The New Human Edge

 This Week’s Essay

There is a chart making the rounds from a recent Anthropic report. It maps theoretical AI capability against observed AI usage across every major occupational category — and the gap between the two is striking. But more striking than the gap is where it lives. The highest theoretical AI coverage is concentrated in business, finance, legal, engineering — precisely the professions that for decades were considered the exclusive domain of highly educated knowledge workers. The adoption curve is still early. But the direction is clear.

The skills we optimized for were never the most human ones. Most modern education systems were designed during the industrial era. Their goal was not creativity or originality. It was reliable cognitive execution. Students were trained to solve structured problems, apply known frameworks, execute analytical steps correctly. These skills became the foundation of elite professions. Entire career ladders were built around the ability to process structured information better than others.

For decades, that worked extremely well.

But large language models are fundamentally pattern engines trained on the entire corpus of human knowledge. And pattern recognition across structured problems is exactly where they excel. The implication is not that those professions disappear. It’s that the scarcity moves elsewhere.

The new scarcity isn’t answers. It’s knowing which questions are worth solving.

This is where irreducibly human capabilities start to dominate. The skills that are hardest to formalize — and therefore hardest to automate — are judgment, creativity, storytelling, emotional intelligence, leadership, taste, strategic framing, trust building. These capabilities are nonlinear. They are contextual. They are deeply shaped by lived experience and human interaction. They are precisely the things that allow people to decide what should be built, not just how to build it.

In many ways, the AI era is shifting the value stack from execution to direction.

This pattern is not new in economic history. When spreadsheets became widely available, the differentiator shifted from doing calculations to interpreting what the numbers meant. When Photoshop became ubiquitous, the bottleneck shifted from technical ability to aesthetic taste. When the internet democratized access to information, the premium moved to curation, synthesis, and perspective.

AI is accelerating a similar transition. But at a much larger scale. And much faster.

The most misleading way to frame AI is as a replacement technology. A more accurate framing is that it’s the most powerful productivity amplifier ever built. Think about what happened with navigation. There was a time when being able to read complex maps or navigate by physical landmarks was a distinctly valuable skill. Today, that knowledge is embedded inside GPS. The skill did not disappear. It was absorbed by the tool.

AI is doing something similar for analytical reasoning. Tasks that used to take hours now take minutes. This does not eliminate the need for human input. It raises the leverage of human input. And as the most technically demanding cognitive skills get absorbed into tools, the frontier of differentiation moves to an entirely different galaxy.

The emerging advantage will belong to people who combine two things: deep human capabilities and high AI leverage. The most powerful combination is not AI alone. It is human judgment multiplied by AI execution. A founder with conviction and AI-assisted execution. An investor who combines intuition about founders with AI-driven research. A creator who pairs storytelling instincts with AI production tools. In each case, AI does not replace the human edge. It amplifies it.

Much of the public conversation around AI focuses on what might be lost. Those concerns are real. But they miss something important. Every major technological shift initially feels disruptive because it changes where value lives. What we are witnessing now is not the disappearance of human relevance. It is the redefinition of human advantage.

The traits that matter most going forward are the ones that have always been uniquely human. Curiosity. Empathy. Imagination. Judgment. Leadership. The future may reward precisely the qualities that traditional education systems consistently undervalued.

I won’t share my actual VC thesis around AI just yet. But one area I keep coming back to is what becomes possible at the intersection of content, technology, and venture. Here are some actual trends I am excited about in the AI universe.

1. The creator is becoming a full-stack company.

Steven Bartlett is probably one of the clearest signals here. He is no longer just “a Diary of a CEO podcaster.” His business has become a broader media + venture + creator OS ecosystem — and his company was recently positioned publicly as aiming to become the “Disney of the creator economy,” with creator IP, capital, and technology under one roof. Forbes reported his creator business was on track for roughly $40M in 2025 revenue, while his broader company structure now includes media production and investment arms.

The future is creator as holding company: content as top-of-funnel, community as retention, products as monetization, and venture/investing as balance-sheet upside. Steven is building that model very explicitly.

2. Media is eating venture.

The clearest example is Harry Stebbings’ 20VC — a podcast that became a venture platform managing hundreds of millions of dollars — $8M first fund in 2020, $140M second fund in 2021, $400M third fund in 2024. The podcast created what traditional firms spend decades building: founder trust, proprietary deal flow, and a real-time pulse on the ecosystem. Once you see the model, it’s obvious why it works. Media compounds trust, builds narrative authority, and creates distribution that portfolio companies can immediately tap into.

a16z saw this early — and made their thesis explicit. In late 2025 they built a full media operation inside the firm. Their bet is that narrative and distribution are now as structurally important as capital. The firms that control the story will win the deals.

What makes this moment particularly interesting is that AI dramatically lowers the cost of building this kind of platform. And in a world where AI is exponentially increasing the supply of content, trusted distribution becomes even more valuable. The next generation of venture firms may not start with capital and then build brand. They may start with media, audience, and narrative authority — and only later add capital.

3. Founder-led media is becoming a new go-to-market strategy.

For decades, companies acquired customers through three primary channels: sales teams, partnerships, and marketing. But a different channel is emerging — founders who build in public and turn their thinking into distribution.

Tyler Denk, CEO of beehiiv, is one of the clearest examples. His newsletter Big Desk Energy — where he documents building the company in real time — became what he calls a “real superpower.” Investors started reaching out weekly because of it. His $33M Series B led by NEA in 2024 came at a moment when beehiiv had $10M in the bank and didn’t need to raise — the distribution created the leverage. The company now reaches 400M readers monthly, projects $50-55M in revenue for 2026, and just hired its first ever CMO — Darren Chait from Calendly — as it expands beyond newsletters into a full creator OS.

Tyler drinks his own champagne. And it shows.

The common thread across all three is distribution. Who has it, who is building it, and who is turning it into something more than reach. In the AI era, the most defensible moat may not be technology or capital. It may be the trust of a specific community that knows you, believes you, and keeps coming back. That is very hard to buy. And very hard to replicate.

 This Week’s Number

 425%

The surge in GenAI course enrollments in Latin America in 2025 — the highest of any region in the world, according to Coursera’s Global Skills Report. The region everyone overlooks is learning the skills everyone needs. Fastest.

Community Picks

We couldn’t stop there. Five more from Hernán Kazah:

1. On building

“Going from zero to 95% is very challenging. But the true sustainable value comes from that last 5%.”

2. On venture

“What happens when things go bad? That’s the question founders should ask VCs — but almost never do.”

3. On AI

“Mobile internet didn’t make the internet better. It made it completely different. AI is doing the same thing — but exponential on steroids.”

4. On power law

“We cannot run away from the power law. It doesn’t matter how much we help our companies — most results come from one or two investments per fund.”

5. On decision making

“When there’s too much consensus, we get nervous. If everyone is agreeing, there’s probably an elephant in the room that nobody sees.”

And then there was this — Hernán’s top piece of advice to LATAM founders:

What I’m Loving 

1. John Arnold: China, Energy Markets and Fixing America’s Systems — Invest Like the Best

The most famous energy trader of all time on China’s convergence in robotics, AI and EVs, and the misaligned incentives preventing America from building real infrastructure. The constraints slowing down the US might be the opening that emerging markets — including Latin America — have been waiting for.

Listen here

2. Formula 1 — Acquired

Four and a half hours on how a chaotic, deadly, and gloriously dysfunctional European racing series became one of the greatest business stories in sports — with over 827 million fans globally. Everything we talk about in media, brand building, and distribution — told through the lens of billionaire egos and 200mph cars.

Listen here

3. The Anthropic Economic Index

The report behind the chart that inspired this essay. Anthropic analyzed over a million real Claude conversations to map where AI is actually being used versus where it theoretically could be. The gap is enormous — and the implications for how we think about skills, careers, and competitive advantage are only beginning to land.

Read it here

Thanks for reading,

Olga 

 P.S. If this issue was valuable to you please share it with a founder who needs to hear it. Let’s build LATAM’s next tech leaders—together

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