Inside Amazon's AI video generator | Kabir Bedi

What if creating a professional video for your business was as simple as a single click?We're joined by Kabir Bedi, Head of Product for Image and Video Generation at Amazon Ads, to discuss how generative AI is making that a reality. He provides an inside look at Amazon's mission to democratize video advertising, empowering everyone from mom-and-pop shops to large enterprises with their innovative video generator that evolved from simply showing products to showcasing them in realistic, multi-scene lifestyle settings.Kabir shares key insights into the engineering culture that powers this innovation, built on deep customer obsession and a dynamic, experimental mindset. He explains why bringing the entire team—including engineers and scientists—into direct conversations with users was a game-changer for their development process. Plus, listen as Kabir explains why a "learn and be curious" mindset is the key to thriving in this new landscape of AI-driven product development.Check out:The DevEx guide to AI-driven software developmentDownload: The 6 trends shaping the future of AI-driven development Follow the hosts:Follow BenFollow AndrewFollow today's guest(s):Follow Kabir on LinkedInLearn more on the About Amazon Blog and the Amazon Ads BlogReferenced in today's show:Meta's $100M poaching project“Real strength is not in poaching rather it’s in growing, retaining and respecting the people you already have.” -Mohit Malik“Localhost tracking” explained. It could cost Meta 32 billion.Cursor’s Bold Hiring Playbook: No AI in Interviews, Just Real Projects and Real PeopleWriting Toy Software Is A JoySupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

What if the traditional engineering career path is being fundamentally rewritten by AI? We're joined by Philipp Schmid, Senior AI Developer Relations Engineer at Google DeepMind, to explore how artificial intelligence is not just a tool, but a force reshaping engineering roles, team dynamics, and the foundational methods of skill development. Philipp, with his background at Hugging Face and now at the cutting edge with Google DeepMind, offers a unique perspective on the rise of AI-native teams and engineers who learn faster, work more broadly, and drive innovation at an unprecedented scale.Philipp offers an inside look at Google DeepMind's engine of AI innovation and breaks down the key differences between Google's flagship Gemini models and the versatile Gemma family of open models, detailing their distinct purposes.We also touch upon exciting takeaways from the recent Google I/O event, including powerful new on-device capabilities and the mind-blowing text-to-video generation with Veo.Finally, Philipp shares practical advice for engineers and their organizations on navigating this AI-driven landscape, emphasizing continuous learning, an adaptable mindset, and how to effectively leverage a diverse AI toolkit to thrive.Check out:Download: The 6 trends shaping the future of AI-driven development Follow the hosts:Follow BenFollow AndrewFollow today's guest:Twitter: @philschmidLinkedInGitHub (philschmid)Learn more about Google DeepMind's models: Google AI StudioReferenced in today's show:OpenAI's latest partner: Mattel | LinkedIn I Read All Of Cloudflare's Claude-Generated Commits AI coding assistants aren’t really making devs feel more productive - LeadDev Congratulations on creating the one billionth repository on GitHubSupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

Imagine saving as much as 75 days of work within a six-month period, all through intelligent automation.Building on last week’s discussion about the critical shift from passive metrics to active productivity, host Ben Lloyd Pearson and LinearB co-founder Dan Lines now look forward to realities like this: 19% cycle time reduction and reclaiming significant engineering time. They move beyond common narratives surrounding AI to present actionable success stories and strategic approaches for engineering leaders seeking tangible results from their AI initiatives. This concluding episode tackles how to safely and effectively adopt AI across your software development lifecycle. Dan explains the necessity of programmatic rules and control, detailing how LinearB's gitStream technology empowers teams to define precisely when, where, and for whom AI operates. This ranges from AI-assisted code reviews with human oversight for critical services, to enabling senior developers to make judgment calls, and even automating merges for low-risk changes. Ben and Dan also explore the exciting future of agentic AI workflows, where AI agents could manage tasks from design and Jira story creation to coding and deployment, making developer control even more critical. Check out:The DevEx guide to AI-driven software developmentSurvey: Discover Your AI Collaboration StyleFollow the hosts:Follow BenFollow AndrewReferenced in today's show:The Pentagon launched a military-grade Y Combinator, signaling that defense tech is officially cool on college campusesJapan Post launches 'digital address' systemReddit sues Anthropic for scrapingMy AI Skeptic Friends Are All NutsSupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

Are your teams feeling the intense pressure to "produce more" in an era increasingly dominated by AI?Join hosts Ben Lloyd Pearson and Dan Lines as they unpack a major shift in how engineering organizations must now approach productivity. Dan reveals the urgent challenges he hears directly from CTOs and VPs, who are grappling with how to define their AI strategy for genuine productivity gain, accurately measure its true impact, and understand the resulting implications for their workforce.In this episode, Ben and Dan explore why traditional software engineering intelligence (simply having metrics and information) is no longer sufficient in 2025. Together, they explore productivity's nuanced meaning and discover how organizations can shift from passive data observation to an active improvement mindset, and get a look at what defines a developer productivity insights platform.Check out:Register for Beyond Copilot: What’s Next for AI in Software DevelopmentSurvey: Discover Your AI Collaboration StyleFollow the hosts:Follow BenFollow AndrewReferenced in today's show:Why Your AI Coding Assistant Keeps Doing It Wrong, and How To Fix ItAs a developer, my most important tools are a pen and a notebookThe problem with shadow developmentSupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

What can ancient languages and epic poems teach us about building resilient tech and future-proof teams?Host Andrew Zigler welcomes Matt Greenwood, Chief Innovation Officer of Two Sigma, for a conversation that uniquely blends their shared background in classical languages with over two decades of Matt’s experience at the forefront of financial technology. Matt unveils how this classical training has profoundly shaped his approach to building enduring innovation, fostering a resilient company culture, and leading with empathy.Matt explains his vision for building and evolving innovation via platforms, alongside his strategies for effective goal-setting and fostering deep conceptual understanding in his team. He offers invaluable lessons on the importance of forgiving the decisions of our past selves, adapting processes for evolving needs, and thoughtfully engaging with AI to augment human creativity. This conversation is a masterclass in strategic foresight, cultivating a constant hunger for learning, and building an adaptable organization ready for whatever the future holds.Check out:Beyond Copilot: What’s Next for AI in Software DevelopmentSurvey: Discover Your AI Collaboration StyleFollow the hosts:Follow BenFollow AndrewFollow today's guest(s):Website: twosigma.comLinkedIn: Matt GreenwoodReferenced in today's show:Google I/OMicrosoft BuildCode with ClaudeJava at 30: The Genius Behind the Code That Changed TechSupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

What happens when the person trained to spot burnout becomes its next victim?Kelly Vaughn is a Senior Engineering Manager at Zapier, the author of the After Burnout Substack, and a trained therapist. She joins hosts Ben and Andrew to share her incredibly candid journey of discovering burnout in herself. Kelly reveals how she (despite her professional understanding of burnout's mechanisms) found herself deep in its grip, recounting the slow realizations like dwindling passion, increasing cynicism, and distinct physical tolls like disrupted sleep and a loss of hunger cues.This raw conversation offers vital lessons for anyone in a high-pressure career (and let’s face it: that’s all of us!). As the tech landscape accelerates with AI, Kelly shares insights on managing its pressures and opportunities. She redefines ambitions for herself alongside the non-negotiables she established for her own well-being when seeking her new role. Listeners will gain powerful insights into identifying their own limits, the courage for pivotal changes, and integrating new demands without self-sacrifice.Check out:AI Code Reviews: Automate AI code reviews for every PRSurvey: Discover Your AI Collaboration StyleFollow the hosts:Follow BenFollow AndrewFollow today's guest(s):Personal Website: kvlly.com"After Burnout" Newsletter: afterburnout.co"The Modern Leader" Newsletter: modernleader.isKelly’s Article: On burnout, quitting, and redefining what mattersReferenced in today's show:The FAA has resorted to buying parts on eBay because its equipment is so old, Transportation Secretary Sean Duffy says 2025-05-11 air traffic controlDOGE Is in Its AI EraIRS hopes to replace fired enforcement workers with AI Microsoft lays off about 3% of its workforce in what one executive calls a ‘day with a loSupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

Still stuck in a reactive loop with incident response, only fixing problems after they happen? JJ Tang, Co-founder and CEO of Rootly, joins host Andrew Zigler to reveal how to shift beyond reactive, leveraging powerful AI and an often-underestimated skill in engineering: genuine customer empathy. Discover how these elements are crucial for navigating the complexities of modern infrastructure and shaping the future of incident management.JJ explores the forefront of incident response automation, discussing how to integrate shiny new tech like AI safely and why deep customer understanding is key to building trust and reliability. Learn about the common pitfalls leaders face, the cultural shifts needed for proactive reliability, and how teams can make our digital world safer.Check out:Beyond Copilot: What’s Next for AI in Software DevelopmentSurvey: Discover Your AI Collaboration StyleFollow the hosts:Follow BenFollow AndrewFollow today's guest(s):LinkedIn: JJ TangWebsite: rootly.comReferenced in today's show:OpenAI agrees to buy Windsurf for about $3 billion, Bloomberg News reportsAmazon launches first Kuiper internet satellites, taking on StarlinkAvoiding Skill Atrophy in the Age of AIWhy developers and their bosses disagree over generative AISupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

Is front-end vs. back-end an antiquated way to structure engineering teams? With AI augmenting skills, a new model is emerging: the product engineer.This week, Andrew sits down with Lee Robinson, VP of Product at Vercel to crack open the future of the web. As a respected educator and voice in the webdev community (check out his YouTube!), Lee shares his unique perspective on building both cutting-edge tools and high-performing teams.As the VP of Product, Lee charts the evolution of developer roles and illustrates for us the rise of "product engineers" who own features end-to-end. Learn how AI tools are not just augmenting specialists but enabling designers, PMs, and founders to build "personal software." We also cover changing team dynamics and get Lee's advice on navigating the hiring process in the AI era, including: why personalization is key for candidates, how managers can spot authenticity (hint: AI-generated cover letters are obvious!), and why building in public is critical for career growth today.Check out:Beyond Copilot: What’s Next for AI in Software DevelopmentSurvey: Discover Your AI Collaboration StyleFollow the hosts:Follow BenFollow AndrewFollow today's guest(s):Website: leerob.comYouTube: @leerobLinkedIn: Lee RobinsonVercel: vercel.comNext.js: nextjs.orgv0 by Vercel: v0.dev Referenced in today's show:This week in social, we noticed: AIDuolingo has an AI mandate tooGoogle Just Launched an AI-Powered Duolingo AlternativeIntel CEO announces layoffs, restructuring, $1.5 billion in cost reductions, expanded return to office mandate | Tom's HardwareSupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

We've spent decades teaching ourselves to communicate with computers via text and clicks. Now, computers are learning to perceive the world like us: through sight and sound. What happens when software needs to sense, interpret, and act in real-time using voice and vision?This week, Andrew sits down with Russ d'Sa, Co-founder and CEO of LiveKit, whose technology acts as the crucial infrastructure enabling machines to interact using real-time voice and vision, impacting everything from ChatGPT to critical 911 responses.Explore the transition from text-based protocols to rich, real-time data streams. Russ discusses LiveKit's role in this evolution, the profound implications of AI gaining sensory input, the trajectory from co-pilots to agents, and the unique hurdles engineers face when building for a world beyond simple text transfers.Check out:AI Code Reviews: An Engineering Leader’s Survival GuideSurvey: Discover Your AI Collaboration StyleFollow the hosts:Follow BenFollow AndrewFollow today's guest(s):Website: livekit.ioGitHub: github.com/livekitX: x.com/livekitRuss: x.com/dsaReferenced in today's show:The Rise of Slopsquatting: How AI Hallucinations Are Fueling a New Class of Supply Chain AttacksHas the VSCode C/C++ Extension been blocked?OpenAI tells judge it would buy Chrome from GoogleChain-of-Vibes | Pete Hodgson Seattle crosswalk signals with deepfake Bezos audio may have been hacked with just a cellphone Support the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever

Think building killer APIs like Stripe or Twilio is purely a technical feat? Think again.This week, we dive into why crafting successful APIs is fundamentally an organizational challenge, demanding internal excellence long before code is deployed. Sagar Batchu, co-founder and CEO of Speakeasy, joins us to unpack the crucial role of ownership, design principles, and why even internal APIs benefit from treating them like first-class products. Discover how Conway's Law dictates your API's fate and why achieving that coveted developer experience starts with your company's structure.Getting these foundations right is more critical than ever, as the landscape now faces a dramatic shift with the rise of LLMs and agentic AI. This potentially multiplies API usage and introduces the concept of "Agent Experience" (AX), demanding even greater rigor around clear standards, documentation, and metrics like "Time to First 200." Sagar also explores the emerging Model Context Protocol (MCP) and explains why focusing on developer productivity today prepares you for the AI-driven future of tomorrow.Check out:AI Features Demo: The Future of Productivity Is AI-DrivenSurvey: Discover Your AI Collaboration StyleFollow the hosts:Follow BenFollow AndrewFollow today's guest(s):Website: speakeasy.comLinkedIn: SpeakeasyX: @speakeasydevReferenced in today's show:It costs nothing to be polite unless you're talking to ChatGPT - then it costs tens of millionsAnnouncing the Agent2Agent Protocol (A2A) - Google Developers Blog A Deep Dive Into MCP and the Future of AI ToolingSupport the show: Subscribe to our Substack Leave us a review Subscribe on YouTube Follow us on Twitter or LinkedIn Offers: Learn about Continuous Merge with gitStream Get your DORA Metrics free forever