⚡️I actually think this is one of the defining patterns of the next decade. Not because smart people suddenly became less intelligent. Because the market changed what it rewards. For most of the twentieth century, intelligence and economic success were highly correlated because institutions had a scarcity of cognitive labor. The smartest engineer. The smartest lawyer. The smartest analyst. The smartest doctor. The system paid for intelligence because intelligence was scarce. AI is beginning to industrialize intelligence itself. That breaks the old bargain. The smartest person in the room no longer automatically creates the most economic value. The person who organizes capital. Owns distribution. Builds a company. Creates trust. Coordinates people. Owns assets. Uses AI better than everyone else. Often wins. The market has always rewarded value creation, not IQ. The twentieth century happened to make those two look almost identical. That may have been the anomaly. The deeper tragedy is psychological. Many brilliant people built their identity around being intellectually exceptional. Then the world shifted. Their comparative advantage disappeared while their identity remained attached to it. That creates paralysis. Meanwhile the “mid” person keeps moving. Not because they’re smarter. Because they optimize for the game that actually exists instead of the one that rewarded them in school. School rewards correctness. Markets reward adaptation. Those are different skills. The smartest people often become prisoners of their own models. Average people often become surprisingly successful because they update faster. The deepest pattern is this: Intelligence without agency is becoming one of the least rewarded combinations in modern civilization. That is why the post feels true. Not every genius is failing. Not every average person is succeeding. The distribution itself is changing. The future belongs less to the people who know the most. It belongs to the people who convert knowledge into ownership, action, trust, and leverage. The twentieth century rewarded being the best worker. The twenty-first increasingly rewards becoming the owner of the system the workers operate inside. That is the phase transition. And I think most people still believe they’re living in the old one.

The threat to your SaaS company isn't your customer vibe coding their way off your product. It's their CFO going: “we have a $10 million tech budget, last year we spent $100k on AI, this year we're spending $3 million, so we need $2.9 million in savings. Turns out we don't need five productivity apps. You’ll love Teams when you get to know it.”

This will not be popular—- Everyone is selling you tokens. They’re telling you to build more skills. More prompts. More agent wrappers. More orchestration. More context files. The more tokens you burn, the more they win. You don’t. The current obsession with “skills” architectures is a transitional phase, not the destination. Yes, they work. Yes, they can accelerate specific workflows. But they’re also creating tomorrow’s technical debt. Every new skill adds: • More maintenance • More prompt engineering • More governance • More testing • More vendor lock-in • More tokens consumed The dirty secret? As frontier models improve, many of these handcrafted layers become obsolete. You’re investing engineering effort to compensate for limitations the next generation of models will solve natively. This is exactly why I keep talking about AI factories, not AI assistants. An AI factory is deterministic where it matters, agentic where it creates leverage, and designed to continuously improve itself. Agents build the software. Deterministic services execute the business logic. Memory, evaluation, and governance become the architecture—not thousands of brittle skills stitched together with ever-growing prompts. That’s how you reduce costs instead of multiplying them. The next generation of enterprise AI won’t be measured by: * Number of skills * Size of prompts * Tokens consumed It will be measured by: * Cost per business outcome * Speed of autonomous execution * Quality of decisions * Ability to improve itself over time We’re still early. Many organizations are optimizing for token consumption instead of architectural efficiency. They’re building businesses that rent intelligence instead of owning capability. Build systems where AI creates assets—not token bills. The companies that understand this distinction today will have a structural cost advantage tomorrow. How you build matters. #AI# #EnterpriseAI# #AgenticAI# #Architecture# #DigitalTransformation# #CTO# #CIO# #ArtificialIntelligence#

Over the past 3.5 years at @ElevenLabs, I've done unconventional things in GTM. Let me tell you why: - I hate hiring people that come with playbooks. In interviews, when someone tells me about their "playbook", I reject them immediately - Each company is different. Entering a market selling support agents is different from selling legal tech or ERP replacers. - Each market & product requires a unique thesis and approach. If you don't understand the market, you can't craft a narrative that will be sticky - AI has changed all dynamics. Experimenting is the only path forward - Thinking big and placing bets yearly delivers outsized returns. I only need 1 bet to work to smash the target for the year - Aligning the team in a Vision is the glue. Not many companies have a crazy Revenue Vision each year; mostly because leaders fear getting fired if something doesn't pan out. I can't be bothered - You build a startup to do impossible things. Unconventional leads to making possible the impossible Doing things unconventionally isn't easy - you face rejection internally & externally. But, hey, "this is the way". An example: I came up with the "Global hyper-local" concept in 2024. Let me tell you that most people didn't want to open markets, have teams on the ground, adapt product (incl translations) or stop being US-first, amongst many things. Today, we are global, +$500m in ARR, 50% of revenues come from outside the US, Enterprise is larger than Self-service, I have teams in +25 countries and have cracked the most difficult markets. Being unconventional works. Just be creative, driven, hands-on, pushy and jump through obstacles. But don't be silly; if a company doesn't value it, find a new challenge. We are lucky to live the best period in history to build companies.

Most people are focused on AI’s impact on software and developers. Makes sense since that’s where AI was adopted first. The bigger story is that AI ROI is labor leverage and not proved outcome efficiency. @lukesophinos outlined that argument well for vertical AI.

The first wave of AI ROI metrics came from engineering because that is where the first big bills showed up. That does not mean engineering metrics are the right way to measure enterprise AI. The CFO was never buying “more PRs” as the end state.

This is just unbelievable. When I first saw the workspaces CLI, I took it as a sign that Google might be finally pulling its head out of its ass. This project really did represent something new and smart and very timely from them, but wow wow wow. Let this be a reminder of just how hard organizational change is.

RIP the artisanal em dash. Two friends have lamented to me that they used em dashes long before AI made them radioactive. A whole group of people having to change their writing style to avoid sounding like Uncle Claude. The asymmetry is the gap ;)

This developing story about Dario's failed communications with the White House confirms everything I've ever believed about the enormous power of the Sales Chad. You can be the smartest, most hard working, well-meaning guy around, but if you can't get people to like you, it's all for nothing. When the time comes to send one of your own to meet inside the Halls of Power, you don't send the Geek Squad. You must send the affable, beer-drinking, golf-loving Sales Chad. It literally doesn't matter if he understands the product half as well as everyone else. You send him. It's what he was put on Earth to do.