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  • Are you using AI or is AI using you? | Ricardo Luiz | Season finale
    2026/07/02

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    We talk a lot on this show about what AI can do. This one's about what it can quietly take, if you let it.

    Ricardo Luiz has spent over twenty years building products at the intersection of psychology, UX and AI, and his warning is simple: the moment you outsource what to think, you've outsourced who you are. AI is good enough and fast enough that most people won't notice the handoff happening.

    We get into exactly where the line sits between AI amplifying you and AI quietly making you dependent on it. Ricardo's test: if the tool disappeared tomorrow, would you panic or would you just slow down? Panic means you were never really driving.

    We also get into why Anthropic named 'understanding what's happening inside the black box' a real 2026 goal, why intent is the one word Ricardo wants you to sit with before opening another AI tool and a story involving a dog, a cancer diagnosis and a vaccine formula that shouldn't have existed. Plus a study on why people trust an AI's medical answer over an actual doctor's, even when it's wrong.

    And we get honest about the economics nobody wants to talk about. The tools feel cheap right now because the real cost isn't being charged yet. Ricardo's bet: give it two years and the businesses behind these tools will have to charge what they actually cost and not everyone will be able to afford what they've gotten used to.

    Fair warning: this one might change how you use every AI tool you touch after it.

    About Ricardo: Ricardo is a product leader focused on AI-native product development, mentorship and the cultivation of communities of practice. He's spent his career turning ambiguous problems into shipped products and individual contributors into the teams everyone wants to work on. He mentors emerging and senior PMs across geographies, hosts peer-learning circles and believes the most effective thing a senior practitioner can do is multiply other practitioners.

    - LinkedIn: https://www.linkedin.com/in/uxluiz/
    - UXDX: https://uxdx.com/profile/ricard-luiz/
    - WUD Portugal: https://wudportugal.com/orador/ricardo-luiz/

    Mentioned in this episode:

    • 'The Urgency of Interpretability' - Dario Amodei: https://darioamodei.com/post/the-urgency-of-interpretability
    • The study on over-trust in AI-generated medical responses: https://arxiv.org/abs/2408.15266
    • Coverage of the Claude Max plan usage-limits lawsuit (Engadget): https://www.engadget.com/2194626/anthropic-hit-with-lawsuit-over-its-claude-max-usage-limits/

    Season 2 ends here. Season 3 arrives in September and takes the show beyond tech; we will have doctors, chefs, scientists, artists, all asked the same closing question. Subscribe now so you're there for episode one.


    Human × Intelligent is a podcast at the intersection of design, AI and human agency. Hosted by Madalena Costa.
    → humanxintelligent.com
    → https://www.instagram.com/humanxintelligent/
    → https://www.linkedin.com/company/human-x-intelligent/
    → https://www.instagram.com/designwithmaddie/
    → https://www.linkedin.com/in/madalenafigueirasdacosta/


    📩 Want to be a guest on Human X Intelligent? Reach out to Madalena at madalena@humanxintelligent.com

    Support the show

    🎙️ Human × Intelligent - a podcast about trust, transparency and human agency in AI systems, for product designers, PMs and founders building with AI.

    🔔 Subscribe so you don't miss the next episode

    🌐 humanxintelligent.com

    Hosted by Madalena Costa · Senior product designer and AI systems strategist

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    48 分
  • Is AI making us dumber? The science, the warning and what to do about it
    2026/06/18

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    You've heard the productivity pitch. AI makes you faster. AI makes you more efficient. AI makes your work better.

    But what if it's also making you worse at working without it and faster than you think?

    In this episode of Human × Intelligent, I go deeper into a cluster of research and stories that, taken together, paint a picture we can't afford to ignore. A study from Carnegie Mellon, Oxford, MIT and UCLA found that just 10 minutes of AI assistance was enough to impair independent problem-solving. Researchers have shown that inaudible sounds hidden inside background music can hijack AI notetakers in your meetings without you knowing. MIT professor Max Tegmark has pointed out that AI is currently less regulated than a sandwich shop. And the movie Idiocracy, a 2006 comedy barely anyone saw, is starting to feel less like satire and more like a schedule.

    This isn't a doom episode. It's an episode where I share a perspective. I walk through what the science actually says, what it means for how we work and lead and what to do about it. From the three questions you should be asking every AI vendor you work with, to the one habit that protects your cognitive independence, to what it actually means to be an irreplaceable human professional in 2026.

    If you use AI at work and you do, this is the episode to sit with.


    Reading list:

    • AI Assistance Reduces Persistence and Hurts Independent Performance - arXiv
    • Using AI for 10 minutes damages intellect, study shows - Euronews
    • AI: the "boiling frog" effect on cognition - Futurism
    • AI assistants can be hijacked by inaudible sounds - Cyber Insider
    • AI is less regulated than sandwiches - Euronews
    • Idiocracy: A Prophetic View of an AI-Driven Future - Aragon Research
    • A Place for Human Talent in the AI Age - IMF
    • Redesigning work around human skills - EY


    Connect with us:
    🌐 humanxintelligent.com
    📸 Instagram: @designwithmaddie
    📸 Instagram: @humanxintelligent
    💼 linkedin.com/in/madalenafigueirasdacosta
    💼 linkedin.com/company/human-x-intelligent

    Support the show

    🎙️ Human × Intelligent - a podcast about trust, transparency and human agency in AI systems, for product designers, PMs and founders building with AI.

    🔔 Subscribe so you don't miss the next episode

    🌐 humanxintelligent.com

    Hosted by Madalena Costa · Senior product designer and AI systems strategist

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    23 分
  • From prototype to production: Why building reliable Agentic AI is still so hard | Joana Mesquita
    2026/06/09

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    Building an AI agent has never been easier. But getting it to production? That's where most projects quietly die.

    In this episode of Human X Intelligent, host Madalena Costa sits down with Joana Mesquita, Machine Learning Engineer at Swiss Post and former ML practitioner at Adidas and Feedzai, to explore what fundamentally changes when you move from deterministic software to probabilistic, generative AI systems and why so many teams are unprepared for that shift.

    Joana has spent years building scalable AI systems, implementing MLOps practices and even developing tools to measure the carbon footprint of machine learning workflows. She's one of the clearest thinkers working at the intersection of AI engineering and responsible development.

    In this episode, we cover:

    • Why building a working prototype is easy, but building a reliable agentic system is a completely different challenge
    • What fundamentally breaks when you move from deterministic to probabilistic, generative systems
    • Why traditional governance models fail for agentic AI and what needs to replace them
    • How to embed governance into the product itself
    • Input, output, data and tool guardrails with practical examples
    • Why evaluation needs to start on day one (and the data behind why it matters)
    • The risks and trade-offs of using LLMs as judges and how actually to align them
    • What breaks in the prototype-to-production transition: data quality, cost, latency and governance
    • How to move from 'trust me, it looks good' to trust backed by evidence and measurement
    • How organizations can balance innovation speed with responsible AI development
    • What sustainable AI scaling actually means, including environmental impact

    One idea that will stay with you: 'Stop thinking about AI products as only the model. Start thinking about them as a system that learns over time.'

    Whether you're an ML engineer, a product manager or a technical leader navigating the GenAI transition, this conversation will change how you think about what it actually takes to build AI that works in the real world.


    Connect with Joana Mesquita:
    → LinkedIn: https://www.linkedin.com/in/joanamesquita96/
    → Medium: https://medium.com/@joana.c.mesquita.f


    Human × Intelligent is a podcast at the intersection of design, AI and human agency. Hosted by Madalena Costa.
    → humanxintelligent.com
    → https://www.instagram.com/humanxintelligent/
    → https://www.linkedin.com/company/human-x-intelligent/
    → https://www.instagram.com/designwithmaddie/
    → https://www.linkedin.com/in/madalenafigueirasdacosta/


    📩 Want to be a guest on Human X Intelligent? Reach out to Madalena at madalena@humanxintelligent.com

    Support the show

    🎙️ Human × Intelligent - a podcast about trust, transparency and human agency in AI systems, for product designers, PMs and founders building with AI.

    🔔 Subscribe so you don't miss the next episode

    🌐 humanxintelligent.com

    Hosted by Madalena Costa · Senior product designer and AI systems strategist

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    44 分
  • How to use NotebookLM to do real product research (with the prompts)
    2026/05/05

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    NotebookLM can do in an afternoon what used to take a research team a week, if you know how to prompt it.

    In this episode of Human × Intelligent, we walk through a complete 8-step AI-assisted research workflow using a real Spotify UX interview study as our working example. Eight participants, 60-minute sessions and a set of raw transcripts, turned into personas, empathy maps, Jobs to Be Done analysis, How Might We questions, an opportunity matrix and a full synthesis report.

    Every step includes the exact prompt to paste into NotebookLM. No vague instructions. No, just ask AI to help you. Real prompts, real frameworks, real output.

    What you'll learn:

    • How to orient NotebookLM before any analysis begins (and why this matters)
    • How to build 3 grounded user personas, including a tension map that shows where their needs conflict
    • How to create empathy maps per persona using actual participant language
    • How to identify functional, emotional and social Jobs to Be Done and rank those that are most underserved
    • How to generate and prioritise How Might We questions that open up real solution space
    • How to build a feature opportunity matrix and effort vs impact quadrant
    • How to affinity cluster raw insights into a 3-level observation → insight → opportunity hierarchy
    • How to generate an executive summary, full research report and stakeholder presentation outline

    All 16 prompts are included in the show notes as a ready-to-use guide.

    This workflow applies to any qualitative research: user interviews, usability test notes, support tickets, survey responses. If you can put it in a document, NotebookLM can help you make sense of it.

    Show Notes:

    • Full prompt guide PDF
    • NotebookLM
    • Follow Human × Intelligent

    Support the show

    🎙️ Human × Intelligent - a podcast about trust, transparency and human agency in AI systems, for product designers, PMs and founders building with AI.

    🔔 Subscribe so you don't miss the next episode

    🌐 humanxintelligent.com

    Hosted by Madalena Costa · Senior product designer and AI systems strategist

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    27 分
  • AI doesn't fix broken products. It amplifies them | Michelle Brito
    2026/04/28

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    AI won’t fix your product. In many cases, it makes things worse.

    In this conversation, Michelle Brito explains why most companies are getting AI adoption wrong and what they should be doing instead.

    From her work at Volkswagen Digital Solutions, Michelle shares practical insights on designing AI-powered products that actually deliver value and not confusion.

    In this episode, you’ll learn:
    - When artificial intelligence actually makes sense in a product
    - Why AI is often used as a shortcut for deeper problems
    - The difference between AI and simple automation
    - How to evaluate if your workflows are ready for AI
    - Why user trust breaks when AI is introduced too early

    ⚠️ The biggest mistake?
    Starting with the technology instead of the problem.

    💡 Key takeaway:
    AI doesn’t fix broken systems. It amplifies them.

    Connect with Michelle Brito:
    → LinkedIn: https://www.linkedin.com/in/michelle-brito-47342554/

    Human × Intelligent is a podcast at the intersection of design, AI and human agency. Hosted by Madalena Costa.
    → humanxintelligent.com
    → https://www.linkedin.com/company/human-x-intelligent/
    → https://www.instagram.com/humanxintelligent/
    → https://www.instagram.com/designwithmaddie/
    → https://www.linkedin.com/in/madalenafigueirasdacosta/

    Guest bio
    Michelle Brito is a Senior Product Designer at Volkswagen Digital Solutions and a mentor at Ladies that UX Lisbon, with over 15 years of experience spanning journalism, editorial design, and digital product strategy. Based in Lisbon, she currently leads design efforts for B2B search engines and researches the integration of AI-driven solutions within the automotive sector. Her background is uniquely multidisciplinary, combining a Master’s in Communication Sciences with a d.MBA and specialized training in UX/UI design. Throughout her career, which includes work for publishing houses, government agencies and marketing firms, Michelle has focused on bridging the gap between business goals and user needs through benchmarking, usability testing and visual thinking.

    Chapter timestamps
    00:00 – Why companies are asking the wrong AI question
    00:42 – Introduction to Michelle Brito
    01:15 – Is AI the right starting point?
    02:20 – Where companies misuse AI (simple problems, wrong solutions)
    03:18 – AI as a shortcut for deeper issues
    03:39 – Why organizations rush into AI
    04:44 – When AI creates confusion and distrust
    05:30 – How to push back on stakeholders
    06:14 – How to know when AI actually makes sense
    07:27 – Why users don’t adopt AI tools
    08:24 – Questions to evaluate AI vs automation
    08:40 – AI driven by hype vs real need
    09:28 – Real example: AI making simple tasks harder
    10:10 – Red flags in AI product decisions
    11:03 – Why research still matters (even if it’s “boring”)
    12:07 – Responsible AI in regulated environments
    13:28 – Who is accountable for AI decisions?
    14:48 – What healthy AI adoption looks like inside teams
    16:40 – Where to start with AI (the right way)
    17:21 – The most overlooked first step
    18:16 – Making decisions under pressure
    19:21 – AI requires simplification, not complexity
    19:53 – Practical advice to avoid AI traps
    21:06 – Final thoughts on AI hype vs reality

    Concepts to explore further:
    → AI vs Automation
    → AI as a multiplier (not a fixer)
    → Problem-first vs technology-first thinking
    → User trust in AI systems
    → AI readiness (data, workflows, goals)

    👉 Subscribe for more conversations on AI, product design and human-centered technology.

    Support the show

    🎙️ Human × Intelligent - a podcast about trust, transparency and human agency in AI systems, for product designers, PMs and founders building with AI.

    🔔 Subscribe so you don't miss the next episode

    🌐 humanxintelligent.com

    Hosted by Madalena Costa · Senior product designer and AI systems strategist

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    23 分
  • The interface trap: Why your AI adoption is failing (and how to fix it) | Kaisa Martiskainen
    2026/04/21

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    Is your team actually using AI, or are they just playing with it?

    In this episode of Human X Intelligent, host Madalena Costa sits down with Kaisa Martiskainen, AI Operations lead, to uncover the hidden gap in corporate AI adoption. While usage metrics might be up, true understanding is often lagging. Kaisa explains why providing access to chatbots isn’t the same as building capability and how the 'Interface Trap' prevents organizations from seeing the real value of AI.

    In this episode, we explore:

    • The missing conceptual layer: Why mental models are more important than tool proficiency.
    • The interface trap: How limiting AI to a chatbot window narrows your strategic vision.
    • Human learning vs. Machine speed: Why humans need friction and failure to truly 'get' AI.
    • Predictors vs. knowers: Understanding the three foundational concepts every employee needs before their first prompt.
    • Beyond surface level: How to transition from "interacting" with AI to 'integrating' it into your organizational DNA.

    If you’re a leader, manager or individual contributor feeling overwhelmed by the AI hype, this conversation will help you shift from reactive usage to intentional system thinking.

    Connect with Kaisa Martiskainen:
    → LinkedIn: www.linkedin.com/in/kaisamartiskainen
    → Substack: https://mamaknowsai.substack.com

    Human × Intelligent is a podcast at the intersection of design, AI and human agency. Hosted by Madalena Costa.
    → humanxintelligent.com
    → https://www.linkedin.com/company/human-x-intelligent/
    → https://www.instagram.com/humanxintelligent/
    → https://www.instagram.com/designwithmaddie/
    → https://www.linkedin.com/in/madalenafigueirasdacosta/

    Guest bio
    Kaisa works at the intersection of technology and human understanding. She helps organizations and individuals understand how to work with artificial intelligence in practical, thoughtful ways, focusing not just on tools, but on how technology changes the way people think, learn and make decisions

    Chapter timestamps

    • 00:00 – Use vs. Understand
    • 01:09 – Real AI Adoption
    • 02:49 – AI Mental Models
    • 04:29 – The Metrics Myth
    • 05:35 – How Humans Learn AI
    • 07:21 – 3 Rules of Prompting
    • 10:06 – The Interface Trap
    • 12:38 – Access ≠ Capability
    • 15:47 – AI as a Collaborator
    • 17:28 – The Teaching Problem
    • 19:54 – A Learning Challenge
    • 21:43 – The "Ideal" AI Org
    • 24:32 – The Best Investment
    • 25:49 – Where to Learn More
    • 26:57 – Final Takeaways


    Concepts to explore further:
    → AI vs Automation
    → AI as a multiplier (not a fixer)
    → Problem-first vs technology-first thinking
    → User trust in AI systems
    → AI readiness (data, workflows, goals)

    👉 Subscribe for more conversations on AI, product design and human-centered technology.

    Support the show

    🎙️ Human × Intelligent - a podcast about trust, transparency and human agency in AI systems, for product designers, PMs and founders building with AI.

    🔔 Subscribe so you don't miss the next episode

    🌐 humanxintelligent.com

    Hosted by Madalena Costa · Senior product designer and AI systems strategist

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    29 分
  • The future of UX: design that knows you better than you know yourself | Joana Cerejo
    2026/04/14

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    What does it mean to truly anticipate a user and not just what they'll click next...but what they're trying to become?

    In Episode 19 of Human × Intelligent, Madalena Costa is joined by Joana Cerejo, design lead, AI product designer and author of the Anticipatory Design Playbook. Together, they explore the real depth of anticipatory design, how behavioral science fits into modern AI product work and why most systems fail not because of bad technology but because of a fundamental misunderstanding of human intent.

    In this episode:
    - The three layers of anticipation: needs, behavior and outcomes
    - Why designing for agency can't be an afterthought
    - Behavioral science frameworks every AI designer should know
    - The filter bubble problem and collective manipulation
    - What the Nest Thermostat gets wrong about resilient design
    - Why transparency is the foundation of everything

    Connect with Joana Cerejo:
    → LinkedIn: https://www.linkedin.com/in/jcerejo/
    → Website: https://jcerejo.com/
    → The Anticipatory Design Playbook (Amazon): https://www.amazon.es/-/pt/dp/1041079109
    → Watch Why Personas Fail AI (And What Works): https://www.youtube.com/watch?v=_7dSuJB6M1o&t=897s

    Human × Intelligent is a podcast at the intersection of design, AI and human agency. Hosted by Madalena Costa.
    → humanxintelligent.com
    → https://www.instagram.com/humanxintelligent/
    → https://www.linkedin.com/company/human-x-intelligent/
    → https://www.instagram.com/designwithmaddie/
    → https://www.linkedin.com/in/madalenafigueirasdacosta/

    Guest bio
    Joana Cerejo is a design lead and AI product designer working at the intersection of user experience, behavioral science, and intelligent systems. With nearly a decade of experience designing AI-powered products across fintech, e-learning, and manufacturing, she specializes in making systems that are human-centered, trustworthy, and ethically grounded. She is the author of the Anticipatory Design Playbook, exploring how AI can move beyond predicting behavior to genuinely supporting people in meaningful, long-term ways.

    Resources & tools section
    Frameworks mentioned in this episode:
    → Prochaska Transtheoretical Model - stages of behavioral change; helps design systems that meet users where they actually are
    → Fogg Behavior Model - behavior happens when motivation, ability, and prompt align at the same time
    → Nudge Theory - the right intervention at the right moment can make or break a service

    Book:
    The Anticipatory Design Playbook by Joana Cerejo - available on Amazon

    Concepts to explore further:
    → Filter bubble effect
    → Human-in-the-loop design
    → Foresight/futures thinking methodology
    → AI literacy and explainability

    Support the show

    🎙️ Human × Intelligent - a podcast about trust, transparency and human agency in AI systems, for product designers, PMs and founders building with AI.

    🔔 Subscribe so you don't miss the next episode

    🌐 humanxintelligent.com

    Hosted by Madalena Costa · Senior product designer and AI systems strategist

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    29 分
  • Is AI fixing your teams or just making the cracks more visible? | PART II | Hugo Froes
    2026/04/09

    Send us an email!

    In Part II of this conversation, Madalena Costa and Hugo Froes move from diagnosis to direction, exploring what conscious AI adoption actually looks like inside product teams, why designers may be the most underestimated players in the AI era and whether any organization should even be trying to become AI-first.


    Hugo Froes is Director of Product Strategy at Nagarro and former Head of Product Operations at OLX and Farfetch, with over 25 years of experience building and transforming product organizations.


    In this episode, you’ll learn:
    - Why designers may become the most valuable players in the AI era
    - How to redefine team structures around skill sets
    - Why the PM, designer and engineer trio may need to be completely rethought
    - The hidden danger of AI-generated code that looks production-ready but isn’t
    - Why LinkedIn is no longer a reliable signal of someone’s actual capability
    - How recommendations and trust networks are becoming the new hiring filter
    - What organizations should be asking instead of ‘how do we become AI-first?’
    - Why adding AI to a broken product just creates a more broken product, faster

    Key ideas explored:
    - The designer’s moment: systems thinking and human empathy position designers as critical infrastructure
    - Team structure rethink: the future isn’t about roles, it’s about skill sets distributed differently
    - The trust filter: as AI floods the market with content and code, personal recommendations become the real signal
    - AI-aware not AI-first: the better question is always does AI reduce friction here, or add it?
    - The role of judgment: the hardest things to automate are the most human: taste, framing, empathy, direction


    Chapters
    00:00 The Cycle of Information Quality
    01:47 Understanding System Functionality
    04:03 The Role of Designers in AI
    07:38 Redefining Team Structures
    11:04 The Future of Product Management and Design
    13:14 Navigating Titles and Roles in UX
    16:35 The Challenge of Hiring in the AI Era
    20:49 Should Organizations Be AI-First?


    Links
    Website: humanxintelligent.com
    Join the conversation: https://forms.gle/qdnd3pMnr6KBDCA1A
    LinkedIn: @hugofroes
    Instagram: @thehugofroes
    LinkedIn: @human-x-intelligent
    Instagram: @humanxintelligent
    LinkedIn: @madalenafigueirasdacosta
    Instagram: @designwithmaddie


    // Human x Intelligent explores how humans and AI design, build and collaborate in intelligent systems //

    Support the show

    🎙️ Human × Intelligent - a podcast about trust, transparency and human agency in AI systems, for product designers, PMs and founders building with AI.

    🔔 Subscribe so you don't miss the next episode

    🌐 humanxintelligent.com

    Hosted by Madalena Costa · Senior product designer and AI systems strategist

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    24 分