Knowledge Distillation Podcast

ASK-Y

Knowledge Distillation: The Rise of the AI Analyst Welcome to Knowledge Distillation – a series exploring how AI Analysts are transforming the future of data work. We look at practitioners becoming AI Analysts, founders building AI Analyst tools, VCs backing the AI Analyst wave, and market analysts mapping the trend. Each episode uncovers what it means to be an AI Analyst today – the workflows being reinvented, the skills analysts need now, and the promises AI is keeping or breaking. From prompt engineering to context management, we dive into the real conversations shaping this role. Let’s distill some knowledge. Because bots won’t win. AI Analysts will. Explore More: www.ask-y.ai

  1. 14# Simo Ahava on AI in Marketing, Why Thinking Matters & Agentic Commerce

    MAR 25

    14# Simo Ahava on AI in Marketing, Why Thinking Matters & Agentic Commerce

    In this episode of Knowledge Distillation, Katrin Ribant speaks with Simo Ahava – quite simply the person the entire digital analytics and technical marketing community turns to when they need to understand how things actually work. Simo has been writing about web analytics, tag management, and the Google marketing stack since 2010, and his blog at simoahava.com has become the definitive technical reference for anyone implementing Google Analytics or Google Tag Manager. A Google Developer Expert in both platforms from 2014 to 2025, a multiple Digital Analytics Association award finalist, and one of the most generous knowledge sharers the industry has ever seen – if you’ve ever asked a question on Measure Slack, there’s a good chance Simo answered it, thoughtfully, for free. He co-founded Simmer with his wife Mari Ahava, an online learning platform for technical marketers that has become the gold standard for courses on server-side tagging and BigQuery. He is partner and co-founder at 8-bit-sheep, a Helsinki-based digital services consultancy, and co-hosts the Standard Deviation Podcast with Juliana Jackson. The conversation opens with what Simo calls the educator’s dilemma: AI makes it trivially easy to get answers, which removes the incentive for deep learning. His students take course content to an LLM, get a conflicting answer, and bring the contradiction back – without the baseline knowledge to judge which is correct. Katrin pushes back: practitioners doing real analytics work need to understand fundamentals like context windows and attention mechanisms. They land on a distinction – Simo’s concern applies to learners seeking quick answers, Katrin’s to practitioners maintaining context continuity across complex workflows. The episode then pivots to agentic commerce. Simo draws a direct line from his data layer and server-side tracking expertise to the challenge of designing websites for AI agent access. Tag management systems have let organizations survive with poorly structured data for years. Agentic commerce breaks that – agents need structured data by design, not retroactive patches. Simo warns against over-optimizing for agents at the expense of human UX, and raises the unsolved measurement problem: how do you track agentic traffic when AI agents have no reason to identify themselves? All episodes on our website: www.ask-y.ai/knowledge-distillation-podcast Learn more about ASK-Y: www.ask-y.ai

    1h 5m
  2. 13# Scott Brinker on the SaaS Apocalypse, Changing Software Moats & the Rise of Context Engineering

    MAR 16

    13# Scott Brinker on the SaaS Apocalypse, Changing Software Moats & the Rise of Context Engineering

    In this episode of Knowledge Distillation, Katrin Ribant speaks with Scott Brinker – the creator of the Marketing Technology Landscape Supergraphic, the map of the martech industry that started with 150 logos in 2011 and now tracks over 14,000. Scott spent eight years as VP of Platform Ecosystem at HubSpot, where he built out their partnership and integration ecosystem. He holds degrees from Columbia and MIT Sloan, co-authors the annual State of Martech report with Franz Riemersma, and now works full-time as an independent martech analyst through Chief MarTech. Katrin still drinks her coffee from a mug Scott gave out a decade ago – the one with snails at a boardroom table and the tagline: technology changes exponentially, organizations change logarithmically. Together they dig into the so-called SaaS Apocalypse – triggered by AI-native tools lowering the barrier to building software – and land on a nuanced take: the market overreacted in the short term, but the long-term disruption to SaaS business models is real. The risk isn’t that customers will vibe code their own CRM; it’s that a thousand new companies will. Scott introduces his framework of systems of truth and systems of context – an evolution of the classic systems of record and systems of engagement – and explains why delivering the right information, to the right person or agent, at the right moment is the hardest and most valuable problem in martech today. Katrin connects this directly to Ask-Y’s thesis: that the central challenge in analytics isn’t the tools, it’s maintaining context continuity across every step of the workflow – from data connection through transformation to stakeholder output. The conversation goes deep on Scott’s framework of three types of AI agents in marketing: agents for marketers (internal productivity), agents for customers (brand-controlled interactions like AI-powered chatbots and SDRs), and agents of customers (the disruptive category – AI assistants that work for the buyer, not the seller). They explore how agents of customers are forcing a rethink of everything from SEO to email marketing to e-commerce, and Katrin lays out her thesis that agentic commerce will trigger a workstream comparable to mobile platforming, the GA4 migration, and a fundamental shift in customer relationships – all at once. Scott agrees and adds his prediction that agentic email is the next major disruption most marketers aren’t preparing for. The episode closes on the AI analyst role itself: Scott argues that hands-on experience with AI tools is non-negotiable, that understanding code remains critical even when you’re not writing it, and that the only way to build the mental model required for this era is through consistent, daily practice. His advice: the only way out is through. All episodes on our website: www.ask-y.ai/knowledge-distillation-podcast Learn more about ASK-Y: www.ask-y.ai

    1h 7m
  3. 12# Eliot Durbin on the SaaS Apocalypse, Betting on People Over Products, and Founder Skills

    MAR 9

    12# Eliot Durbin on the SaaS Apocalypse, Betting on People Over Products, and Founder Skills

    In this episode of Knowledge Distillation, Katrin Ribant speaks with Eliot Durbin, General Partner at Boldstart Ventures – one of enterprise software’s most active inception-stage funds, with a portfolio that includes Clay, Snyk, Wiz, Crew AI, Kustomer, and Keycard, among others. Boldstart was founded in April 2010 with a $1M first fund and pioneered what Eliot calls “inception investing”: backing technical founders on the strength of a person and a thesis – before a product, before a pitch deck, sometimes before there’s even a market. Katrin and Eliot have known each other for 15 years, with Boldstart backing Ask-Y at its earliest stage. Together they unpack the so-called SaaS Apocalypse – the trillion-dollar collapse in software market cap triggered by AI-native competition – and whether the hype matches the reality. Eliot argues it doesn’t: software isn’t dying, it’s evolving, just as it did through the cloud and mobile revolutions. The companies that move fast and go AI-native will survive; those that don’t will go the way of the ones that missed mobile. The conversation goes deep on what actually compounds at inception in a world where anyone can vibe-code a prototype in a week, how moats are being redefined around trust and interaction data, and why speed remains the only real advantage at the earliest stage. They also dig into agentic commerce – the wave forcing brands to re-architect their websites and data layers for both human and AI agent audiences – and what that means for analytics teams. The episode closes on the AI analyst role itself: Eliot draws a direct parallel to how Clay created the GTM engineer out of rev ops, arguing the same elevation is coming for analysts – not replacement, but a shift to higher-order reasoning. His single best piece of advice for anyone navigating this moment: play with as many tools as you can. All episodes on our website: www.ask-y.ai/knowledge-distillation-podcast Learn more about ASK-Y: www.ask-y.ai

    53 min
  4. 11# June Dershewitz on AI Investment, Reinvention & Skills That Survive Disruption

    MAR 2

    11# June Dershewitz on AI Investment, Reinvention & Skills That Survive Disruption

    In this episode of Knowledge Distillation, Katrin Ribant talks with June Dershewitz – a pioneering analytics leader who has been at the center of the data community for over two decades. June started her career in web analytics in 1999, co-founded Web Analytics Wednesdays (the industry gathering that launched a thousand local analytics communities), served as President of the Board of the Digital Analytics Association, and has led analytics and data governance teams at some of the largest media and entertainment platforms in the world. Now, as co-founder of InvestInData – a collective of 50+ Chief Data Officers and VPs of Data who angel invest in early-stage data startups – she sits at the unique intersection of practitioner, community builder, and investor. Together they explore what 25 years of analytics evolution teaches you about the current AI transformation, how angel investing from the practitioner seat gives you a fundamentally different lens on which AI tools will actually matter, and why the community-building instinct that drove Web Analytics Wednesdays is more relevant now than ever as analysts figure out what the AI ​​Analyst role actually looks like. June shares her perspective on scaling data teams through every major disruption – from the early days of web measurement through big data, real-time analytics, and now agentic AI – and what she’s learned about the human skills that no technology cycle has managed to automate away. All episodes on our website: www.ask-y.ai/knowledge-distillation-podcast Learn more about ASK-Y: www.ask-y.ai

    1 hr
  5. 10# Tim Wilson on Thinking Before Measuring in the Agentic Commerce Era

    FEB 20

    10# Tim Wilson on Thinking Before Measuring in the Agentic Commerce Era

    In this episode of Knowledge Distillation, Katrin Ribant talks with Tim Wilson – one of the most respected voices in digital analytics, widely known as the Quintessential Analyst (a title he’ll deny but absolutely deserves) and equally famous for climbing on a soapbox and delivering the kind of rants that somehow leave you smarter when he’s done. Tim has been working with digital data full-time since 2001, holding senior analytics roles at Search Discovery, Analytics Demystified, and across multiple agencies and Fortune 500 consultancies, and is widely known for his no-nonsense, clarity-first approach to getting business value out of data – earning him a reputation as one of the industry’s most beloved (and self-admittedly cranky) analytical thinkers. Continuing the agentic e-commerce series, this episode goes upstream: before you instrument, before you build the data layer, how do you decide what to measure? Tim draws on over two decades of experience to argue that the agentic commerce shift – comparable in scale to mobile, Amazon, and GA4 combined – demands business clarity first, not more data collection. Together they explore why organizations keep repeating the same measurement mistakes across every technology disruption, how to use hypothesis testing and primary research to cut through the hype, and why the analyst’s real superpower is resisting the urge to solution before the business question is clear. The conversation also dives into the evolving skills analysts need now, from understanding LLMs to prompt and context engineering as the new SQL. All episodes on our website: www.ask-y.ai/knowledge-distillation-podcast Learn more about ASK-Y: www.ask-y.ai

    1h 27m
  6. 9# Josh Silverbauer on Agentic Measurement, Instant Checkout Attribution, and What’s Next

    FEB 13

    9# Josh Silverbauer on Agentic Measurement, Instant Checkout Attribution, and What’s Next

    Josh Silverbauer is Head of Analytics and CRO and Partner at From the Future, where he architects data layers and analytics implementations for brands navigating the messiest parts of measurement. He’s also the host of The Third Party Show – a comedy-musical talk show for digital marketing – and the creator of a rock opera about an alien named Cookie who loses his universe when Universal Analytics sunsets. In this episode, we dig into what happens when a purchase occurs without a browser session. OpenAI’s Instant Checkout means transactions can complete entirely server-side, with no JavaScript firing, no user journey, and no attribution – just an order appearing in your backend. Josh walks through where “ChatGPT / not set” shows up in your unassigned traffic, why server-side webhooks are currently the only way to count agent-driven purchases, and what the GA4 migration taught us about not dragging old assumptions into new architectures. We also explore why Microsoft Clarity is ahead of Google on AI traffic dashboards, and why building the agentic data layer feels less like a migration and more like a construction project with no blueprints. All episodes on our website: www.ask-y.ai/knowledge-distillation-podcast Learn more about ASK-Y: www.ask-y.ai

    54 min
  7. 8# Sani Manić on Why the Web Isn’t Ready for AI Agents and How GA4 Analysts Are Ready

    FEB 6

    8# Sani Manić on Why the Web Isn’t Ready for AI Agents and How GA4 Analysts Are Ready

    “We have so much trash in terms of websites that AI is now supposed to ingest and give us something meaningful. It’s not going to work.” Sani Manić has spent 15+ years optimizing websites for speed, accessibility, and technical health. A contributor to Search Engine Journal and WordPress Core, he’s now turned that expertise toward a new challenge: making the web work for AI agents. In this episode, we explore the emerging data layer beneath the agentic web – where users never see your brand’s colors or copy because an AI assistant completed the purchase for them. Sani and Katrin discuss why clean semantic HTML is the new competitive advantage, why you should never trust a tool built by someone who couldn’t do the job without AI, and the real security exposure of frontier models. Sani hosts the NoHacks Podcast, now subtitled “Optimizing the Web for AI Agents” and is building an auditing tool that shows how different LLMs and agents see, navigate, and transact on your website. For analysts and e-commerce teams, this episode makes a compelling case that GA4’s event-driven architecture and the BigQuery skills analysts built during migration may be their best preparation for tracking the agentic web, even if nobody planned it that way. All episodes on our website: www.ask-y.ai/knowledge-distillation-podcast Learn more about ASK-Y: www.ask-y.ai

    53 min
  8. 7# Yaniv Makover & Avigad Oron on Building AI Before ChatGPT and Why Context Is Everything

    JAN 19

    7# Yaniv Makover & Avigad Oron on Building AI Before ChatGPT and Why Context Is Everything

    “My mom called me about this cool thing called an LLM. I was like, I’ve been working on this for 10 years.” Yaniv Makover, CEO of Anyword, joins Avigad Oron, Head of Technology for Ask-Y, Two AI engineers with combined 40 years of experience dissect their ChatGPT moment and what it means for the future of work. We discuss the architecture decisions behind enterprise AI-from RAG and ranking to security nightmares where “your data goes into a super complex distributed system with multiple models.” They debate whether transformers will reign forever and agree on one thing: AI is pushing everyone toward senior-level integrative skills while routine tasks disappear. All episodes on our website: www.ask-y.ai/knowledge-distillation-podcast Learn more about ASK-Y: www.ask-y.ai

    1h 13m
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About

Knowledge Distillation: The Rise of the AI Analyst Welcome to Knowledge Distillation – a series exploring how AI Analysts are transforming the future of data work. We look at practitioners becoming AI Analysts, founders building AI Analyst tools, VCs backing the AI Analyst wave, and market analysts mapping the trend. Each episode uncovers what it means to be an AI Analyst today – the workflows being reinvented, the skills analysts need now, and the promises AI is keeping or breaking. From prompt engineering to context management, we dive into the real conversations shaping this role. Let’s distill some knowledge. Because bots won’t win. AI Analysts will. Explore More: www.ask-y.ai

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