Scott and Mark learn...how agents reshape software engineering | BRK247

Microsoft Developer · Intermediate ·📰 AI News & Updates ·1mo ago

Key Takeaways

Explores how AI agents reshape software engineering with lessons learned and failure modes

Original Description

AI is changing how software is created—and what it means to be a software engineer. We’ll explore how AI agents are reshaping development: where they accelerate progress, where they fall short, and what’s changing for the profession. Along the way, we’ll share failure modes, lessons learned, and propose ways engineers and organizations can adapt. Real talk, no hype. Seating for this session is first-come, first-served. Add it to your schedule to plan your day and arrive early to secure a spot. To learn more, please check out these resources: * https://aka.ms/build26/BRK247 𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Mark Russinovich * Scott Hanselman 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This is one of many sessions from the Microsoft Build 2026 event. View even more sessions on-demand and learn about Microsoft Build at https://build.microsoft.com BRK247 | English (US) | Agents & apps Breakout | (300) Advanced #MSBuild Chapters: 0:00 - Project Lobster and Aspire team demonstrate AI-augmented software practices 00:14:42 - AI Compared to an Intern: Limited Context and Learning Ability 00:15:33 - Examples of AI’s Faulty Fixes and Benchmark Misinterpretations 00:19:55 - AI Challenges Demonstrated Through Zoomit Panorama Feature 00:22:33 - Discussion on complexities of Cleartype and pixel color challenges 00:27:12 - Observations on AI-generated code pitfalls and effects on early-career developers 00:39:38 - Historical perspective—each technology wave prompts panic but skills evolution continues 00:42:00 - Preceptor demo analogy—training through guided real experiences and safe mistakes 00:44:27 - Future outlook—AI will not replace human oversight; focus shifts to learning, mentoring, and cognitive engagement
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Chapters (9)

Project Lobster and Aspire team demonstrate AI-augmented software practices
14:42 AI Compared to an Intern: Limited Context and Learning Ability
15:33 Examples of AI’s Faulty Fixes and Benchmark Misinterpretations
19:55 AI Challenges Demonstrated Through Zoomit Panorama Feature
22:33 Discussion on complexities of Cleartype and pixel color challenges
27:12 Observations on AI-generated code pitfalls and effects on early-career develop
39:38 Historical perspective—each technology wave prompts panic but skills evolution
42:00 Preceptor demo analogy—training through guided real experiences and safe mista
44:27 Future outlook—AI will not replace human oversight; focus shifts to learning,
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