Explore every episode of the podcast Habit Machine: AI Product Management
| Title | Pub. Date | Duration | |
|---|---|---|---|
| Learn Over Build: Master The Lean Validation Loop Before You Write Another Line of Code — Deep Dive Episode 30 | 14 sept. 2026 | 00:49:30 | |
Episode 30: The Lean Validation Loop: From Ideal Concept to Market Signal | Habit Machine Podcast The most expensive mistake in product development is building a solution before validating the problem. The Lean Validation Loop flips that script—transforming an ideal concept into a market signal through a disciplined Build‑Measure‑Learn cycle that prioritizes learning over shipping. In this episode, we break down the MVP mindset (it’s not about the product, it’s about the hypothesis), how to build experiments instead of features, how to measure behavior instead of opinions, and how to decide whether to pivot, iterate, or scale. We also introduce a practical filter for translating an ideal vision into a testable MVP, and a framework for knowing when you’ve earned the right to build beyond the experiment. If you’re still shipping on intuition, this loop is your sanity check. Episode Overview Too many teams treat MVP as a half‑baked product rather than a learning vehicle. This episode redefines the Lean Validation Loop as a continuous system that runs parallel to your vision, not as a one‑time gate. We walk through the Build‑Measure‑Learn cycle in practice: how to frame falsifiable hypotheses, how to choose the lightest possible experiment, how to track behavioral signals instead of vanity metrics or survey responses, and how to use the learning to make a clear decision—pivot, iterate, or scale. The practical filter for translating an ideal concept into an MVP helps you avoid the trap of overbuilding before the market has spoken. Finally, we discuss when to evolve: the signals that tell you your experiment has earned the right to become a real product, and when it’s time to walk away. What You Will Learn
Key Takeaways “The Lean Validation Loop isn’t a phase—it’s a permanent engine. The moment you stop validating is the moment your product starts drifting on assumptions. Build tests, not features. Measure what users do, not what they say. Learn with enough clarity to make a binary decision: persevere, pivot, or kill. And remember, the right to build is earned by the signal your last experiment produced, not by how elegant your vision deck looks.” About the Book Title: Habit Machine: AI Product Management Habit Machine is a practical playbook for Product Managers, founders, and builders who engineer products that change behavior, not just ship features. Connect with Vladimir Dyachkov
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| Design Thinking: The Discipline of Problem-First Creation Saves Products —Deep Dive Episode 29 | 07 sept. 2026 | 00:31:25 | |
Episode 29: Design Thinking: The Discipline of Problem-First Creation | Habit Machine Podcast This episode installs Problem-First Creation as the core discipline that prevents product teams from building beautiful solutions to the wrong problems. Design Thinking is not a workshop exercise—it’s an expand‑converge rhythm that moves from empathy to a value‑driven backlog without getting stuck in research theater. We walk through the five stages: Empathize to map hidden friction, Define to isolate the real job, Ideate to search for the ideal state, Prototype to make the hypothesis tangible, and Test to measure actual behavioral response. Most importantly, we tackle the trap that kills Design Thinking—research without shipping—and show how to output a backlog of decisions, not just sticky notes. Episode Overview Too many teams treat Design Thinking as a pre‑development phase that produces empathy maps no one uses. This episode reframes it as an operating rhythm that drives the entire product creation system. The expand‑converge dynamic is the engine: divergent exploration to gather rich signals, then ruthless convergence to isolate the problem worth solving. Each of the five stages is dissected with practical lenses: how to uncover friction users can’t articulate, how to define a job statement that makes ideation targeted, how to prototype at the right fidelity for behavioral feedback, and how to test not for opinions but for measurable shifts in user behavior. The output is not a report—it’s a value‑driven backlog that directly feeds the Build‑Validate‑Ship Loop. And the trap? Research that never leaves the lab. We close with the rule: every round of thinking must end with a decision to ship something testable, or it’s just procrastination in designer clothes. What You Will Learn
Key Takeaways “Design Thinking without the discipline of Problem‑First Creation becomes design theater. You can empathy‑map your way into oblivion if the loop doesn’t close with a behavioral test. The expand‑converge rhythm is the heartbeat: diverge to capture the richness of human experience, converge to make a bet you can validate. Prototypes are not artifacts—they are hypotheses made tangible. And the ultimate output is not insight reports; it’s a backlog where every item is tied to a real human job. If your research doesn’t change what you ship next week, you’re performing research, not doing it.” About the Book Title: Habit Machine: AI Product Management Habit Machine is a practical playbook for Product Managers, founders, and builders who engineer products that change behavior, not just ship features. Connect with Vladimir Dyachkov
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| How to Build The Experience Stack That Turns a UI Into a Habit — Episode 27 | 02 sept. 2026 | 00:34:12 | |
Episode 27: The Experience Stack: From Interface to Identity | Habit Machine Podcast This episode unpacks The Experience Stack—the five layers that carry a product from surface-level UI all the way to a behavioral identity shift. If you’ve ever wondered why great-looking interfaces still fail to change behavior, the answer lies in the missing layers. We break down Layer 1 & 2 (UI and Usability), Layer 3 & 4 (UX and CX), and the often-overlooked Layer 5: HX—the Behavioral Shift where the product becomes part of the user’s self-concept. Then we reveal the 4‑step process for “Engineering the Illusion of Effort”: define the core job, collapse decision trees, remove pre‑value friction, and lock the habit loop so the product feels inevitable, not effortful. Episode Overview Most product teams stop at the surface—pixel-perfect UI and smooth usability—and wonder why retention curves bend downward. This episode introduces The Experience Stack as a diagnostic and design framework. The first two layers handle the interface; the next two manage the holistic journey and customer experience. But the real moat lives at Layer 5: HX, where the product doesn’t just serve a need—it reshapes how the user sees themselves. We then walk through the four-step process for Engineering the Illusion of Effort, showing how to collapse complexity into automatic actions that feel native. It’s not about removing work; it’s about designing so that the work disappears. What You Will Learn
Key Takeaways “The Experience Stack shows that interface is entry, but identity is retention. If you stop at usability, you’re just making a pretty commodity. Layer 5—HX—is where the product becomes a habit that the user defends, because it’s part of who they are. Engineering the illusion of effort doesn’t mean tricking users; it means removing everything that makes the right action feel like work. Collapse the decision tree, kill pre-value friction, and the habit loop locks itself.” About the Book Title: Habit Machine: AI Product Management Habit Machine is a practical playbook for Product Managers, founders, and builders who engineer products that change behavior, not just ship features. Connect with Vladimir Dyachkov
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| Stop Building Blind: The Build-Validate-Ship Loop That Turns Ideas Into Products — Deep Dive Episode 28 | 24 août 2026 | 00:41:52 | |
Episode 28: The Build-Validate-Ship Loop: An Operating System for Product Creation | Habit Machine Podcast Discover The Build-Validate-Ship Loop—the operating system that replaces chaotic product development with a single, repeatable rhythm. Most teams treat discovery, validation, and delivery as separate disciplines. They aren’t. They are phases of the same loop, and when you run them as a connected system, you stop building features nobody wants and start shipping outcomes that stick. This episode breaks down Phase 1 (Discovery with Design Thinking), Phase 2 (Validation with Lean Startup), and Phase 3 (Delivery with Agile), then shows how to operate the whole loop as a rhythm, not a ritual. If you’re tired of wasted sprints and feature graveyards, this is the mental model you need. Episode Overview Product creation is not a linear assembly line—it’s a loop that must spin fast and stay connected. Too many teams run Discovery as a research project, Validation as a separate experiment, and Delivery as a feature factory, never linking them back together. This episode integrates the three phases into one operating system: Discovery defines the problem space with deep empathy and framing; Validation tests the riskiest assumptions with the lightest possible artifacts; Delivery ships the increment that actually moves the metric. The conversation then zooms out to show how to operate the loop—keeping the rhythm short, the feedback tight, and the team’s focus on learning velocity rather than output volume. Rhythm over ritual means the loop becomes the way the team breathes, not a checkbox process. What You Will Learn
Key Takeaways “The Build-Validate-Ship Loop is not a methodology cocktail—it’s an operating system. Discovery without rapid validation is a museum of assumptions. Validation without shipping is a graveyard of experiments. And delivery without discovery is a feature factory that builds things nobody needs. The magic happens when you collapse the handoffs and run the whole loop in tight cycles. Rhythm over ritual: if the loop feels like a ceremony, you’re doing it wrong. It should feel like the heartbeat of the product.” About the Book Title: Habit Machine: AI Product Management Habit Machine is a practical playbook for Product Managers, founders, and builders who engineer products that change behavior, not just ship features. Connect with Vladimir Dyachkov
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| The Simplicity Dividend: How Simple Products Build Habits While Complex Ones Disappear — Deep Dive Episode 26 | 18 août 2026 | 00:34:09 | |
Episode 26: Simple Products: Engineering the Modern Magic | Habit Machine Podcast Simple Products aren’t minimalist for the sake of aesthetics—they’re engineered to eliminate the cognitive tax that starves habit formation. This episode reveals why complexity is the silent killer of user behavior, and how the most habit-forming products master the art of doing less. We dissect the four principles of frictionless design: making a product obvious without instructions, mapping one action to one outcome, fitting into existing habits, and becoming the default status. Then we introduce the Simplicity Dividend—a diagnostic that helps product teams measure whether their product is fighting the user’s brain or working with it. If your product needs a manual, you’ve already lost the habit war. Episode Overview Modern products often crumble under the weight of feature bloat, assuming that more options equal more value. This episode dismantles that assumption. We explore the cognitive tax of complexity—how every extra decision point, ambiguous flow, or unfamiliar interaction forces the user to spend mental energy that could have been invested in forming a new habit. The four principles of frictionless design are broken down with concrete examples, showing how great products become invisible tools that users adopt without thinking. Finally, we walk through the Simplicity Dividend diagnostic: a set of questions that reveal whether your product’s design is accelerating habit formation or silently undermining it. What You Will Learn
Key Takeaways “The real magic of simple products is that they remove the user’s need to think about the tool, freeing cognitive capacity for the habit itself. Complexity starves habit formation because every unnecessary decision is a withdrawal from a limited mental budget. If your product requires instructions, it’s already failing the first principle. The Simplicity Dividend isn’t about stripping features—it’s about designing so that the right action becomes the only obvious one.” About the Book Title: Habit Machine: AI Product Management Habit Machine is a practical playbook for Product Managers, founders, and builders who engineer products that change behavior, not just ship features. Connect with Vladimir Dyachkov
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| The Signal-to-Standard Pipeline: Why Some Products Change Behavior While Others Disappear — Deep Dive Episode 25 | 11 août 2026 | 00:34:38 | |
Episode 25: Why Some Products Change Behavior While Others Disappear | Habit Machine Podcast The real moat isn’t features. It’s behavioral design. In this episode, we break down the Signal-to-Standard Pipeline—a four‑stage framework that turns a weak user signal into an institutional habit. Most products capture a signal and then die before it scales. Stage 1 isolates the weak signal from noise. Stage 2 engineers the interaction shift that makes the new behavior feel effortless. Stage 3 locks the behavior into a habit loop. Stage 4 embeds the standard into the organization itself—making the behavior stick even when the original context disappears. If you want to build products that change behavior, not just ship features, this is the blueprint. Episode Overview Why do some products rewire daily routines while others vanish the moment the novelty wears off? This episode dismantles the myth that features create loyalty and reveals the Signal-to-Standard Pipeline—a repeatable pathway from fragile early signal to durable institutional lock. We examine each stage with real examples: how a tiny behavioral signal is spotted and protected, how the interaction is redesigned to remove cognitive friction, how the habit loop is reinforced through triggers and rewards, and finally how the behavior becomes “the way we do things here.” The discussion also exposes why most signals die before they scale—and how to avoid that trap by treating behavioral design as the product itself. What You Will Learn
Key Takeaways “A product that changes behavior doesn’t just add a feature. It rewires the context. The Signal-to-Standard Pipeline shows that the real moat isn’t what the product does—it’s what the user becomes because of it. Stage 4 is where 90% of products fail: you can’t just design a habit loop inside the app; you have to embed the new behavior into the team’s rituals, metrics, and institutional memory. If the standard disappears when the champion leaves, you never had a moat—you had a demo.” About the Book Title: Habit Machine: AI Product Management Habit Machine is a practical playbook for Product Managers, founders, and builders who engineer products that change behavior, not just ship features. Connect with Vladimir Dyachkov
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| Your Gut Is Lying — The Product Audit That Saved 30% Churn in 30 Days | Habit Machine Podcast | 04 août 2026 | 00:05:36 | |
Episode 24: Your Gut Is Lying — The Product Audit That Saved 30% Churn in 30 Days | Habit Machine Podcast Why Anecdotes Are Not Evidence, and the 4‑Layer Diagnostic Framework That Turns Data into Decisions Before You Bleed Runway Episode Overview You 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 Learn
Key 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 Book Title: Habit Machine: AI Product Management Series: AI and Human, Volume 1 Author: Vladimir Dyachkov, PhD Habit 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/B0GYYP119X 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
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| The Friction Tax — Why Every Extra Click Is a Confession of Laziness | Habit Machine Podcast | 28 juil. 2026 | 00:05:24 | |
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
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
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and replace growth hope with distribution architecture. 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. Your browser does not support the audio element. Episode 23 preview — full episode available now on all podcast platforms. | |||
| Growth Is a Trap — The 5 Ways Scaling Destroys Your Product | Habit Machine Podcast | 21 juil. 2026 | 00:05:50 | |
Episode 22: Growth Is a Trap — The 5 Ways Scaling Destroys Your Product | Habit Machine Podcast Why Surviving the Chaotic Middle Is the Only Test That Proves Your Success Was Real, and How to Scale Without Burning Everything Down Episode Overview You 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 Learn
Key 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 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
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and replace growth hope with distribution architecture. 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. Your browser does not support the audio element.Episode 22 preview — full episode available now on all podcast platforms. | |||
| The Normality Illusion & Institutional Lock-In | Habit Machine Podcast | 14 juil. 2026 | 00:05:19 | |
Episode 21: The Normality Illusion & Institutional Lock-In | Habit Machine Podcast Why Growth Without Pattern Stabilization Is Just Expensive Noise, and How to Engineer Behavioral Normality Before It's Too Late Episode Overview Downloads climb. Daily active users look healthy. Most teams declare victory and scale. This episode dismantles that trap. Normality is not a finish line—it's when the behavior reproduces itself without you pushing it. Two Product Managers dissect why retention without pattern specificity is a vanity metric, and why institutional analysis asks a fundamentally different question: what pattern of behavior emerged from your signal, how stable is it across contexts, and how does it interact with other routines in a user's life? The conversation moves from surface metrics to the five real signals of normality—active user intensity, frequent usage cadence, ongoing economic behavior, organic spread, and pattern stability. It then exposes the false signals that trick teams: likes, views, downloads, and hype that fades fast. The episode closes with a five-point diagnostic that separates products that have achieved behavioral lock-in from those pouring users into a leaky bucket. Normality is not permanent. Once a pattern becomes routine, the challenge shifts from formation to defense. Competitors send counter signals. The environment changes. Your product succeeds not by becoming permanent, but by remaining adaptive within a changing informational environment. What You Will Learn
Key Takeaways "Habits compound. Hype decays. Build for the former. Normality is not a finish line—once a pattern becomes routine, the challenge shifts from formation to defense. Competitors send counter signals. The environment changes. Your product succeeds not by becoming permanent, but by remaining adaptive." 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
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and replace growth hope with distribution architecture. 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. | |||
| The Hidden "Friction Tax" That Kills 90% of Habits Before They Start | 07 juil. 2026 | 00:05:19 | |
Episode 21: The Next One | Habit Machine Podcast Why Normality Is Engineered, Not Hoped For, and How to Know When Your Product Has Actually Become a Habit Episode Overview Downloads climb. Daily active users look healthy. But is that growth real, or just expensive noise? This episode kills the myth that retention metrics tell the full story and reveals the institutional framework that separates products that fade from those that become normal. The conversation begins where virality ends—pattern stabilization. Five signals separate genuine behavioral lock-in from vanity metrics: high active user intensity, frequent usage cadence, ongoing economic behavior, organic spread, and pattern stability across contexts. The episode then dismantles the false signals that trick teams—likes, views, downloads—and provides a five-point diagnostic that cuts through the noise. The episode closes with a truth: normality is not a finish line. Once a pattern becomes routine, the challenge shifts from formation to defense. Competitors send counter signals. The environment changes. Your product succeeds not by becoming permanent, but by remaining adaptive within a changing informational environment. What You Will Learn
Key Takeaways "Growth without pattern stabilization is just expensive noise. Habits compound. Hype decays. Build for the former. Normality is not a finish line—once a pattern becomes routine, the challenge shifts from formation to defense. Your product succeeds not by becoming permanent, but by remaining adaptive within a changing informational environment." 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
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and replace growth hope with distribution architecture. Habit Machine AI Product Management https://www.amazon.com/Habit-Machine-AI-Product-Management-ebook/dp/B0GYYP119X 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. | |||
| How Products Become Invisible Infrastructure That Society Can’t Unthink | 30 juin 2026 | 00:05:32 | |
Episode 18: The Institutional Layer | Habit Machine Podcast Episode 18: The Institutional Layer | Habit Machine Podcast How Products Become Invisible Infrastructure That Society Can’t Unthink Episode Overview The highest success is not being a tool users choose—it is becoming the environment they operate within without a second thought. In this episode, two Product Managers dissect the institutional layer: the sequence that turns a novel signal into a social default, why the same signal can spawn unintended patterns, and how to map the spectrum of behavioral responses instead of just the target. The conversation redefines the product manager as an institutional engineer who measures pattern formation, not feature adoption, and reveals the four traps that turn a promising signal into a costly institutional failure. The ultimate moat is not code; it is making your solution feel so inevitable that switching away feels like breaking gravity. What You Will Learn
Key Takeaways "Products that become norms do not just offer a better solution. They reduce cognitive load below the threshold of alternatives. The moat that lasts is not code—it is habit, pattern maintenance, and making your solution feel so inevitable that switching away feels like breaking gravity." 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
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and learn to build the institutional layer that outlasts every feature war. ISBN: 978-83-8455-089-2 Part of the AI and Human series. Subscribe to the Habit Machine Podcast for more on Behavioral Design, institutional cartography, and the patterns that turn products into the environment. | |||
| Why Relevance Beats Innovation, and How to Map Your Product Signal to the Actual Human Need | 23 juin 2026 | 00:05:38 | |
Episode 17: Need-Signal Alignment | Habit Machine Podcast Why Relevance Beats Innovation, and How to Map Your Product Signal to the Actual Human Need Episode Overview A sharp signal that misses the real human motivation is just noise. This episode builds on the behavioral proposition of a launch by aligning it with the hierarchy of needs that actually drives user behavior—from urgent physiological relief to long-term meaning. Two Product Managers climb the pyramid layer by layer, showing why the most powerful signals reduce explanation to instinct. The conversation delivers five concrete rules for need-signal alignment and a litmus test: if your message doesn't resonate in a low-fidelity prototype, it will never scale. What You Will Learn
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
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and align your signal with the need that converts curiosity into habit. ISBN: 978-83-8455-089-2 Part of the AI and Human series. Subscribe to the Habit Machine Podcast for more on Behavioral Design, signal engineering, and the needs that make products inevitable. | |||
| The Information Signal: How a Product Rewires Behavior | 16 juin 2026 | 00:05:09 | |
Episode 16: The Signal That Rewires Habits | Habit Machine Podcast Episode 16: The Signal That Rewires Habits | Habit Machine Podcast Why a Launch Is a Behavioral Proposition, Not a Marketing Campaign Episode Overview Most products don't fail because engineering was slow—they fail because the signal never lands. In this episode, two Product Managers redefine the relationship between product and market. A launch is not a press release or a burst of ads. It is an information signal that must rewire a routine by promising less work, fewer decisions, and instant cognitive relief. We map the three paths a product can take—capturing the default, fading into noise, or mutating into an unexpected institution—and break down the three psychological thresholds a signal must pass to even begin the journey. The episode closes by distinguishing a slogan that sells a feature from a signal that sells a new behavioral contract, and teases the next critical layer: Need-Signal Alignment. What You Will Learn
Key Takeaways "A slogan sells a feature. A signal sells a new routine. When your positioning focuses on what users stop doing instead of what they start doing, adoption accelerates. The goal is not to sound innovative—it is to sound inevitable." Coming Next Episode: Need-Signal Alignment—why curiosity must become habit, and how to map your value proposition to actual human motivation. 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
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and learn to send signals that become defaults, not noise. ISBN: 978-83-8455-089-2 Part of the AI and Human series. Subscribe to the Habit Machine Podcast for more on Behavioral Design, market signals, and the systems that turn curiosity into habit. | |||
| Behavioral Intelligence: The Art of Customer Research | 09 juin 2026 | 00:05:44 | |
Episode 15: The Research That Ships | Habit Machine Podcast Episode 15: The Research That Ships | Habit Machine Podcast Why Users Can’t Tell You What to Build, and How Jobs to Be Done, Behavioral Personas, and Hybrid Journey Maps Reveal What They Actually Need Episode Overview Asking users what they want is the fastest route to building features nobody needs. This episode dismantles the polite fiction of feature-request research and replaces it with a rigorous, behavioral discipline. Two Product Managers walk through Jobs to Be Done that account for AI-era autonomy, personas grounded in cognitive load rather than demographics, journey maps that track emotional peaks and AI trust thresholds, and pain-and-gain analysis that connects retrieval quality directly to user anxiety. The output is not a research report—it is a testable hypothesis and a vibe-coded prototype within days. What You Will Learn
Key Takeaways "Research is not a phase you complete before development. It is a continuous loop that informs every sprint. If your research hasn’t produced a clear behavioral hypothesis and a testable prototype, you haven’t finished the job. You’ve just gathered opinions. And the market pays for outcomes, not opinions." 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
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and turn user research into a prototype, not a report. ISBN: 978-83-8455-089-2 Part of the AI and Human series. Subscribe to the Habit Machine Podcast for more on Behavioral Design, Jobs to Be Done, and the research that actually ships. | |||
| Why Artificial Intelligence Is the Infrastructure Every Modern PM Must Conduct | 02 juin 2026 | 00:05:24 | |
Episode 14: AI-Native Product Infrastructure | Habit Machine Podcast Why Artificial Intelligence Is Not a Feature Toggle—It Is the Infrastructure Every Modern PM Must Conduct Episode Overview Treating AI as a chatbot you bolt on is career suicide. It is infrastructure, not a gadget—like electricity, not a toaster. This episode maps the four capabilities that separate the AI-native product leader from the obsolete backlog administrator. Two Product Managers walk through conversational UX design, retrieval-augmented generation architecture, vibe coding as a validation weapon, and agent orchestration as the new choreography skill. The episode closes with a unified diagnostic: eight questions that reveal whether you are conducting infrastructure or just surviving a backlog. What You Will Learn
Diagnostic rule: Score below four out of eight, step back. Clarify your stakeholder map. Get evidence on the table. Rebuild your decision architecture from scratch. 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
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and learn to conduct the infrastructure, not just toggle the feature. ISBN: 978-83-8455-089-2 Part of the AI and Human series. Subscribe to the Habit Machine Podcast for more on AI-native product strategy, behavioral design, and the skills that survive the infrastructure shift. | |||
| Why the Backlog Administrator Is Dead, and the Equilibrium Engineer Is the New Survival Skill | 26 mai 2026 | 00:05:23 | |
Episode 12: The Modern Product Leader | Habit Machine Podcast Episode 12: The Modern Product Leader | Habit Machine Podcast Why the Backlog Administrator Is Dead, and the Equilibrium Engineer Is the New Survival Skill Episode Overview The most fragile component of any product is often the person leading it. The title hasn't changed, but the job has mutated into something unrecognizable. Two Product Managers dismantle the outdated backlog-administrator identity and map the four pillars of the modern product leader: behavioral designer, systems thinker, evidence-driven executor, and AI-native orchestrator. The conversation then shifts by company stage—startup truth-seeker, scale-up alignment navigator, mature product steward, and turnaround surgeon—each with distinct failure patterns and leverage points. The episode closes with a clear mandate: literacy across all four pillars is no longer optional. What You Will Learn
Key Takeaways "The modern product leader architects the space where business viability, technical feasibility, and human desirability find equilibrium. You don't need to be the deepest expert in all four pillars. You need enough literacy to make high-quality trade-offs across them. Literacy compounds." 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
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and build the four pillars before the market demands them. ISBN: 978-83-8455-089-2 Part of the AI and Human series. Subscribe to the Habit Machine Podcast for more on Behavioral Design, product leadership, and the skills that survive an AI-driven market. | |||
| Why Great Products Self-Destruct on the Launchpad—and the Six Predictable Patterns You Can Defuse Before They Trigger | 19 mai 2026 | 00:05:28 | |
Episode 11: The Six Launch Killers | Habit Machine Podcast Why Great Products Self-Destruct on the Launchpad—and the Six Predictable Patterns You Can Defuse Before They Trigger Episode Overview A brilliant competitive moat means nothing if the launch itself self-destructs. Launch day is often treated as a finish line instead of a stress test for behavioral assumptions. In this episode, two Product Managers dissect the six predictable patterns that cause even well-engineered products to vanish after the party: the Idea Trap, the Behavior Gap, deadly timing, the Retention Blind Spot, the Paid Illusion, and the Hype Hangover. Each pattern is traced to a specific failure in validating demand, reducing routine friction, reading market readiness, or building retention mechanics that survive the initial spike. The conversation closes with a pre-launch risk diagnostic—six rapid-fire checks that force teams to confront whether genuine habit exists before scaling. The core message: catastrophic launches are always optional. What You Will Learn
Pre-Launch Diagnostic Checklist
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
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and learn to defuse the six launch killers before they strike. ISBN: 978-83-8455-089-2 Part of the AI and Human series. For Product Managers who build for behavior, not just output. Subscribe to the Habit Machine Podcast for more on Behavioral Design, launch readiness, and the systems that make habits stick. | |||
| Why Features No Longer Protect You, and How Behavioral Defaults, Data Gravity, and Ecosystem Lock-In Build Unbeatable Products | 12 mai 2026 | 00:05:14 | |
Episode 10: The New Moat | Habit Machine Podcast Why Features No Longer Protect You, and How Behavioral Defaults, Data Gravity, and Ecosystem Lock-In Build Unbeatable Products Episode Overview The old playbook—panic, add features, hope a better spec sheet wins—is dead. When competitors with equal capabilities emerge overnight, the winners aren't those who ship first but those who lock a new routine into a habit before anyone else. This episode redefines competitive advantage around speed to behavioral capture, data that compounds with every interaction, attention engineering that shapes behavior instead of just analyzing it, and ecosystem gravity that makes leaving feel irrational. Two Product Managers dismantle the myth of feature parity and reveal the four shifts that turn a product from a replaceable alternative into an infrastructure people can't imagine abandoning. The conversation closes with four strategic mandates: design for institutional impact, treat AI as a behavior-shaping layer, own the proprietary data loop, and build connected leverage across systems—not isolated excellence. What You Will Learn
Coming Next Episode: We flip to the dark side—the six launch killers that sink great products before they ever scale. 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
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and build a moat no competitor can copy. ISBN: 978-83-8455-089-2 Part of the AI and Human series. Subscribe to the Habit Machine Podcast for more on Behavioral Design, competitive moats, and the systems that turn products into defaults. | |||
| How Artificial Intelligence Accelerates Insight Without Replacing Product Judgment | 05 mai 2026 | 00:04:59 | |
Episode 9: The AI Multiplier | Habit Machine Podcast How Artificial Intelligence Accelerates Insight Without Replacing Product Judgment Episode Overview Raw data is slow to interpret, but throwing AI at it without discipline just adds noise dressed as wisdom. In this episode, two Product Managers reframe artificial intelligence not as an autopilot but as a multiplier—one that speeds the path from signal to decision across five application layers. The conversation cuts through the hype to reveal exactly where AI compresses research, ideation, personalization, development, and growth work, and where human judgment must guard the compass. The real skill is knowing what to delegate and what to protect. What You Will Learn
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
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and learn where to let AI multiply your insight without losing your compass. ISBN: 978-83-8455-089-2 Part of the AI and Human series. Subscribe to the Habit Machine Podcast for more on Behavioral Design, evidence-driven delivery, and the systems that turn AI into a genuine multiplier. | |||
| How Behavioral Telemetry Sharpens Judgment, Replaces Vanity Metrics, and Closes the Loop Between Shipping and Learning | 29 avr. 2026 | 00:05:28 | |
Episode 8: The Evidence Engine | Habit Machine Podcast How Behavioral Telemetry Sharpens Judgment, Replaces Vanity Metrics, and Closes the Loop Between Shipping and Learning Episode Overview Execution rhythm means nothing if it's directed by the loudest opinion in the room. This episode introduces the Evidence Engine, the nervous system that connects user intent to engineering execution. Two Product Managers walk through how data acts as a compass that sharpens human judgment rather than replacing it. From behavioral telemetry that reveals hesitation no interview can surface, to staged rollouts that tie every roadmap item to a specific metric, the conversation shows how evidence precedes investment, why behavior outranks opinion, and what hard stop signals demand a rollback. The episode closes by acknowledging that data tells you what is happening—but to understand why, you need something messier: actual customer research. What You Will Learn
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
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and let evidence drive your next increment. ISBN: 978-83-8455-089-2 Part of the AI and Human series. Subscribe to the Habit Machine Podcast for more on Behavioral Design, evidence-driven delivery, and the systems that turn data into durable habits. | |||
| Why Marketing Starts Before Code and Runs in Parallel with Design Thinking, Validation, and Delivery | 28 avr. 2026 | 00:05:14 | |
Episode 7: The Embedded Marketing Engine | Habit Machine Podcast Episode 7: The Embedded Marketing Engine | Habit Machine Podcast Why Marketing Starts Before Code and Runs in Parallel with Design Thinking, Validation, and Delivery Episode Overview The old model is dead: build first, then hand to marketing for clever copy. In this episode, two Product Managers reveal marketing as an embedded system—one that shapes positioning during Discovery, tests demand during Validation, teaches new behaviors during Delivery, and accelerates organic growth only after retention proves real. The core lesson: marketing that begins after development starves the product of the very signal it needs to survive. What You Will Learn
Key Takeaways "Acquisition opens the door. Retention keeps it open. Marketing is not a department at the end of the hallway—it is the behavioral system connecting value, adoption, and distribution from day zero." 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
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and embed marketing where it belongs—before a single line of code. ISBN: 978-83-8455-089-2 Part of the AI and Human series. Subscribe to the Habit Machine Podcast for more on Behavioral Design, embedded marketing, and the systems that turn products into defaults. | |||
| How Two-Week Learning Loops Turn Validated Insight Into Shipped Value Without Sacrificing Clarity | 27 avr. 2026 | 00:05:04 | |
Episode 6: The Agile Execution Engine | Habit Machine Podcast Episode 6: The Agile Execution Engine | Habit Machine Podcast How Two-Week Learning Loops Turn Validated Insight Into Shipped Value Without Sacrificing Clarity Episode Overview Validated concepts die on shelves when delivery becomes a black box. This episode confronts the waterfall reflex—massive requirements, six-month builds, and the inevitable ghost product that no longer fits the market. Two Product Managers reveal the Agile Execution Engine, not as a set of empty ceremonies but as a compressed management rhythm that forces learning into two-week cycles. We walk through the four ceremonies that actually work: Sprint Planning that negotiates reality, Sprint Execution that replaces micromanagement with autonomy, Sprint Review that evaluates behavioral outcomes instead of completed tickets, and Sprint Retrospective that treats process improvement as operational hygiene. The deeper shift is organizational architecture—teams that build with transparency, autonomy, and outcome ownership produce products that feel the same clarity. With examples like Linear, we show how mature agility compounds speed without sacrificing direction. If your sprints feel like theater, this episode will reset the engine. What You Will Learn
Key Takeaways "Speed without direction accelerates waste. The Agile Execution Engine directs speed with evidence. Ceremonies are just guardrails to keep learning in public, not a cage to trap creative work. A shipped feature nobody uses is technical debt, not progress." 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 want to engineer products that change behavior, not just ship features. About the Author Vladimir Dyachkov, PhD is a Product leader in AI. He holds a PhD in Economics and has spent two decades building products that people actually use, from AI-driven medical products to platforms reaching 180 million monthly users. Connect with Vladimir Dyachkov
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and start applying the Behavioral Adoption Checklist. ISBN: 978-83-8455-089-2 Part of the AI and Human series. For Product Managers who build for behavior, not just output. Subscribe to the Habit Machine Podcast for more on Behavioral Design, Lean Validation, and the Agile rhythms that turn insight into habit. | |||
| How Smart Validation Lowers Uncertainty, Not Standards, Using Concierge Tests, Fake Doors, and the Build-Measure-Learn Rhythm | 26 avr. 2026 | 00:05:02 | |
Episode 5: The Lean Validation Loop | Habit Machine Podcast How Smart Validation Lowers Uncertainty, Not Standards, Using Concierge Tests, Fake Doors, and the Build-Measure-Learn Rhythm Episode Overview After Design Thinking, the backlog is beautiful, compelling, and dangerously expensive. This episode confronts the collision of vision with reality—budget, technical debt, market uncertainty—and reveals that collision as a feature, not a crisis. Two Product Managers dismantle the biggest myth about Minimum Viable Products and walk through the Lean Validation Loop that separates teams who learn fast from those who scale prematurely. The central lesson: you earn the right to scale through evidence. Trust and habit must be proven before architecture is built. What You Will Learn
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 want to engineer products that change behavior, not just ship features. Grounded in behavioral economics, AI-native product strategy, and two decades of real-world experience, this book offers standalone diagnostics you can use the moment retention drops or your roadmap feels like a prayer. About the Author Vladimir Dyachkov, PhD is a Product leader in AI with experience in team management and aligning products with business objectives. He holds a PhD in Economics with a focus on how information influences behavior, and has spent two decades building products that people actually use. His background includes leading AI projects based on World Health Organization data, launching seven AI-driven digital medical products, managing product portfolios reaching 180 million monthly users, and integrating payment systems that generated over one hundred million dollars in profit. Vladimir specializes in AI Product Management, Behavioral Design, Agile Product Development, and Growth and Monetization strategy across Business to Consumer, Business to Business, and Business to Government contexts. Connect with Vladimir Dyachkov
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and start applying the Behavioral Adoption Checklist to your next product initiative. ISBN: 978-83-8455-089-2 Part of the AI and Human series. For Product Managers who build for behavior, not just output. Subscribe to the Habit Machine Podcast for more conversations on Behavioral Design, the Lean Validation Loop, and the methods that lower uncertainty without lowering your standards. | |||
| How Design Thinking Shapes the Architecture of Behavior, Not Just the Visual Layer | 25 avr. 2026 | 00:05:04 | |
Episode 4: Problem-First Creation | Habit Machine Podcast How Design Thinking Shapes the Architecture of Behavior, Not Just the Visual Layer Episode Overview Design Thinking carries a bad reputation in product circles—often dismissed as a decorative ritual that burns calendars and ships nothing. In this episode, two Product Managers dismantle that fallacy. The real discipline of Design Thinking is not about sticky notes or visual polish. It is the architecture of behavior: mapping service logic, interaction flows, and the invisible rules that make a product feel effortless. What You Will Learn
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 want to engineer products that change behavior, not just ship features. Grounded in behavioral economics, AI-native product strategy, and two decades of real-world experience, this book offers standalone diagnostics you can use the moment retention drops or your roadmap feels like a prayer. About the Author Vladimir Dyachkov, PhD is a Product leader in AI with experience in team management and aligning products with business objectives. He holds a PhD in Economics with a focus on how information influences behavior, and has spent two decades building products that people actually use. His background includes leading AI projects based on World Health Organization data, launching seven AI-driven digital medical products, managing product portfolios reaching 180 million monthly users, and integrating payment systems that generated over one hundred million dollars in profit. Vladimir specializes in AI Product Management, Behavioral Design, Agile Product Development, and Growth and Monetization strategy across Business to Consumer, Business to Business, and Business to Government contexts. Connect with Vladimir Dyachkov
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and start applying the Behavioral Adoption Checklist to your next product initiative. ISBN: 978-83-8455-089-2 Part of the AI and Human series. For Product Managers who build for behavior, not just output. Subscribe to the Habit Machine Podcast for more conversations on Behavioral Design, problem-first creation, and the methods that transform struggle into market defaults. | |||
| Why The Best Teams Stitch Design Thinking, Lean Startup, and Agile Into One Learning Rhythm | 24 avr. 2026 | 00:05:23 | |
Episode 3: The Build-Validate-Ship Loop | Habit Machine Podcast Why The Best Teams Stitch Design Thinking, Lean Startup, and Agile Into One Learning Rhythm Episode Overview Product development is not a straight line. In this episode we dissect the Build-Validate-Ship Loop, the continuous rhythm that sets habit-forming teams apart. Two Product Managers dismantle the myth of competing methodologies and walk through exactly how Discovery, Validation, and Delivery are stitched together—not as religious ceremonies, but as a single engine that compounds learning while rivals compound features. We move from theory to practice, exposing the exact moments where the loop breaks: when speed is mistaken for direction, when clicks are mistaken for commitment, and when story points are mistaken for progress. Listeners will leave with a clear, repeatable operating system that turns behavioral telemetry into product truth. What You Will Learn
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 want to engineer products that change behavior, not just ship features. Grounded in behavioral economics, AI-native product strategy, and two decades of real-world experience, this book offers standalone diagnostics you can use the moment retention drops or your roadmap feels like a prayer. About the Author Vladimir Dyachkov, PhD is a Product leader in AI with experience in team management and aligning products with business objectives. He holds a PhD in Economics with a focus on how information influences behavior, and has spent two decades building products that people actually use. His background includes leading AI projects based on World Health Organization data, launching seven AI-driven digital medical products, managing product portfolios reaching 180 million monthly users, and integrating payment systems that generated over one hundred million dollars in profit. Vladimir specializes in AI Product Management, Behavioral Design, Agile Product Development, and Growth and Monetization strategy across Business to Consumer, Business to Business, and Business to Government contexts. Connect with Vladimir Dyachkov
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and start applying the Behavioral Adoption Checklist to your next product initiative. ISBN: 978-83-8455-089-2 Part of the AI and Human series. For Product Managers who build for behavior, not just output. Subscribe to the Habit Machine Podcast for more conversations on Behavioral Design, the Build-Validate-Ship Loop, and the methods that turn behavior into market defaults. | |||
| Why better features rarely win markets — and how Behavioral Design builds invisible moats | 24 avr. 2026 | 00:05:06 | |
Episode 2: Inside the Signal to Standard Pipeline | Habit Machine Podcast How Behavioral Design Turns Early Signals Into Market Defaults Episode Overview Building on the foundations laid in Episode 1, this episode moves from theory into practice. We walk through each phase of the Signal to Standard Pipeline with precision, examining why Behavioral Design is not a layer you add after building—but the engine that determines whether anyone sticks around. Two Product Managers dissect real scenarios where teams mistook noise for signal, scaled prematurely, and learned the hard way that adoption cannot be brute-forced with features. Central to the conversation is the Behavioral Adoption Checklist, a diagnostic tool from the Habit Machine playbook that forces an honest reckoning before a single engineering cycle is wasted. We unpack each checkpoint, debate which leading indicators genuinely predict habit formation, and offer clear tests for distinguishing a fleeting feature from a category creator. What You Will Learn
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 want to engineer products that change behavior, not just ship features. Grounded in behavioral economics, AI-native product strategy, and two decades of real-world experience, this book offers standalone diagnostics you can use the moment retention drops or your roadmap feels like a prayer. About the Author Vladimir Dyachkov, PhD is a Product leader in AI with experience in team management and aligning products with business objectives. He holds a PhD in Economics with a focus on how information influences behavior, and has spent two decades building products that people actually use. His background includes leading AI projects based on World Health Organization data, launching seven AI-driven digital medical products, managing product portfolios reaching 180 million monthly users, and integrating payment systems that generated over one hundred million dollars in profit. Vladimir specializes in AI Product Management, Behavioral Design, Agile Product Development, and Growth and Monetization strategy across Business to Consumer, Business to Business, and Business to Government contexts. Connect with Vladimir Dyachkov
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and start applying the Behavioral Adoption Checklist to your next product initiative. ISBN: 978-83-8455-089-2 Part of the AI and Human series. For Product Managers who build for behavior, not just output. Subscribe to the Habit Machine Podcast for more conversations on Behavioral Design, the Signal to Standard Pipeline, and the adoption patterns that separate durable products from forgotten launches. | |||
| Why Some Products Change the World While Others Fade Into Oblivion. Habit Machine: AI Product Management | 21 avr. 2026 | 00:05:24 | |
Episode 1: The Real Moat Is Not Features | Habit Machine Podcast Episode 1: The Real Moat Is Not Features Why Some Products Change Behavior While Others Disappear Episode Overview Breakout products rarely win because they ship faster or pack more functionality. They win because they quietly replace old routines with new defaults. In this episode, we unpack the opening chapter of the Habit Machine playbook and challenge the industry obsession with feature parity. Two Product Managers with different lenses walk through the Signal to Standard Pipeline, a four phase framework that separates market curiosities from market defaults. We explore why cognitive load is the actual barrier to adoption, how to engineer a Habit Loop that holds beyond day one, and which leading indicators actually predict scale. What You Will Learn
About the Book Title: Habit Machine: AI Product Management Series: AI and Human, Volume 1 Author: Vladimir Dyachkov, PhD Habit Machine is a practical playbook for Product Managers, founders, and builders who want to engineer products that change behavior, not just ship features. Grounded in behavioral economics, AI-native product strategy, and two decades of real-world experience, this book offers standalone diagnostics you can use the moment retention drops or your roadmap feels like a prayer. About the Author Vladimir Dyachkov, PhD is a Product leader in AI with experience in team management and aligning products with business objectives. He holds a PhD in Economics with a focus on how information influences behavior, and has spent two decades building products that people actually use. His background includes leading AI projects based on World Health Organization data, launching seven AI-driven digital medical products, managing product portfolios reaching 180 million monthly users, and integrating payment systems that generated over one hundred million dollars in profit. Vladimir specializes in AI Product Management, Behavioral Design, Agile Product Development, and Growth and Monetization strategy across Business to Consumer, Business to Business, and Business to Government contexts. Connect with Vladimir Dyachkov
Ready to Engineer Habits, Not Just Features? Grab your copy of Habit Machine: AI Product Management and start applying the Behavioral Adoption Checklist to your next product initiative. ISBN: 978-83-8455-089-2 Part of the AI and Human series. For Product Managers who build for behavior, not just output. | |||