Artificial Insights: Conversations About AI

Students are already finding their own ways to use AI. Can schools do a better job of showing them how to use it well?

In part 1 of our student special, Aasha argued that schools need more AI literacy and less fear.

In part 2, Keya described the tension students feel when AI is helpful and suspicion is high.

In part 3, Maizah named the deeper dilemma of living with a tool that is everywhere.

In part 4 of 4, Daniel speaks with Vaani, a high school student interested in law, coding, and the arts, whose...

What happens when AI is everywhere in a student’s life, but school mostly talks about it as something to avoid?

In part 1 of our student special, Aasha called for AI literacy instead of fear. In part 2, Keya described what it feels like when trust breaks down around student work. In part 3 of 4, Maizah widens the lens again: she talks about what it's like to grow up with AI as a constant presence, even while school treats it as taboo.

Maizah is a Grade 12 student and her perspective is thoughtful, conflicted, and very current. She se...

Students are already building AI into how they learn—are schools can help them use it well?

In part 1 of our student special on AI and education, Aasha raised the question of what schools are actually preparing students for. In part 2 of 4 of our student special on AI and education, Daniel speaks with Keya, a Grade 12 student balancing classes, sports, work, and plans for what comes after graduation. In this conversation, she shares a grounded and optimistic view of AI at school. For her, AI is already part of the rhythm of student life. It can explain to...

What happens when schools focus so hard on detecting AI that students start reshaping their own writing just to avoid suspicion?

In part 1 of 4 of our student special on AI and education, Daniel speaks with Aasha, a Grade 12 student from Waterloo, founder of Youth Tech Labs, and a young leader already helping other students think more clearly about AI, privacy, and what meaningful learning should look like now.

Aasha’s argument is sharp: what should education look like when AI is already here? She describes how AI detection tools created an environment of fear, how st...

Schools are trying to figure out AI in real time, but students are already living with the results.

In this special repost episode, Daniel brings back a short conversation with Pat Belliveau to open our student series on AI and education. Pat raises a hard question: if AI is already part of the world students are growing up into, what does it mean for schools to treat it mainly as a threat? There is a real risk when teachers rely on AI detection tools that aren't reliable, and real damage that can follow when students are accused...

What would you do if you had to start an AI consultancy from scratch today?

In this bonus clip, Daniel asks Pat Belliveau of Gambit Co exactly that. And Pat does what he does so well: he shares practical advice without posturing:

Start with someone in your network. Solve one real problem. Do it well enough to earn a case study. Then, build from there.

Thanks, Pat, for being refreshingly candid, quick to teach, and generous with lessons that many people would keep to themselves. It's why you're one of our favorite people!<...

AI feels easy right up until a team tries to ship it. Patrick Belliveau of Gambit Co joins Daniel to talk about the messy middle between a promising prototype and something a business can actually trust.

In this candid conversation, Daniel and Pat reflect on what changed between year one and year two of building an applied AI company. Pat explains why Gambit moved from fixed-price projects to retainer-based partnerships, how rapid prototyping helps teams stay close to the real problem, and why so many AI projects fail before they ever have a chance to deliver.

AI can automate matching and readiness checks in lending. It cannot automate trust.

In this bonus clip, Daniel asks Sharmeen Aqeel how Lyyvora will scale as borrower volume grows. Sharmeen’s answer is simple: at an early-stage fintech, one broken interaction can damage credibility. Even if AI produces the "right" output, a human still needs to verify, interpret context, and provide real connection when borrowers are anxious or unsure.

Sharmeen also looks ahead. If a "borrower-to-offers" workflow becomes trivial in a few years, Lyyvora's moat is not the application flow. It's the network and community sh...

Clinics get stuck in lending for a frustratingly simple reason: the process is hard to navigate. The information exists, lenders are willing, and qualified borrowers do get funded. But the path is not accessible, especially when you're running a clinic and don't have time to decode criteria buried across pages, videos, and jargon.

Sharmeen Aqeel is the founder and CEO of Lyyvora, and she treated this as a human-centered design problem. Lyyvora is a Lending-as-a-Service platform built for healthcare and medical aesthetics clinics, designed to make “what happens next” clear: one streamlined intake, prescreening for readiness, and matc...

AI licensing can sound like a moral argument until you look at the product constraints. If the best material is behind paywalls and contracts, “just scrape it” stops working.

In this bonus clip, Daniel pressures the obvious skeptical question: if big AI companies can afford lawsuits, why bother building fair, legal access at all? Julie Trelstad’s answer is practical. She expects the next wave of AI advancements to include many more small, domain-specific models, and those models will need verified, high-quality sources like textbooks and peer-reviewed journals.

🎧 Want the bigger picture?

This clip is o...

AI has been trained on the world’s writing. Now, we have to figure out how creators prove ownership, set permissions, and get paid when their work is used.

Julie Trelstad has spent 30 years inside publishing’s biggest technology shifts, from desktop publishing to eBooks to print-on-demand to self-publishing. In this episode, she explains why AI is forcing publishing into a new kind of rights era, one where piracy and fast imitation can flood the market within days of a book launch.

Julie is Head of US Publishing at Amlet.ai and runs Paperbacks & Pixels. She...

When AI threatens your job, the real risk is clinging to the parts of work that are already predictable.

In this bonus short, Daniel Manary and Dave Boyce (Winning by Design, author of Freemium) talk about the fear many people feel right now: AI is coming for my job. Dave argues that AI doesn't replace you as a human unless you keep trying to do work AI should handle. The path forward is to automate what is routine, and double down on the human work: alignment, confidence, strategy, and helping people navigate uncertainty.

🎧 Want the big...

"Run experiments" is easy advice. Measuring them inside a real customer journey is the hard part.

Dave Boyce has lived through multiple SaaS eras, from $1.2M ACV enterprise deals to $1,200 self-serve motions. Now, as Product lead and Executive Chair at Winning by Design, he works with growth-stage companies to rebuild their revenue systems for an AI-shaped market.

In this conversation, Daniel and Dave get concrete about what “AI-forward GTM” actually requires: a clear theory of the case, a real data model for the whole customer lifecycle (the bow tie), and an operating model that can surv...

An AI-written encyclopedia can sound coherent and still be wrong and that gap matters more than it first appears.

In this bonus short, Daniel Manary and William Beutler of Beutler Ink and The Notability Company look at the first real challenger to Wikipedia's long-standing dominance. They discuss Grokipedia, Elon Musk's AI-generated encyclopedia: why its entries can feel clearer and more complete than Wikipedia, and how that polish can mask weak or missing sources.

🎧 Want the bigger picture?

In the full episode, Bill explains why Wikipedia remains the shared reference point for major AI sys...

Wikipedia has become one of the quiet foundations of modern AI.

In this episode, Daniel explores why large language models rely so heavily on Wikipedia, both as training data and as a real-time citation source. Its concise structure, dense linking, and topic-first writing make it ideal for machines, even as fewer humans read it directly.

Daniel is joined by Bill Beutler, founder of Beutler Ink, who works inside Wikipedia’s rules to help organizations correct inaccuracies and navigate notability standards. Bill explains how Wikipedia’s volunteer model, conflict-of-interest policies, and reliance on independent journalism shape what...

This season, we’re not talking about models, benchmarks, or demos. We’re talking about how AI is reshaping how humans work, coordinate, and judge as tools get better at remembering, acting, and contextualizing. With context increasingly automated, wisdom and judgment matter more, not less.

We’ll hear from builders, operators, researchers, and leaders wrestling with how experience, trust, value, and incentives shift as AI becomes part of the fabric of work.

👀 What to expect this season:

Artificial Insights is a podcast about how AI is changing economics and work, and what happens once the technology moves beyond demos and into real organizations.

The podcast features conversations with founders, operators, and thinkers who are close to the work. People building AI products. People deploying them inside teams. And people who have already learned where AI helps and where it quietly creates problems.

Daniel started Artificial Insights to stand at the gate of businesses using AI, separating hype from lasting impact.

If you are new here, the most recent season trailer...

Across healthcare, nonprofits, construction, and creative tools, the same shift kept appearing. AI is moving work from impossible to practical.

This special wrap up episode closes out Season 4 by revisiting a handful of moments that captured that shift most clearly. Rather than focusing on replacement or marginal efficiency gains, AI is removing constraints around memory, time, coordination, and execution.

When those constraints fall, entirely new kinds of work become feasible.

Daniel reflects on examples from across the season, including systems that surface organizational context no one person could retain, workflows that compress months...

This special Christmas and New Year bonus episode is a pause. We're looking back at 2025 and thinking about what surfaced across a year of conversations with builders, executives, philosophers, and operators working close to AI.

Across industries and roles, the same shift kept appearing. Work isn't disappearing per se... but it is changing. Flipping.

Humans are moving upstream. Away from direct execution and toward enabling, guiding, and judging systems that now do the work itself. Execution is cheaper than it has ever been. Direction, responsibility, and wisdom are not.

This bonus episode weaves...

Across healthcare, nonprofits, construction, and creative tools, the same shift kept appearing. AI is moving work from impossible to practical.

This special wrap up episode closes out Season 4 by revisiting a handful of moments that captured that shift most clearly. Rather than focusing on replacement or marginal efficiency gains, AI is removing constraints around memory, time, coordination, and execution.

When those constraints fall, entirely new kinds of work become feasible.

Daniel reflects on examples from across the season, including systems that surface organizational context no one person could retain, workflows that compress months...

Regulation and innovation rarely move at the same speed. In this bonus clip, Daniel Manary and David Proulx talk about who should shape the future of AI. David argues that the people building modern systems understand both the risks and the capabilities far better than policymakers who lack technical grounding.

He contrasts Europe’s tendency to regulate early with the United States’ focus on innovation, liability, and builder responsibility. He points to the “Winning the AI Race” framework as an example of policy written by people who clearly understand the field, from guardrails to energy use to how a sy...

One of the things David Proulx is most proud of is building an AI agent that has handled more than 100,000 mental health conversations without a single hallucination.

David is the Chief AI Officer at HoloMD, where an AI agent becomes a third party in the Therapeutic Alliance. The patient wants to feel better. The psychiatrist guides their care. HoloMD adds a daily point of contact that checks in, gathers context, tracks medication adherence, and offers support between visits. Psychiatrists stay fully in charge while gaining a clearer picture of a patient's life than a single appointment can...

Most AI conversations describe personalization as if it were new. In this bonus clip, Alex Maier explains why the real shift is not personalization itself, but how agentic systems read context and respond to a person's actual state the moment they ask a question.

Alex describes how onWater uses prompts, sentiment, language patterns, and user actions to understand experience level and intent. He compares it to the way great salespeople have always read a person's posture, tone, and energy to meet them where they are. The technology is new. The underlying posture toward users is not.

Most companies stop at “ask the bot a question”. onWater wants to go further, building an app that can answer “Should I go today?” and then quietly handle everything that comes after yes.

In this episode of Artificial Insights, Daniel talks with Alex Maier, now President of onWater. His team has been working on a simple idea with complicated stakes: help people decide where to fish or paddle, understand the real conditions on the water, and act on that information without forcing users to dig through dozens of screens or data sources.

Alex explains how they app...

AI is currently in a transitional moment: a new tool being used to make old kinds of content. But, what if AI can do more than just help us create the same old things faster and better?

In this bonus clip, Daniel Manary and Ahmad Iqbal step back from product and design to explore how AI is a new creative medium that could change how people make, share, and experience ideas.

Drawing on the work of Marshall McLuhan, the Canadian media theorist who coined "the medium is the message", Ahmad explains how each technological leap...

What if "designing well" no longer requires years of training, and the real work becomes choosing the story to tell?

In this episode of Artificial Insights, host Daniel Manary interviews Ahmad Iqbal, product lead and Head of MENAP at Canva, about what it really means to design for accessibility in the age of AI. Ahmad helped launch Canva’s first generative AI features and shares how the company's guiding principle, making creativity accessible to everyone, drives its product, culture, and internal AI adoption.

The conversation traces how a 48-hour hackathon project became Magic Write, how Ah...

Most people talk about "data privacy" like it’s a legal checkbox. For Josh Müller, it’s part of faithful stewardship.

In this bonus episode, Josh and Daniel pick up on a single idea from their main conversation: data management as Kingdom stewardship. Josh shares how his once “off-the-cloud-at-all-costs” mindset softened as AI made it possible to do genuinely good things with data.

The hard part now isn’t the tech. It’s building the habits and structures that keep data private, local, and used for good.

💡 Want the full conversation?

This clip come...

What if a six-month production bottleneck became a 16-minute job?

Josh Müller, director at tech nonprofit Waha, tells Daniel how forced alignment and smart automation turned a tedious audio-editing gauntlet into a repeatable pipeline that ships Bible study content across dozens of languages. The result is more time for actual disciple-making and less time in Audacity.

They dig into privacy-first analytics in risky contexts, when to choose local models over cloud tools, and why data management is Kingdom stewardship.

🔑 What You’ll Learn in This Episode

When is the right time to start a company in AI? Adeel Zaman argues it comes down to breakthroughs.

In this bonus clip, Adeel explains why "why now" matters more than ever in AI. Without a recent step forward, most ideas have already been tried and blocked by the same old limits. He points to Jeff Bezos in 1995, who spotted the internet’s growth curve and built Amazon around books, an application that fit the technology’s strengths at the time.

🎧 Curious where Adeel takes this next?

In the full conversation, he and Daniel...

What happens when AI doesn’t just live in text and screens, but begins to reason and act in the physical world?

Adeel Zaman, CTO and Co-Founder of DOZR, has spent his career moving from deep learning research to startups, scaling companies and tackling cold-start problems with machine learning. Now, backed by the HF0 residency, his focus is on "Embodied Intelligence" and how foundation models can learn physical tasks, adapt through feedback, and interact with humans in real time.

In this conversation, Daniel and Adeel explore why embodied AGI may be a prerequisite for true ge...

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...

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 t...

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...

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:

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...

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 firs...

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...

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 conve...

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...

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 h...