Artificial Insights: Conversations About AI

Most people aren’t natural tinkerers. That simple fact shapes how AI adoption actually plays out inside companies. It’s not enough to drop a new tool into the workflow. Deadlines and old habits keep teams from trying new approaches.

In this bonus episode, Daniel and Aydin Mirzaee, CEO of Fellow, talk about why adoption stalls when people stick to the “old way,” how organizations can carve out space to experiment, and why patience is needed to push through the frustration curve.

It’s a candid look at what it really takes for teams to shift from tinkering to transformation.

🎧 Want the bigger picture?

This clip is just a glimpse of Aydin’s perspective. In the full episode, he shares how Fellow pivoted from manual meeting tools to an AI-first platform, why building for future model capabilities is now a necessity, and how AI as a “chief of staff” can raise the quality of decisions across an organization.

Listen to the full episode: https://rss.com/podcasts/manaryhaus/2227017/

🔗 Resources & Links

• 🤝 Connect with Aydin on LinkedIn: https://ca.linkedin.com/in/aydinmirzaee
• ✨ Fellow — AI meeting assistant: https://fellow.ai
• 📩 Subscribe to the Artificial Insights newsletter for summaries and takeaways: https://manary.haus/podcast/#haus

🚀 Learn something new? Leave a review and share it with someone building in AI!

Adopting AI inside an organization is rarely smooth. Most people are not natural tinkerers, and it takes more than enthusiasm to change how teams prepare, run, and follow up on meetings.

For Aydin Mirzaee, CEO and co-founder of Fellow, the turning point was realizing that AI could take the work only the most organized people were willing to do and make it accessible to everyone. He calls this an AI “chief of staff”, a system that prepares meaningful follow-ups, captures decisions and actions, and threads context across meetings so teams can focus on higher-value work.

In this episode, Daniel and Aydin explore what it looks like to move from manual meeting hygiene to AI-first workflows. They discuss reasoning-driven pre-meeting briefs, role-specific templates, and writing back into systems like Salesforce and Jira without extra human effort. Aydin also reflects on adoption realities: how to create room for experimentation, why surfacing high-value workflows matters more than tinkering, and what it means to build for models that don’t exist yet.

🔑 What You Will Learn This Episode

• ✅ Why summaries are table stakes and the real gains come from workflow design
• ✅ How meeting-type templates help you capture the right signals
• ✅ What it takes to drive adoption when most people are not tinkerers
• ✅ Why builders need to build toward a model’s future capabilities, rather than current ones

🔗 Resources & Links

• ✨ Fellow — AI meeting assistant: https://fellow.ai
• 🤝 Connect with Aydin on LinkedIn: https://ca.linkedin.com/in/aydinmirzaee
• 🎧 This New Way with Aydin Mirzaee: https://www.youtube.com/@aydin.mirzaee
• 📩 Subscribe to the Artificial Insights newsletter for key takeaways: https://manary.haus/podcast/#haus

👉 If this conversation sparks an idea, share it with a colleague! It’s a grounded look at how AI reshapes work inside real teams.

Welcome to Artificial Insights where we talk to leaders and thinkers in AI about how to do AI right. On this podcast, we sit down every other Friday with people who build things with, and write things about, AI, and talk to them about what they do and why they do it.

We've been doing this for just over a year now, and a core pattern has emerged:

Why you build with AI matters as much as how you build with AI.

Join Daniel this season as he meets with and learn from a great lineup of guests from awesome companies like Canva, Fellow.ai, and Waha.

We can't wait to introduce them all to you!

In the meantime, check out some of our favorite episodes!

• 🎧 Season 1, Episode 8 with Kris Braun on why human expertise and judgement remain essential, even with AI in the loop: https://rss.com/podcasts/manaryhaus/1788572/
• 🎧 Season 2, Episode 1 with Patrick Belliveau on how curiosity, persistence, and early GPT models kickstarted an unexpected AI journey: https://rss.com/podcasts/manaryhaus/1875537/
• 🎧 Season 2, Episode 6 with Mike Kirkup on what it’s like to demo an AI system you can’t fully predict: https://rss.com/podcasts/manaryhaus/2061508/
• 🎧 Season 3, Episode 2 with Dr. Christopher Watkin on what “infinite efficiency” forces us to rethink about work, effort, and meaning: https://rss.com/podcasts/manaryhaus/2167772/

🔗 Resources & Links

• 🎧 Listen to more episodes: https://rss.com/podcasts/manaryhaus/
• 🤝 Connect with Daniel on LinkedIn: https://www.linkedin.com/in/dmanary/
• 📩 Subscribe to the Artificial Insights newsletter for key takeaways: https://manary.haus/podcast/#haus
• 👉 Have a guest in mind? Reach out to Daniel at [email protected]

🚀 Share this trailer with a friend who’s just starting their AI journey. Thanks for listening!

From ethics to student builders, this past summer season of Artificial Insights dug into how AI shapes what it means to be human and how the next generation is already learning to use it.

Guests shared warnings about convenience, reflections on human worth, and hands-on lessons from shipping early projects.

In this recap episode, Daniel looks back at highlights from every conversation:

• 1️⃣ Sheldon Fernandez on the “instantaneous friend,” useful friction, and raising wise humans. Listen to the full episode: https://rss.com/podcasts/manaryhaus/2157598/
• 2️⃣ Dr. Christopher Watkin on efficiency, meaning, and why friction still matters. Listen to the full episode: https://rss.com/podcasts/manaryhaus/2167772/
• 3️⃣ Dr. K on the wisdom gap, the tyranny of convenience, and protecting agency. Listen to the full episode: https://rss.com/podcasts/manaryhaus/2178635/
• 4️⃣ Dvir Zagury on aligning personalization with privacy and control. Listen to the full episode: https://rss.com/podcasts/manaryhaus/2182186/
• 5️⃣ Aleks Santari on commoditized intelligence and adaptive, human-centred design. Listen to the full episode: https://rss.com/podcasts/manaryhaus/2185753/
• 6️⃣ Aasha Khan on safe spaces for students to learn AI and building with purpose. Listen to the full episode: https://rss.com/podcasts/manaryhaus/2185718/

It’s a chance to revisit the season’s biggest insights, and a reminder that doing AI right starts with protecting human worth, agency, and learning.

🔑 What You’ll Learn in This Episode

• ✅ Why adding friction can protect judgment and trust
• ✅ How to decide which decisions must remain human
• ✅ Patterns for privacy, consent, and editable context
• ✅ Lessons from the next generation about how AI should be and can be used

🔗 Resources & Links

• 🤝 Connect with Daniel on LinkedIn: https://www.linkedin.com/in/dmanary/
• 📩 Subscribe to the Artificial Insights newsletter for key takeaways: https://manary.haus/podcast/#haus
• 👉 Have a guest in mind? Reach out to Daniel at [email protected]

🎧 Looking back sharpens how we move forward. Share this episode with someone reflecting on AI’s role in their own work.

What happens when students are told not to use AI, but also told they’ll need it for their careers?

For Aasha Khan, a Grade 12 student at Cameron Heights and founder of Youth Tech Labs, that tension defined her first encounters with AI. At school, the message was clear: avoid AI or risk suspension. At home, her father, a Chief AI Officer, encouraged her to explore the technology. The mixed signals left her, like many of her peers, caught between fear and curiosity.

Aasha decided to create a safe space where high schoolers could learn AI together. Youth Tech Labs has since grown into a community that draws more than a hundred students, runs hands-on workshops, and hosts demo days where participants present their AI projects. Along the way, Aasha launched AskEve, an AI chatbot designed to break stigma around menstruation and open up conversations often kept silent.

This is the third and final part of our Back to School Special. If you missed them, check out episode four with Dvir Zagury on how curiosity led him from quantum foundations to health tech and personalized AI here: https://rss.com/podcasts/manaryhaus/2182186/ and episode five with Aleks Santari on how AI can fundamentally change the way interfaces are designed here: https://rss.com/podcasts/manaryhaus/2185753

🔑 What You’ll Learn in This Episode

• ✅ Why unclear rules around AI leave students confused and divided
• ✅ How Youth Tech Labs helps students build real projects in a supportive environment
• ✅ Why empathy and creativity are central to student-led AI initiatives
• ✅ How projects like Ask Eve show AI’s potential for social good
• ✅ Why parents and teachers need to create safe spaces for youth to explore AI

🔗 Resources & Links

• 🤝 Connect with Aasha on LinkedIn: https://www.linkedin.com/in/aasha-khan-3a2294250/
• 🌐 Check out Youth Tech Labs: https://youthtechlabs.ca
• 🌐 Check out Gambit Changemakers: https://gambitco.io/#changemakers
• 📩 Subscribe to the Artificial Insights newsletter for key takeaways: https://manary.haus/podcast/#haus
• 👉 Have a guest in mind? Reach out to Daniel at [email protected]

🎒 Inspired by this Back to School Special? Share it with a parent, teacher, or student curious about how AI will shape the classroom and beyond.

The next generation of builders isn’t just asking what AI can do, but what it should do.

For Johns Hopkins student Aleks Santari, the most striking change AI brings is the commoditisation of intelligence. When capabilities once reserved for experts become widely available, it reshapes education, work, and even how people see themselves.

Aleks is exploring that reality firsthand through three projects: Flow, a health app that adapts to each person’s context; a snake-like surgical robot for eye surgery in a lab at Johns Hopkins; and an autonomous rover so he can get first-hand experience studying autonomous behavior.

In this conversation, Daniel and Aleks discuss why people treat AI like a companion, the risks of doing so, and how dynamic user interfaces could make data more accessible and users less reliant on their devices. They also reflect on what happens when intelligence is no longer scarce, and why that might push us to rediscover the value of being human.

This is episode two of our three-part Back to School Special, featuring students experimenting at the edge of AI. In case you missed it, check out Daniel's conversation with Dvir Zagury-Grynbaum on taking the leap from quantum physics to AI here: https://rss.com/podcasts/manaryhaus/2182186/

🔑 What You’ll Learn in This Episode

• ✅ Why commoditized intelligence challenges how we define human value
• ✅ How students are building AI projects with real-world applications
• ✅ The risks of treating AI as a friend instead of a tool
• ✅ Why dynamic user interfaces could simplify health data
• ✅ What it means to apprentice in robotics while thinking like a philosopher

🔗 Resources & Links

• 🤝 Connect with Aleks on LinkedIn: https://www.linkedin.com/in/aleksantari/
• 📩 Subscribe to the Artificial Insights newsletter for key takeaways: https://manary.haus/podcast/#haus
• 👉 Have a guest in mind? Reach out to Daniel at [email protected]

💬 Feel inspired? Share this episode with someone asking how commoditized intelligence might reshape their work and identity.

How do you bridge worlds as different as quantum research and AI product building?

For Dvir Zagury-Grynbaum, the answer lies in curiosity. Still an undergraduate in physics at the University of Waterloo, Dvir has already worked at the Perimeter Institute, led AI design teams, and built tools that personalize decision making.

His project thersona.com learns from its users to help with everything from remembering birthdays to suggesting the right restaurant. He’s also applying causal inference and AI to diabetes management, helping people run “what if” simulations of their blood glucose hours into the future.

In this special Back to School episode of Artificial Insights, Daniel and Dvir explore how quantum foundations connect with causal inference, why personalization raises important privacy questions, and how AI can be designed to reflect the way humans actually operate.

🔑 What You’ll Learn in This Episode

• ✅ How quantum foundations overlap with causal inference
• ✅ How causal inference can power better health tech
• ✅ What Dvir learned building a personalized AI tool
• ✅ Why privacy and control shape user trust in AI tools

🔗 Resources & Links

• 🤝 Connect with Dvir on LinkedIn: https://www.linkedin.com/in/dvirzagury/
• ✨ Explore Persona: https://thersona.com
• 💻 Learn about Project Goose (agent orchestration): https://github.com/block/goose
• 🌐 Perimeter Institute for Theoretical Physics: https://perimeterinstitute.ca
• ✨ Gluroo (diabetes management startup): https://gluroo.com/
• 📩 Subscribe to the Artificial Insights newsletter for key takeaways: https://manary.haus/podcast/#haus
• 👉 Have a guest in mind? Reach out to Daniel at [email protected]

💬 Thinking about the future? Share this Back to School Special with someone who’s curious about how today’s students are shaping tomorrow’s AI.

What happens when the technology you rely on gets better every day while your own capacity remains the same?

For Dr. K, theologian, bioethicist, and former U.S. intelligence officer, this is a deeply human question. With two decades in applied ethics, 14 books, and a career spanning hospital ethics, ministry, and service in the intelligence community, she brings a rare perspective on AI’s impact on human worth and agency.

In this conversation, Daniel and Dr. K explore the “wisdom gap,” the widening distance between human limits and accelerating AI capacity. They discuss the “tyranny of convenience,” the pull to let machines take on hard work, and the importance of preserving agency when tools become persuasive partners.

The conversation also pushes into bigger questions. Where does our worth come from when we now share intellectual space with AI? Why is this moment unlike the printing press or past technologies? And how can leaders resist the easy path in order to choose what is right?

🔑 What You’ll Learn in This Episode

• ✅ What the “wisdom gap” means for humans in an AI-driven world
• ✅ Why convenience can erode agency if left unchecked
• ✅ How persuasive technology shapes decisions without us realizing
• ✅ Why AI will never be worse than it is today and what that means for work and meaning
• ✅ How theology and ethics can guide us through this AI moment

🔗 Resources & Links

• 🌐 Learn more about FaithTech: https://faithtech.com
• 📄 Read Tim Wu’s essay The Tyranny of Convenience: https://www.nytimes.com/2018/02/16/opinion/sunday/tyranny-convenience.html
• 📚 Explore the Center for Humane Technology: https://www.humanetech.com
• 📩 Subscribe to the Artificial Insights newsletter for key takeaways: https://manary.haus/podcast/#haus
• 👉 Have a guest in mind? Reach out to Daniel at [email protected]

💬 Have a moment of insight? Share this episode with someone wrestling with the deeper questions of AI, worth, and what it means to be human.

What happens when the work you’ve built your identity around can be done faster, and sometimes better, by AI?

For Dr. Christopher Watkin, philosopher, theologian, and associate professor at Monash University, AI’s greatest impact may be the questions it forces us to ask: What is work for? Where do we find value when productivity is no longer scarce? And what does this moment reveal about what it means to be human?

In this episode, Daniel and Dr. Watkin discuss “humanity of the gaps,” the risk of defining ourselves only by what AI can’t yet do, and why the ease AI brings to work is both a gift and a challenge. They explore how AI shifts work from process to product, and how this moment can open rare opportunities for deeper public conversations about meaning, value, and the good life.

🔑 What You’ll Learn in This Episode

• ✅ Why AI makes old philosophical questions impossible to ignore
• ✅ How “infinite efficiency” changes the purpose of work
• ✅ What “humanity of the gaps” reveals about our self-definition
• ✅ Why effort, friction, and process still matter in a world of perfect output
• ✅ How AI can help us see assumptions we didn’t know we had

🔗 Resources & Links

• 🤝 Connect with Dr. Watkin on LinkedIn: https://www.linkedin.com/in/christopher-watkin
• 🌐 Explore Dr. Watkin’s work: https://christopherwatkin.com
• 🐦 Follow Dr. Watkin on X: https://x.com/DrChrisWatkin
• 📺 Watch Dr. Watkin's AI relational audit video: https://www.youtube.com/watch?v=GN62ekMtlJg&ab_channel=ChristopherWatkin
• 📩 Subscribe to the Artificial Insights newsletter for highlights: https://manary.haus/podcast/#haus
• 👉 Have a guest in mind? Reach out to Daniel at [email protected]

💬 Learned something worth sharing? Pass this episode along to someone asking deep questions about AI and its place in our lives.

Before ChatGPT, Sheldon Fernandez knew what it was to wrestle with a sentence until it worked. As an AI ethics speaker, former AI CEO, and theologian, he’s seen what’s gained, and what’s lost, when the work of critical thinking is just a click away.

Now, as his children grow up in a world where AI can answer every question and affirm every feeling, he’s asking what that means for how we learn, relate, and make decisions. Sheldon brings a rare mix of technical expertise and philosophical insight to questions at the heart of AI and humanity.

In this episode, Daniel and Sheldon talk about the pace of AI’s progress, why the temptation to outsource thinking is so strong, and how to keep hold of what is uniquely human in a time when that’s harder to define. They explore AI’s role in education, decision-making, and the skills we need to thrive in an AI-powered world.

🔑 What You’ll Learn in This Episode

• ✅ How growing up before AI changes the way you use it
• ✅ Why constant validation from AI can get in the way of honest feedback
• ✅ How AI "shifts" where we do our critical thinking
• ✅ The risks of replacing human relationships with AI conversations
• ✅ How theology and technology meet in questions of consciousness and the sacred

🔗 Resources & Links

• 🤝 Connect with Sheldon on LinkedIn: https://www.linkedin.com/in/sheldonfernandez/
• 📽️ Watch Sheldon's talk on The Theological Implications of Artificial Intelligence: https://www.youtube.com/watch?v=wDPcnnltmf8
• 📩 Subscribe to the Artificial Insights newsletter for summaries and takeaways: https://manary.haus/podcast/#haus
• 👉 Have a guest in mind? Reach out to Daniel at [email protected]

🚀 Learn something new? Leave a review and share it with someone thinking about AI’s future.