Investing In People, AI, and the Future of Work with Virginie Raphael

In this episode, I’m joined by Virginie Raphael — investor, entrepreneur, and philosopher of work — for a wide-ranging conversation about incentives, technology, and how we build systems that scale without losing their humanity.

We talk about her background growing up around her family’s flower business, and how those early experiences shaped the way she thinks about labor, value, and operating in the real economy. That foundation carries through to her work as an investor, where she brings an operator’s lens to evaluating businesses and ideas.

We explore how incentives quietly shape outcomes across industries, especially in healthcare. Virginie shares why telehealth was a meaningful shift and what needs to change to move beyond one-to-one, supply-constrained models of care.

We also dig into AI, venture capital, and the mistakes founders commonly make today — from hiring sales teams too early to raising too much money too fast. Virginie offers candid advice on pitching investors, why thoughtful cold outreach still works, and how doing real research signals respect and fit.

The conversation closes with a contrarian take on selling: why it’s not a numbers game, how focus and pre-qualification drive better outcomes, and why knowing who not to target is just as valuable as finding the right people.

If you’re thinking about the future of work, building with intention, or navigating entrepreneurship in an AI-accelerated world, this episode is for you. And for more conversations like this, join us at Snafu Conference 2026 on March 5th, where we’ll keep exploring incentives, human skills, and what it really takes to build things that last.

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Reflections on Work, Geography, and AI Adoption

• Virginie shares what she’s noticing as trends in work and tech adoption:

• Geographic focus: she’s excited to explore AI adoption outside traditional tech hubs.

• Examples: Atlanta, Nashville, Durham, Utah, Colorado, Georgia, North Carolina, parts of the Midwest.

• Rationale: businesses in these regions may adopt AI faster due to budgets, urgency, and impatience for tech that doesn’t perform.

• “There are big corporates, there are middle and small businesses in those geos that have budget that will need the tech… and/or have less patience, I should say, for over-hub technologies that don’t work.”

• She notes that transitions to transformational technology never happen overnight, which creates opportunities:

• “We always underestimate how much time a transition to making anything that’s so transformational… truly ubiquitous… just tends to think that it will happen overnight and it never does.”

• Robin adds context from her own experience with Robin’s Cafe and San Francisco’s Mission District:

• Observed cultural and business momentum tied to geography

• Mentions Hollywood decline and rise of alternative media hubs (Atlanta, Morocco, New Jersey)

• Virginie reflects on COVID’s impact on workforce behaviors:

• Opened a “window” to new modes of work and accelerated change:

• “There were many preexisting trends… but I do think that COVID gave a bit of a window into what was possible.”

• Emphasis on structural change: workforce shifts require multi-year perspective and infrastructure, not just trends.

Investor, Mission, and Capital Philosophy

• Virginie clarifies she is an investor, not a venture capitalist, resisting labels and prestige metrics.

• “I don’t call myself a venture capitalist… I just say investor.”

• Focuses on outcomes over categories, investing in solutions that advance the world she wants to see rather than chasing trendy tech sectors.

• “The outcome we want to see is everyone having the mode of work that suits them best throughout their lives.”

• Portfolio themes:

• Access: helping people discover jobs they wouldn’t otherwise know about.

• Retention / support: preventing workforce dropouts, providing appropriate healthcare, childcare, and caregiving support.

• “Anyone anywhere building towards that vision is investible by us.”

• Critiques traditional venture capital practices:

• Raising VC money is not inherently a sign of success.

• “Raising from a VC is just not a sign of success. It’s a milestone, not the goal.”

• Concerned about concentration of capital into a few funds, leaving many founders unsupported.

• “There’s a sense… that the work we do commands a lot less power in the world, a lot less effectiveness than holding the capital to hire that labor.”

• Emphasizes structural, mission-driven investing over chasing categories:

• Invests in companies that prevent workforce dropouts, expand opportunity, and create equitable access to meaningful work.

• Portfolio strategy is diversified, focusing on infrastructure and long-term impact rather than quick wins.

• “We’ve tracked over time what type of founders and what type of solutions we attract and it’s exactly the type of deal that we want to see.”

• Reflects on COVID and societal trends as a lens for her investment thesis:

• “COVID gave a bit of a window into what was possible,” highlighting alternative modes of work and talent distribution that are often overlooked.

Labor, Ownership, and Durable Skills

• Virginie reframes the concept of labor, wages, and ownership:

• “The word labor in and of itself… is something we need to change.”

• Interested in agency and ownership as investment opportunities, especially for small businesses transitioning to employee ownership.

• “For a very long time… there’s been a shift towards knowledge work and how those people are compensated. If you go on the blue-collar side… it’s about wages still and labor.”

• Emphasizes proper capitalization and alignment of funds to support meaningful exits for smaller businesses, rather than chasing massive exits that drive the VC zeitgeist.

• AI fits into this discussion as part of broader investment considerations.

• Childhood experience in family flower business shaped her entrepreneurial and labor perspective:

• Selling flowers, handling cash, and interacting with customers taught “durable skills” that persisted into adulthood.

• “When I think of labor, I think of literally planting pumpkin plants… pulling espresso shots… bringing a customer behind the counter.”

• Observing her father start a business from scratch instilled risk-taking and entrepreneurial spirit.

• “Seeing my dad do this when I was seven… definitely part of that.”

• Skills like sales acumen, handling money, and talking to adults were early lessons that translated into professional confidence.

• Non-linear career paths and expanding exposure to opportunity:

• Concerned that students often see only a narrow range of job options:

• “Kids go out of high school, they can think of three jobs, two of which are their parents’ jobs… Surely because we do a poor job exposing them to other things.”

• Advocates for creating more flexible and exploratory career pathways for young people and adults alike.

• Durable skills and language shaping work:

• Introduction of the term “durable skills” reframes how competencies are understood:

• “I use it all the time now… as a proof point for why we need to change language.”

• Highlights the stigma and limitations of words like “soft skills” or “fractional work”:

• Fractional roles are high-impact and intentional, not temporary or inferior.

• “Brilliant people who wanna work on a fractional basis… they truly wanna work differently… on a portfolio of things they’re particularly good at solving.”

• Work in Progress uses language intentionally to shift perceptions and empower people around work.

• Cultural significance of language in understanding work and people:

• Virginie notes that language carries stigma and meaning that shapes opportunities and perception.

• References Louis Thomas’s essays as inspiration for attention to the nuance and power of words:

• He’ll take the word discipline and distill it into its root, tie it back into the natural world.”

• Robin shares a personal anecdote about language and culture:

• “You can always use Google Translate… but also it’s somebody learning DIA or trying to learn dharia, which is Moroccan Arabic… because my fiance is Moroccan.”

Human-Positive AI, Process, and Apprenticeship

• Virginie emphasizes the value of process over pure efficiency, especially in investing and work:

• “It’s not about the outcome often, it’s about the process… there is truly an apprenticeship quality to venture and investing.”

• Using AI to accelerate tasks like investment memos is possible, but the human learning and iterative discussion is critical:

• “There’s some beauty in that inefficiency, that I think we ought not to lose.”

• AI should augment human work rather than replace the nuanced judgment, particularly in roles requiring creativity, judgment, and relationship-building:

• “No individual should be in a job that’s either unsafe or totally boring or a hundred percent automatable.”

• Introduces the term “human-positive AI” to highlight tools that enhance human potential rather than simply automate tasks:

• “How do we use it to truly augment the work that we do and augment the people?”

• Project selection and learning as a metric of value:

• Virginie evaluates opportunities not just on outcome, but what she will learn and who she becomes by doing the work:

• “If this project were to fail, what would I still learn? What would I still get out of it?”

• Cites examples like running a one-day SNAFU conference to engage people in human-centered selling principles:

• “Who do I become as a result of doing that is always been much more important to me than the concrete outcomes of this thing going well.”

AI Bubble, Transition, and Opportunity

• Discusses the current AI landscape and the comparison to past tech bubbles:

• “I think we’re in an AI bubble… 1999 was a tech bubble and Amazon grew out of it.”

• Differentiates between speculative hype and foundational technological transformation:

• “It is fundamental. It is foundational. It is transformative. There’s no question about that.”

• Highlights the lag between technological introduction and widespread adoption:

• “There’s always a pendulum swing… it takes time for massively transformative technology to fully integrate.”

• AI as an enabler, not a replacement:

• Transition periods create opportunity for investment and human-positive augmentation.

• Examples from healthcare illustrate AI’s potential when applied correctly:

• “We need other people to care for other people. Should we leverage AI so the doctor doesn’t have to face away from the patient taking notes? Yes, ambient scribing is wonderful.”

• Emphasizes building AI around real human use cases and avoiding over-automation:

• “What are the true use cases for it that make a ton of sense versus the ones we need to stay away from?”

• History and parallels with autonomous vehicles illustrate the delay between hype and full implementation:

• Lyft/Uber example: companies predicted autonomous vehicles as cost drivers; the transition opened up gig work:

• “I was a gig worker long before that was a term… the conversation around benefits and portability is still ongoing.”

• AI will similarly require time to stabilize and integrate into workflows while creating new jobs.

Bias, Structural Challenges, and Real-World AI Experiments

• Discusses the importance of addressing systemic bias in AI and tech:

• Shares the LinkedIn “#WearThePants” experiment: women altered gender identifiers to measure algorithmic reach:

• “They changed their picture, in some cases changed their names… and got much more massive reach.”

• Demonstrates that AI can perpetuate structural biases baked into systems and historical behavior:

• “It’s not just about building AI that’s unbiased; it’s about understanding what the algorithm might learn from centuries of entrenched behavior.”

• Highlights the ongoing challenge of designing AI to avoid reinforcing existing inequities:

• “Now you understand the deeply structural ingrained issues we need to solve to not continue to compound what is already massively problematic.”

Parenting, Durable Skills, and Resilience

• Focus on instilling adaptability and problem-solving in children:

• “I refuse to problem solve for them. If they forget their homework, they figure it out, they email the teacher, they apologize the next day. I don’t care. I don’t help them.”

• Emphasizes allowing children to navigate consequences themselves to build independence:

• “If he forgets his flute, he forgets his flute. I am not making the extra trip to school to bring him his flute.”

• Everyday activities are opportunities to cultivate soft skills and confidence:

• “I let them order themselves at the restaurant… they need to look the waiter in the eye and order themselves… you need to speak more clearly or speak loudly.”

• Cultural context and exposure shape learning:

• Practices like family meals without devices help children appreciate attention, respect, and communication:

• “No iPad or iPhone on our table… we sit properly, enjoy a meal together, and talk about things.”

• Travel and cultural exposure are part of teaching adaptability and perspective:

• “We spent some time in France over the summer… the mindset they get from that is that meals matter, and people operate differently.”

• Respecting individuality while fostering independence:

• “They are their own people and you need to respect that and step away… give them the ability to figure out who they are and what they like to do.”

• Parenting as a balance of guidance and autonomy:

• “Feel like that was a handbook that you just offered for parenting or for management? Either one. Nobody prepares you for that… part of figuring out.”

Future of Work and Technology Horizons

• Timeframes for predicting trends:

• Focus on a 5-year horizon as a middle ground between short-term unpredictability and long-term uncertainty:

• “Five years feels like this middle zone that I’m kind of guessing in the haze, but I can kind of see some odd shapes.”

• Short-term (6–18 months) is more precise; long-term (10–15 years) is harder to anticipate:

• “I’m a breezy investor. Six months at a time max… deal making between two people still matters in 18 months.”

• Identifying emerging technologies with latent potential:

• Invests in technologies that are ready for massive impact but haven’t yet had a “moment”:

• “I like to look at technologies that have yet to have a moment… the combo of VR and AI is prime.”

• Example: Skill Maker, a VR+AI training platform for auto technicians, addressing both a labor shortage and outdated certification processes:

• “We are short 650,000 auto technicians… if you can train a technician closer to a month or two versus two years, I promise you the auto shops are all over you.”

• Focuses on alignment of incentives, business model innovation, and meaningful outcomes:

• “You train people faster, even expert technicians can benefit… earn more money… right, not as meaningful to them and not as profitable otherwise.”

• Principles guiding technology and investment choices:

• Solving enduring problems rather than temporary fads:

• “What is a problem that is still not going to go away within the next 10–15 years?”

• Ensuring impact at scale while creating economic and personal value for participants:

• “Can make a huge difference in the lives of 650,000 people who would then have good paying jobs.”

Scaling, Incentives, and Opportunity

• Re-examining traditional practices and identifying opportunities for change:

• “If you’ve done a very specific thing the exact same way, at some point, that’s prime to change.”

• Telehealth is an example: while helpful for remote access, it hasn’t fundamentally created capacity:

• “You’re still in that one-to-one patient’s relationship and an hour of your time with a provider is still an hour at a time.”

• Next version of telehealth should aim to scale care beyond individual constraints:

• “Where do we take telehealth next… what is the next version of that that enables you to truly scale and change?”

• Incentives shape outcomes:

• “Thinking through that and all the incentives… if I were to change the incentives, then people would behave differently? The answer very often is yes, indeed.”

• Paraphrasing Charlie Munger:

• “Look for the incentives and I can tell you the outcome.”

Founders, Pitching, and Common Mistakes

• Pet peeves in founder pitches:

• Lack of research and generic outreach is a major turn-off:

• “I can really quickly tell if you have indeed spent a fraction of a minute on my site… dear sir, automatic junk. I won’t even read the thing.”

• Well-crafted, thoughtful cold inbound pitches get attention:

• “Take some time. A well crafted cold inbound will get my attention… you don’t need to figure out an intro.”

• Big mistakes entrepreneurs make:

• Hiring too early, especially in sales:

• “Until you have a playbook, like don’t hire a sales team… if you don’t have about a million in revenue, you’re probably not ready.”

• Raising too much capital too quickly:

• “You get into that, you’re just gonna spend a lot more time fundraising than you are building a company.”

• Comparing oneself to others:

• “You don’t know if it’s true… there’s always a backstory… that overnight success was 15 years in the making.”

Sales Strategy and Non-Sales Selling

• Approach is contrarian: focus on conversion, not volume:

• “It is not a numbers game. I think it’s a conversion game… I would much rather spend more time with a narrower set of targets and drive better conversion.”

• Understanding fit is key:

• “You gotta find your people… and just finding who is not or should not be on your list is equally valuable.”

• Recognizes that each fund and business is unique, so a tailored approach is essential:

• “The pitch is better when I’m talking to the quote unquote right people in the right place about the right things.”

Where to Find Virginie and Her Work

• Resources for listeners:

• Full Circle Fund: fullcirclefund.io 

• Work in Progress: workinprogress.io 

• LinkedIn: Virginie Raphael 

Where to Access Snafu

• Go to joinsnafu.com and sign up for free.