nearly perfectly AI models may not always use the latest API versions, causing security or functionality issues Enterprise AI development involves continuous iteration, evolving from V1 to more refined versions    Who are they?     View Scott Hanselman on LinkedIn  View Mark Russinovich on LinkedIn    Watch Scott and Mark Learn on YouTube        Listen to other episodes at scottandmarklearn.to           Discover and follow other Microsoft podcasts at microsoft.com/podcasts   Download the Transcript Hosted on Acast. See acast.com/privacy for more information.