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Joyce Shin, founder of The Human Edge and ex-head of design operations at Dropbox, helped scale teams and systems there. Trained in neuroscience and raised across Texas, Ohio, Seoul, and Tokyo, she studied resilience and effectiveness, first after a traumatic brain injury and later professionally in tech. She left Dropbox to ask: in AI everywhere, what makes us human? She created the PEARLS framework—six skills in thinking, creativity, ethics, and leadership—areas AI can't replicate.

This is her first public sharing of PEARLS. Many see AI as just a tool, not a way to rethink business. For startup founders building better teams, this chapter offers valuable insights.

What we covered

1. The PEARLS framework, fully unpacked — Presence, Edge, Authority, Roots, Legacy, and Signal as the six dimensions of human and organizational differentiation in the AI era.
2. Why leading indicators beat lagging ones — The signals that tell you a team is cognitively decaying before engagement scores and turnover catch up.
3. What acquisitions actually break inside a scaling company — Lessons from Dropbox on cultural integration, tooling, and the human work most M&A playbooks skip.
4. The shift from linear careers to horizontal experience — Why disparate cross-functional exposure now beats two-years-and-promote, and what that means for how you design growth paths.
5. The CEO's job in an AI-native organization — Why senior leaders should stop trying to dictate AI workflows and start building the container their teams operate inside.

Three insights worth keeping

• AI commoditizes the average, so the moat moves to what AI can't do. Partnerships, community building, and the communication of vision and story all become more valuable, not less, as automation eats the middle of the skill curve.
• Resilient organizations are based on their identity, not just their processes. Companies that understand who they are and make steady decisions build trust with customers, employees, and partners—trust that rivals using the same tools can't easily copy.
• Authenticity outperforms polish. The quirks, imperfections, and real-life mistakes of leadership build more trust than highly produced corporate messaging — and that gap will widen as AI-generated content floods every channel.

Links

• The Human Edge: https://humanedge.studio/
• Joyce Shin on LinkedIn: https://www.linkedin.com/in/joyceshin
• Future Ventures: https://ca.linkedin.com/company/future-ventures-corp

About Joyce Shin

Joyce Shin is the founder of The Human Edge, an advisory practice that helps founders, CEOs, and organizations build the capacities AI cannot replicate. Before founding The Human Edge, she was head of design operations at Dropbox, where she scaled teams and systems through IPO growth, acquisitions, and the shift to remote work. She holds a degree in neuroscience and brings a uniquely cross-disciplinary lens to leadership, organizational design, and the future of human work.

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Shahin Nabavian, a computer scientist turned venture builder, has worked across operations, infrastructure, and transformation for the past decade. His experience includes a London-based financial startup, venture-building at Shell's maritime division, work at The Economist Group, and founding edtech startup Super Savvy Education. Now, he leads Team CMV (CentricMind Ventures), focusing on emerging technologies like infrastructure enabling companies to use LLMs effectively. Their main venture, Go-User, applies this to people services.

The conversation is important because much of what is called' AI adoption' is actually just deployment without ROI. Shahin has observed companies of all sizes misusing chatbots, wasting tokens, and ending up with chaos. He can also explain why this happens in simple language. If your company earns $ 3m-$50 M and you're exploring AI's ROI, this episode is for you.

Topics Covered

• Why company culture beats company size in AI adoption. Why The Economist Group made more progress than expected, and why Shell's scale became a hindrance, not an advantage.
• The real reason AI ROI is missing. It's not the models. It's not the agents. It's the infrastructure layer beneath them — and most companies haven't built it.
• Every company needs a brain. What Shahin means by "AI brain," why generic RAG implementations fail, and what a librarian-style routing layer actually looks like in practice.
• The evolving role of the founder and CEO. What AI takes off the executive plate, what stays uniquely human, and why "purple unicorns" — operators fluent in both business and tech — become the default hire.
• Why Kodak and Blockbuster aren't technology stories. Shahin's view on Board dynamics, shareholder pressure, and the kind of CEO incumbents actually need to bring in to survive a platform shift.

Key Insights

1. The bottleneck isn't intelligence — it's plumbing. The models and tools are well-developed, but most organizations still need a way to understand how their business actually operates. This way, the AI can direct questions to the right source instead of randomly searching through every connected system.
2. Engineering-led AI initiatives consistently underdeliver. Starting a transformation by focusing on tools instead of clear service goals can cause a lot of manual work, higher costs, and confusion for users. It's better to start by understanding what the business wants to achieve and then plan the system around that.
3. Transformation is a challenge for the Board before it becomes a tech issue. Most CEOs don’t stumble because the technology is too complex; instead, they often face pressure from shareholders demanding faster results than are realistically achievable. To help overcome these hurdles, companies might consider bringing in a CEO from outside the industry, pairing them with a COO who understands the current business well, and giving them the freedom to learn from mistakes along the way.

Links

• Shahin Nabavian on LinkedIn: https://www.linkedin.com/in/nabavian/
• Future Ventures: https://ca.linkedin.com/company/future-ventures-corp
• Future Ventures Forum: futureventures.ca/community

About the Guest

Shahin Nabavian is the Founder of Go-User and a co-founder of Team CMV (CentricMind Ventures), where he builds AI-native systems for fast-growing companies. He holds a PhD in computer science and has spent over a decade building and supporting ventures across financial services, energy, publishing, and education — including work with Shell and The Economist Group. His current focus is on the infrastructure layer that turns organizational data into something AI can actually reason o

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Dr. Sylvain Charlebois, the "Food Professor," is the Senior Director of Dalhousie’s Agri-Food Analytics Lab, lead author of Canada's Food Price Report, and a prominent researcher in food supply chain management. He’s the go-to expert for food inflation stories and provides data that guides grocery executives. With 20 years studying Canada's rising food costs, he argues that debates wrongly blame big corporations or stores, overlooking factors like trade barriers, slow regulations, retail crime, and recycling policies that lack proper cost analysis. Sylvain’s data helps differentiate between factors influencing prices and those making headlines, offering valuable insights for food producers, agtech investors, and sector analysts to better interpret news.

Topics Covered

1. Grocery theft as a $10 billion problem — The rise of organized retail crime, the urban food deserts it creates, and who ultimately pays.
2. Why Canadian food companies sell in the US, not Canada — How weeks-versus-months approval timelines are quietly redirecting capital and product south.
3. Canada's branding problem — "Boston lobster from Canada" and why a country with great products can't seem to build great food brands.
4. AI in the food system — Where it's already working (precision agriculture, soil science, animal feed), where it's lagging (manufacturing), and where it gets ethically uncomfortable (surveillance pricing for households).

Key Insights

• Bad policy is the blind spot nobody can see. Interprovincial trade barriers, industrial carbon pricing, and recycling laws all add real cost to running a food business — but because consumers can't point at them on a shelf, the political will to fix them never materializes.
• The story of grocers versus consumers overlooks how the real incentives work. When cheaper options like GMO products or newly-made dairy substitutes appear on store shelves, stores with thin profit margins—around 2-3%—don't usually lower prices for shoppers. Instead, they often choose to increase their profit on familiar products. Until labeling requirements and competition rules change, having cheaper ingredients won't necessarily lead to lower grocery prices.
• Greenfield innovation moves faster than retrofitting. Canada's food manufacturing industry is slow to adopt AI and automation because it's weighed down by old habits and investments in outdated equipment. The best way to move forward is to build new facilities, ideally working with universities, so there's no old baggage holding things back.

Links

• 📺 Watch the episode on YouTube: https://youtu.be/vLM1QKjrE40
• 📊 Agri-Food Analytics Lab at Dalhousie: https://www.dal.ca/sites/agri-food.html
• 🎧 The Food Professor Podcast: https://the-food-professor.simplecast.com/
• 🔗 Connect with Sylvain on LinkedIn: https://www.linkedin.com/in/thefoodprofessor/
• 🔗 Connect with Maxim on LinkedIn: https://www.linkedin.com/in/maxim-atanassov

About Dr. Sylvain Charlebois

Dr. Sylvain Charlebois is a professor and Senior Director of the Agri-Food Analytics Lab at Dalhousie University, where he leads research on food supply chains, consumer behavior, and food economics. He is the lead author of Canada's Food Price Report, co-host of The Food Professor podcast, and one of the most-cited researchers globally in food supply chain management and traceability. His work bridges academia, industry, and policy — making him a go-to voice on the forces shaping the future of food, grocery, retail, restaurants, and agriculture.