『Habit Machine: AI Product Management』のカバーアート

Habit Machine: AI Product Management

Habit Machine: AI Product Management

著者： Vladimir Dyachkov PhD
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AI changes everything. But human nature stays the same. Learn to build products that respect attention, reduce friction, and earn repetition. AI has turned product management upside down. Static interfaces are dying. Users now expect products that anticipate, adapt, and execute without asking. The old playbook — roadmaps, backlogs, stakeholder alignment — still exists. It's just no longer enough to win. This book is for product leaders who feel the shift. The author spent 20 years building at scale — AI products, apps for 180 million users. And he holds a PhD in behavioral economics.Vladimir Dyachkov PhD マネジメント マネジメント・リーダーシップ 経済学
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  • Your Gut Is Lying — The Product Audit That Saved 30% Churn in 30 Days | Habit Machine Podcast

    Your Gut Is Lying — The Product Audit That Saved 30% Churn in 30 Days | Habit Machine Podcast
    2026/08/04
    Episode 24: Your Gut Is Lying — The Product Audit That Saved 30% Churn in 30 Days | Habit Machine PodcastWhy Anecdotes Are Not Evidence, and the 4‑Layer Diagnostic Framework That Turns Data into Decisions Before You Bleed RunwayEpisode OverviewYou just inherited a live product. Users exist. But something feels off. Your gut says one thing; the engineers say another; angry customers say a third. This episode dismantles the collector's fallacy—gut feelings are not diagnosis, they are anecdotes wearing a confident coat. Two Product Managers introduce a systematic product audit that compresses months of learning into weeks, and they run it at three critical triggers: when you inherit a new product, when metrics start bleeding (retention drops, conversion stalls, churn rises), and before aggressive scaling. The conversation moves from strategy and unit economics (LTV/CAC, payback period, gross margin) to behavioral health (time-to-first-value, heatmaps, AI interaction logs), technical infrastructure (latency, vector index freshness, hallucination patterns), and audience/community signals (segment-specific LTV, support sentiment). The episode then builds a short/mid/long-term action pipeline—from patching performance leaks to strategic market bets—and closes with a real case study: a subscription product that cut first-month churn by 30% without changing pricing or features, simply by surfacing premium value through onboarding. An audit is not a report; it is a decision system. Define the goal, isolate the signal, and stop confusing activity with progress.What You Will LearnWhy gut feelings and angry customer anecdotes are not diagnosis—and how to replace them with a structured decision systemThe three triggers that demand an immediate product audit: inheriting a product, sudden metric bleeding, and pre‑scale readinessThe four layers of a real audit: strategy & unit economics, behavioral health & UX, technical & infrastructure, and audience & community signalsKey Takeaways"An audit is not a report. It is a decision system. Define the goal, isolate the signal. Aggregate metrics hide rot in specific segments—what looks green on average can be quietly dying in your highest‑value cohort. Diagnosis does not give you more opinions; it gives you clearer causality. The audit's leverage is not more data—it is a framework that turns data into decisions, not documents. If you score five or more on the readiness checklist, you produce decisions. Below three, you are just collecting data without a diagnostic framework."About the BookTitle: Habit Machine: AI Product ManagementSeries: AI and Human, Volume 1Author: Vladimir Dyachkov, PhDISBN: 978-83-8455-089-2Habit Machine is a practical playbook for Product Managers, founders, and builders who engineer products that change behavior, not just ship features.https://www.amazon.com/Habit-Machine-AI-Product-Management-ebook/dp/B0GYYP119XAbout the AuthorVladimir Dyachkov, PhD is a Product leader in AI with a PhD in Economics and two decades of experience building products people actually use.Connect with Vladimir DyachkovLinkedIn: linkedin.com/in/uxproductEmail: vladimiruso@gmail.comTelegram: t.me/vlrusoAI Care Products: ⁠⁠⁠aidevmd.com⁠⁠A2A Hub: ⁠itinai.comA2A Dubai Hub: ⁠⁠allahub.com⁠A2A A2H H2H Asia Hub: ⁠⁠⁠ha2ah.com⁠⁠A2A GitHub Repo: ⁠⁠⁠https://github.com/aihlp/itinai⁠
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    6 分
  • The Friction Tax — Why Every Extra Click Is a Confession of Laziness | Habit Machine Podcast

    The Friction Tax — Why Every Extra Click Is a Confession of Laziness | Habit Machine Podcast
    2026/07/28

    Episode 23: The Friction Tax — Why Every Extra Click Is a Confession of Laziness | Habit Machine Podcast

    How Feature Bloat, Captchas, and "Are You Sure?" Dialogs Are Stealing Your Users' Trust — and the 4-Step Audit to Restore Invisible Simplicity

    Episode Overview

    You survived the scaling chaos. But something else crept in—the product feels heavy. Menus everywhere. Options nobody uses. Friction is never a necessary evil; it is always a design failure. Two Product Managers dismantle the cognitive tax we pass to users because we didn't solve problems invisibly. Security is the team's obligation, never the user's—passkeys, magic links, and silent risk checks absorb complexity behind the scenes. The conversation exposes seven patterns of justified friction that are actually laziness: registration before value, configuration overload, interruptive monetization, opaque data collection, latency and decorative delays, confirmation overload, and homework onboarding. It then reveals the three illusions that keep us adding weight—"users asked for it," measuring shipping volume, and competitor panic—and offers four strategies to protect coherence: remove relentlessly, hide complexity until proven necessary, measure complexity as a metric, and build teams that are allowed to simplify. The episode closes with a quick subtraction audit to separate products that protect the simplicity edge from those paying the bloat penalty. Simplicity is not a feature. It is the discipline of absorbing complexity so the user never has to.

    What You Will Learn

    • Why every captcha, verification wall, and confirmation dialog is a tax on attention—and how to make security invisible
    • The seven patterns of "justified" friction that are actually design failures: registration before value, configuration overload, interruptive monetization, opaque data collection, latency and decorative delays, confirmation overload, and homework onboarding


    Key Takeaways

    "Simplicity is not a feature. It is the discipline of absorbing complexity so the user never has to. Every extra step, even a well‑intended one, multiplies interaction cost. The core job gets buried under our internal needs. Remove relentlessly. Hide until proven necessary. Measure complexity in every sprint. And build teams that are allowed to simplify—because courage to remove is harder than the ease to add."

    About the Book

    Title: Habit Machine: AI Product Management

    Series: AI and Human, Volume 1

    Author: Vladimir Dyachkov, PhD

    ISBN: 978-83-8455-089-2

    Habit Machine is a practical playbook for Product Managers, founders, and builders who engineer products that change behavior, not just ship features.

    About the Author

    Vladimir Dyachkov, PhD is a Product leader in AI with a PhD in Economics and two decades of experience building products people actually use.

    Connect with Vladimir Dyachkov

    • LinkedIn: linkedin.com/in/uxproduct
    • Email: vladimiruso@gmail.com
    • Telegram: t.me/vlruso

    Ready to Engineer Habits, Not Just Features?

    Grab your copy of Habit Machine: AI Product Management and replace growth hope with distribution architecture.

    ISBN: 978-83-8455-089-2

    Part of the AI and Human series.

    Subscribe to the Habit Machine Podcast for more on Behavioral Design, virality engineering, and removing the friction that kills habit.

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    Episode 23 preview — full episode available now on all podcast platforms.
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    5 分
  • Growth Is a Trap — The 5 Ways Scaling Destroys Your Product | Habit Machine Podcast

    Growth Is a Trap — The 5 Ways Scaling Destroys Your Product | Habit Machine Podcast
    2026/07/21
    Episode 22: Growth Is a Trap — The 5 Ways Scaling Destroys Your Product | Habit Machine PodcastWhy Surviving the Chaotic Middle Is the Only Test That Proves Your Success Was Real, and How to Scale Without Burning Everything DownEpisode OverviewYou found product-market fit. Users are flooding in. The team is euphoric. This episode is your cold shower. Growth is not a victory lap—it is a brutal stress test that exposes every fragile assumption and skipped process from the early days. Two Product Managers dissect the four predictable phases of product evolution and reveal why misreading your stage is how teams optimize for the wrong metrics and burn runway. The conversation moves from the search for the core job to active growth chaos, maturity optimization, and the stagnation nobody wants to admit. It then exposes the five killers that strike during the scaling phase: infrastructure cracking under load, retention decaying while acquisition rises, support collapsing under volume, core value dilution through feature bloat, and community quality degradation. The episode closes with a survival framework—clear ownership boundaries, documented decision frameworks, strict feature acceptance criteria, and the hard rule: if any critical metric dips below three, pause growth and fix the systems first. Complexity does not disappear when you ignore it. It compounds silently until it breaks everything.What You Will LearnWhy growth is not a victory lap—it's the test that reveals whether your success was real in the first placeThe four predictable phases: product-market fit, active growth, maturity, and stagnation/decline—and why misreading your stage kills runwayThe critical retention threshold: Day 30 stabilization above 40% before you even think about scaling reachThe five killers of active growth: infrastructure cracks, retention decay, support collapse, core value dilution, and community degradationWhy novelty attracts but habit retains—and how to build repeat-use triggers from day one, not bolt them on after the leak startsHow to deploy retrieval-augmented assistants to protect human agents from repetitive queries and keep support a frontline retention engineWhy more surface area means more cognitive load—and how to reject features that do not strengthen the core behaviorThe hard rule: pause growth if any critical metric dips below three—fix the systems first before scaling furtherWhy chaos was a feature at five people but a liability at fifty—and how to preserve speed through clarity, not hallway conversationsKey Takeaways"Scaling is not what happens after success. It is the test that reveals whether the success was real in the first place. Complexity does not disappear when you ignore it. It compounds silently until it breaks everything. If retention dips while acquisition climbs, you are buying attention, not building habit. Pause growth. Fix the systems. Then scale."About the BookTitle: Habit Machine: AI Product ManagementSeries: AI and Human, Volume 1Author: Vladimir Dyachkov, PhDISBN: 978-83-8455-089-2Habit Machine is a practical playbook for Product Managers, founders, and builders who engineer products that change behavior, not just ship features.About the AuthorVladimir Dyachkov, PhD is a Product leader in AI with a PhD in Economics and two decades of experience building products people actually use.Connect with Vladimir DyachkovLinkedIn: linkedin.com/in/uxproductEmail: vladimiruso@gmail.comTelegram: t.me/vlrusoReady to Engineer Habits, Not Just Features?Grab your copy of Habit Machine: AI Product Management and replace growth hope with distribution architecture.ISBN: 978-83-8455-089-2Part of the AI and Human series.Subscribe to the Habit Machine Podcast for more on Behavioral Design, virality engineering, and removing the friction that kills habit. Your browser does not support the audio element.Episode 22 preview — full episode available now on all podcast platforms.
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    6 分
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