There are certain words so central to the human experience—love, success, happiness—that we assume we understand them without ever stopping to dissect them. We just know, as if through osmosis or collective wisdom, what they mean.

Trust is one of those words.

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We invoke it constantly. We say we need it, want it, lost it, found it. But have you ever actually examined what trust is? Could you define it accurately? Explain it to an alien and make them understand?

The prevailing wisdom treats trust like a leap of faith—something you blindly give in hopes of getting it back. We treat it like a gift with transformative power. But is trust really that esoteric? Or are we unknowingly playing a game with rules designed to make us fail?

What Trust Actually Is (And What We're Getting Wrong)

I used to think of trust as a nebulous feeling—this hope-based belief that someone won't intentionally harm me. It felt rooted in general optimism about human goodness, and ultimately, outside my control. You surrender to a person or situation and wait to see if they'll choose to be good.

The odds are decidedly not in the giver's favor with the surrender approach, and I have been burned enough times to wonder if there's a different way. A better way.

The obvious alternative—trust no one—is the conclusion most of us are forced to reach. But that shrinks your world and limits your options. You end up safe but small.

Paul Zak's research with economist Stephen Knack confirms this: trust is among the strongest predictors of a country's wealth. Nations with low levels of trust tend to be poor.¹

Why? Because trust reduces transaction costs. In high-trust societies, you don't need a lawyer and policeman for every interaction. Deals happen faster. Investment flows more freely. Growth accelerates.

Zak and Knack found that growth rises by nearly 1 percentage point for each 15 percentage point increase in trust.¹ Countries like Norway and Sweden, where over 60% of people say "most people can be trusted," have dramatically higher GDP per capita than low-trust nations.²

But this isn't just macroeconomics—it's your daily life.

Every hour you spend verifying, double-checking, and protecting yourself is an hour not spent creating value. High-trust relationships let you move faster, take bigger swings, and reap compound returns.

Warren Buffett and Charlie Munger built a $630 billion empire on this foundation. At the 2024 Berkshire Hathaway annual meeting, Buffett said of Munger: "Charlie in all the years we worked together, not only never once lied to me, ever, but he didn't even shape things so that he told half lies or quarter lies to sort of stack the deck in the direction he wanted to go."³ That clarity—that absolute trust—freed them to debate honestly, decide quickly, and compound returns for six decades.

Trust isn't naive—it's strategic.

So I wanted to find a better approach—one that doesn't require blind surrender but doesn't sentence you to permanent isolation either. I started my research at the very beginning: the dictionary definition.

trust /trʌst/
noun
​firm belief in the reliability, truth, or ability of someone or something.

I thought I knew this. Truth, yes. Reliability, sometimes. But ability? I'd never consciously considered competence as fundamental to trust—especially not in personal relationships. How do you measure someone's ability to be trustworthy when you've just met them? It feels like a wait-and-see kind of game.

But here's what changes everything: that "or" in the dictionary definition should be an “and”. Without all three elements, trust is lopsided, brittle. With all three, trust becomes an evaluation—not a stroke of emotion, but a judgment about structure, incentives, and capacity.

Thankfully, academic definitions land us where common sense should already live. Organizational researchers Mayer, Davis, and Schoorman describe trust as the willingness to be vulnerable to another person based on positive expectations of their behavior.⁴ That formulation captures the two halves we must manage: vulnerability and expectation. And those expectations rest on three pillars:

1. Competence – Can they actually deliver what they promise?
2. Integrity – Do their actions align with their words
3. Benevolence – Do they genuinely care about your wellbeing, not just their benefit?

What's remarkable—and somewhat ironic—is that we're only starting to understand this systematically. The foundational research paper defining these three components wasn't published until 1995.⁴ For thousands of years, we've been building civilizations, forming partnerships, and creating institutions based on trust, yet we've only recently begun to articulate its actual structure.

Trust In The Wild: A Game Theory Approach

When you strip trust down to incentives—removing emotion, or idealism—you arrive at the two simplest models human beings fall into: avoidance of harm and coordination for gain. Game theory captures both with surprising clarity.

1. The Prisoner’s Dilemma — Trust Under Risk of Betrayal

The prisoner's dilemma is a classic game theory scenario: Two people are arrested and interrogated separately. Each can either cooperate with the other (stay silent) or defect (betray the other).

• If both cooperate, they each get a light sentence.
• If one defects while the other cooperates, the defector goes free while the cooperator gets maximum punishment.
• If both defect, both get moderate sentences.

The rational move in a one-time game is always to defect—but when the game repeats, everything changes.

Robert Axelrod's famous tournaments in the 1980s tested strategies for the repeated prisoner's dilemma. He invited game theorists to submit computer programs that would compete against each other over hundreds of rounds. The winner—submitted by mathematician Anatol Rapoport—was the simplest strategy entered: Tit-for-Tat.⁵

Tit-for-Tat follows two rules:

1. Cooperate on the first move
2. Then do whatever your opponent did on the previous move

What made it so effective? Axelrod identified four key properties: it was nice (never defected first), retaliatory (punished defection immediately), forgiving (resumed cooperation after the opponent cooperated), and clear (easy for opponents to understand and predict).⁶

The "forgiveness" aspect is crucial. As Axelrod wrote: "What accounts for Tit for Tat's robust success is its combination of being nice, retaliatory, forgiving, and clear."⁷ Strategies that punished defection but never forgave got trapped in endless cycles of mutual defection. Tit-for-Tat's willingness to resume cooperation after just one retaliation allowed relationships to recover from mistakes.

One-time interactions incentivize defection (take the money and run). Repeated interactions incentivize cooperation because your reputation follows you—and forgiveness makes sustained cooperation possible even after ruptures.

2. The Stag Hunt — Trust Under Coordination and Shared Ambition

Before “stag hunt” entered modern entrepreneurial vocabulary, it was a foundational thought experiment in game theory—introduced by Jean-Jacques Rousseau and later formalized by economists and mathematicians studying cooperation.

The stag hunt illustrates a different kind of trust challenge than the prisoner’s dilemma. Where the prisoner’s dilemma is about avoiding betrayal, the stag hunt is about coordinating ambition.⁸

Here’s the setup:

Two hunters can either hunt a stag or a rabbit.

• A stag provides a much larger payoff—but it requires both hunters to cooperate. One person cannot catch a stag alone.
• A rabbit can be caught individually—small, predictable, guaranteed.

The outcomes:

• Both cooperate → they catch the stag → both win big.
• One defects (hunts a rabbit) → the other is left exposed and gets nothing.
• Both defect → each gets a rabbit → safe, but small outcomes.

The tension is simple but profound: If you believe the other person will show up, the stag is the superior choice. If you doubt them—even slightly—the rabbit is safer.

This is the essence of trust in high-stakes environments: You can’t build anything meaningful if you’re surrounded by rabbit hunters.

The stag hunt is the formal game-theory backbone that people like Naval Ravikant gesture toward when describing high-trust societies. Naval’s interpretation—that coordinated trust produces outsized returns—aligns with the underlying model, but the real intellectual lineage comes from Rousseau’s framing of mutual dependence:

Great rewards require trust; trust requires the belief that others will pursue the same goal. (Rousseau, “A Discourse on the Origin of Inequality,” 1755)

In modern game-theory terms, stag hunts are assurance games: the biggest win requires cooperation, but cooperation requires confidence—not fear.

It’s one of the cleanest metaphors for ambitious partnership: you cannot build anything meaningful with someone who chooses personal safety over coordination. Trust here is not faith—it’s a shared willingness to pursue the larger payoff.

The tragedy in low-trust environments is that everyone rationally settles for rabbits—safe, small, predictable—because the risk of misalignment is too high.

But the real returns—emotional, financial, creative—belong to the people who can find others willing to show up for the stag.

How Trust Is Built: The Three Mechanisms

When you reframe trust as a three-part structure with identifiable elements, it transforms from a nebulous feeling outside your control into concrete scaffolding you can build deliberately, piece by piece.

Across disciplines, the research converges on three mechanisms that determine whether trust grows, stalls, or fractures.

1. Consistency Over Time: The Small Signals That Rewire the Brain

Charisma attracts. Consistency sustains.

This is where most of us get it wrong. We confuse charisma for trustworthiness. Someone interviews brilliantly, makes great first impressions, says all the right things—and we mistake performance for personality. But trust isn't built in moments of peak performance. It's built in the mundane reliability of hundreds of small interactions.

Paul Zak's research on oxytocin shows that trust builds through repeated reliability, not impressive performances. Small signals of dependability—returning calls when promised, honoring confidences, following through on minor commitments—literally rewire the brain toward safety. Each reliable interaction releases oxytocin, reinforcing the trust loop.⁹

Arthur Aron's famous research on interpersonal closeness also shows that trust and intimacy build when vulnerability is mutual and gradual.

People build closeness by exchanging increasing levels of personal information over time (not all at once). Structured exercises—like the 36 questions that create rapid interpersonal closeness—work not because they are mystical, but because they pace reciprocal risk.¹⁰

That reciprocity reduces asymmetry and converts vulnerability into a shared resource.

At care/of, we've essentially turned this model on its head with our Proust questionnaire approach. You share thoughtful answers upfront, but anonymously. Privacy balances vulnerability—you can be your truest self without real consequence, and only people who feel drawn to your character will reach out. It's depth-first by design, but safety-first in execution.

2. Skin in the Game: The Currency of Real Trust

It's easier to trust when everyone has something to lose.

That's the essence of "skin in the game," as popularized by Nassim Nicholas Taleb, a mathematical statistician and former options trader known for his work on randomness, probability, and uncertainty.

In a lecture given at Stanford University, he argues that people making decisions should also bear the consequences of those decisions. In his words: "Nobody should put someone else at risk without having harm to himself."¹¹

He goes on to share a story from Brazil where they discovered they could lower the rate of helicopter crashes when the engineers were required to randomly take a half-hour ride each month in those helicopters. Suddenly, safety standards improved dramatically.

Taleb's idea underscores exactly why skin in the game builds trust—when both people (or all parties) have real exposure to outcomes, they're more likely to act in alignment, not exploitation.

The same principle applies to relationships. You want partners who have as much to lose as you do. As Taleb writes: "What matters isn't what a person has or doesn't have; it is what he or she is afraid of losing."

When evaluating trust, filter for aligned incentives, not just absence of bad motives. Consider these iconic partnerships:

William Procter and James Gamble formed Procter & Gamble in 1837. Procter was a candlemaker, Gamble a soapmaker, and they were brothers-in-law. It was their father-in-law's suggestion to partner, but it was their shared values that made it work—P&G was one of the first companies to give employees profit-sharing. By combining skills and resources, they could offer a wider product range without competing. Equal risk, complementary skills, aligned values.¹²

Chris Savage and Brendan Schwartz founded Wistia in 2006 as best friends and equal partners (50/50 split). More than 15 years later, they're still best friends running the company together. Their secret? "We decided early on that our friendship always comes first and the business comes second." They pay themselves the same salary despite different roles, specifically to avoid resentment. They maintain equal power sharing. As Chris wrote: "In stressful times, inequity in compensation is an easy thing to fixate on... We've found that paying ourselves the same has helped to stop resentment from creeping in."¹³

When both people have real stakes, trust becomes structural, not sentimental. You're not betting on personality—you're betting on alignment.

Economists call this "relational contracts"—agreements sustained not by enforcement, but by repeated mutual gain and loss over time.¹⁴

3. Structural Safeguards: Design for Trust or Safety

Here's the empowering reframe: You don't need to trust blindly.

You can design structures where you're protected whether trust holds or fails; where both parties have skin in the game and neither can cause catastrophic harm. This paradoxically enables more trust because the downside is contained.

• Contracts define expectations clearly, reducing the need for mind-reading.
• Reversible decisions and exit clauses make staying a choice.
• Escrow holds money with a third party, enabling trade without full trust.
• References let others vouch for reliability, essentially borrowing trust.
• Diversification ensures no single failure can destroy you completely.

With good structures in place, you can take calculated risks and create opportunities for trust to be earned in layers, matching trust level to stakes.

A coffee date requires minimal trust—one hour in a public place. A weekend trip requires significantly more. A move-in decision requires deep trust. Access naturally escalates with proven reliability.

The same applies in business. Freelance project before equity partnership. Small check before leading a round. Milestone-based payments before lump-sum contracts.

Why this is empowering: You can take more smart risks because structure contains the downside. More risks lead to more learning, which leads to better calibration, which leads to genuine trust developing.

Operating with Calibrated Trust

In 2012, Google launched Project Aristotle to understand why some teams dramatically outperformed others. They studied 180 teams over two years.

The single most important factor? Psychological safety—a shared belief that the team is safe for interpersonal risk-taking.¹⁵

Amy Edmondson, who coined the term, found that even extremely smart, high-powered employees needed a psychologically safe work environment to contribute fully.¹⁶ What creates psychological safety?

• Conversational turn-taking (roughly equal airtime for all members),
• Leaders modeling vulnerability (admitting when you don't know something),
• Clear standards without punishment (high expectations with space to learn), and
• Responsive listening (actually acting on feedback and concerns).

This isn't about being nice and polite. It's about creating conditions where people can be candid about problems, mistakes, and new ideas without fear. Teams with high psychological safety are more innovative, more productive, and better at knowledge-sharing.

Psychological safety is a structural element—it's trust by design, not hope.

The care/of Method: Trust by Design

Our product is a structural answer to the trust problem that success creates. We don't remove the problem; we redesign the field of play.

Privacy as scaffolding. Anonymity and aliases aren't secrecy for secrecy's sake. They remove surface-level signals that invite extraction and replace them with curated profiles where values—rather than status—are the default metric.

Slow reveal as safety. Thoughtful matches, guided prompts and controlled disclosure empower members to test alignment before risking vulnerability. That pacing is how competence, integrity, and benevolence can be observed, rather than assumed.

Vetting creates baseline safety. Evaluation happens in layers. Referral means character was vouched for by someone already in the network. Internal verification confirms identity without broadcasting it. Profile completion signals investment—you spent the time. Feedback tracking monitors patterns over time, separating one-time awkwardness from consistent poor behavior.

Mutual investment baked in. All members participate; they build thoughtful profiles, they give feedback, they invite their trusted peers to engage with the process. It's not a one-time consumer transaction. It's a shared relational economy where all of us have skin in the game.

In short: care/of turns product features into philosophical commitments. Privacy, curation, pacing, and shared accountability aren't just UX choices—they're the load-bearing beams of a framework that empowers high-achievers to build trust without risking unnecessary exposure.

This is not just matchmaking—it's engineering trust at scale.

Sources & References