Dev Interrupted

• The CTO must now think like the CFO to survive | Sancus Ventures’ Lake Dai

  AI is forcing engineering leaders to become part-CFO, part-governance expert, and part-business strategist. Are you ready for the shift? We're joined by Lake Dai, a globally recognized AI expert, professor at Carnegie Mellon, and founder of Sancus Ventures, to explore the new operating strategies required in an AI-first era. She explains why AI has evolved from a simple tool to a core business metric that leaders are held accountable for on earnings calls. This new reality introduces massive new compute costs—sometimes 30-50% of OpEx—forcing leaders to adopt the financial foresight of a CFO to forecast and justify spending.Beyond the balance sheet, Lake identifies AI governance as the biggest blind spot for most leaders today, outlining the urgent need for an AI handbook to manage unit, system, and ethical risks. This strategic shift also reshapes the engineering org itself, from managing hybrid teams of humans and agents to the need for new training environments, almost like "AI flight simulators." This episode is an essential briefing on these new complexities, all centered on Lake's most urgent advice: in a world moving this fast, the best strategy is to slow down and focus on the fundamentals.LinearB: Your AI productivity journey starts hereFollow the hosts:Follow AndrewFollow BenFollow DanFollow today's guest(s):Connect with Lake on LinkedInSubscribe to Lake’s Substack: LakeD-AI UnbundledLearn more about: Sancus VenturesReferenced in today's show:I didn't believe it until I saw it: but it *really* works in open offices! And you cannot even hear devs "whispering."Councils of agentsIf you don't tinker, you don't have tasteI invited strangers to message me through a receipt printerSupport 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

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• How leaders win over their team’s biggest AI skeptics | Superhuman’s Loic Houssier

  Forget top-down mandates. How do you foster organic AI adoption on a skeptical, high-performing engineering team? Loic Houssier, Head of Engineering at Superhuman, joins us to share how he did just that. He explains his strategy for overcoming cynicism, which involved leveraging a highly respected internal champion, the Chief Architect, to re-evaluate the tools and prove their potential was no longer just buzz.Discover his team's biggest, unexpected productivity gains: dramatically faster ramp-up times on new codebases and the rapid creation of valuable internal tools, rather than just raw code generation speed. Loic details Superhuman's pragmatic, high-trust approach to measurement, blending qualitative feedback with simple signals like PR labels. He explains how they fostered this adoption with a bottom-up "AI Guild," empowering engineers of all seniorities without a heavy-handed mandate. He also reveals a stunning real-world example where AI turned a potentially days-long compliance task into a 90-minute win. This episode is a practical playbook for building genuine, bottom-up AI adoption.Get the guide: AI productivity guide for engineering leadersFollow the hosts:Follow BenFollow AndrewFollow today's guest(s):Connect with Loïc HoussierLearn more about Superhuman: superhuman.comSuperhuman was acquired by Grammarly: Read about the acquisitionReferenced in today's show:Amazon brain drain finally caught up with AWSClaude Skills are awesome, maybe a bigger deal than MCP How to Say NoThe Field Guide to AI SlopSupport 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

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• AI isn't for cutting costs, it's for multiplying impact | Super.com's Matt Culver

  Is your company using AI to trim your budget, or to multiply your team's impact? We're joined by Matt Culver, a senior engineering leader at Super.com, to discuss why the common view of AI as a tool for cost-cutting is a misguided "accounting mindset" that ultimately destroys trust. He argues that leaders should instead see efficiency gains from AI as a powerful opportunity to reinvest in their teams. This conversation reframes the AI debate by urging leaders to look beyond the coding loop to improve the entire product development lifecycle—from ideation to delivery.Matt explains that the key to successful AI adoption is aligning new initiatives with the developer's core incentives: removing friction and enabling the creative flow state that makes their job enjoyable. He provides a human-centric approach for channeling AI's power to solve upstream problems in product planning and market research, rather than just generating more code. Learn how to use AI not as a means to an end, but as a way to empower your developers, generate more value, and build a high-trust engineering culture.Bring AI into your code review process with LinearBFollow the hosts:Follow BenFollow AndrewFollow today's guest(s):Learn more about Super: Super.comConnect with Matt: LinkedIn | [email protected] in today's show:A small number of samples can poison LLMs of any sizeRevisiting "Intelligence Drift"AI profiteering is now indistinguishable from trolling The AI water issue is fakeHTML’s Best Kept Secret: The <output> Tag Life in a World of Pervasive Immorality: The Ethics of Being AliveSupport 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

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• The timelessness of vector databases | Pinecone’s Ram Sriharsha

  With massive context windows and new agent frameworks, do vector databases still matter? Ram Sriharsha, CTO at Pinecone, joins the conversation to make the definitive case that they're more critical than ever. He explains that at the core of all AI is search, and externalizing this function is non-negotiable for security, auditability, and control.Ram offers a clear starting path for engineering leaders: begin with simple Retrieval-Augmented Generation (RAG) applications, but immediately implement a robust evaluation framework to manage hallucinations and ensure quality. He shares his perspective on the skills that matter most now, arguing that curiosity and the rise of the generalist engineer are critical in an AI-powered world. This episode is a guide to building the AI stack from the ground up, from using AI as a "good junior engineer" for testing to cultivating the engineering mindset of tomorrow.Bring AI into your code review process with LinearBFollow the hosts:Follow BenFollow AndrewFollow today's guest(s):Learn more about Pinecone: pinecone.ioPinecone Tutorials & Blog: Explore guides on RAG, vector databases, and moreConnect with Ram Sriharsha: LinkedInReferenced in today's show:Your New 500K AI Coworkers Just ArrivedHow I influence tech company politics as a staff software engineerCoinbase says 40% of code written by AI, mostly tests and TypescriptCelebrating 1 Trillion Web Pages ArchivedSupport 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

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• Is Agentforce the future of enterprise vibe coding? | Salesforce’s Dan Fernandez

  Vibe coding is a developer's dream, but in the enterprise, it can be a nightmare of risk and shadow IT. So how do you saddle the 'wild horse' of modern AI development? Dan Fernandez, VP of Product Management, Developer Services at Salesforce, joins the conversation to share the answer: a new category his team is pioneering called Enterprise Vibe Coding. This discussion reveals how to move beyond flashy greenfield AI demos and build for the reality of most enterprises, where the goal is to safely reuse existing systems, not reinvent them from scratch.Dan breaks down the specific guardrails Salesforce has built, from sandboxed environments for safe testing to automated "quality gates" that act as a bouncer for both human and AI-generated code. He shares the powerful lesson that building customer trust through policies like zero data retention is more important than any single feature. He explains why the real work of enterprise AI is more like secure "plumbing"—connecting the hardened systems you already have. This is an essential guide for any leader looking to apply the speed of AI to the complex reality of enterprise software.Get the guide: AI productivity guide for engineering leadersFollow the hosts:Follow BenFollow AndrewFollow today's guest(s):Unleash Your Innovation with Agentforce Vibes: Vibe Coding for the EnterpriseLearn more about Salesforce for Developers: developer.salesforce.comSalesforce Extensions for VS Code: VS Code MarketplaceSalesforce Code Builder: Learn more about the zero-install IDEConnect with Dan Fernandez: LinkedInReferenced in today's show:Future of tech leadership survey report 2025 - Riviera PartnersStop Avoiding Politics – Terrible Software Agentic Commerce I built ChatGPT with Minecraft redstone!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

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