When Expertise Goes Viral: Why Your Knowledge is the Killer App.
The tectonic shift from tools and talent to encoded insight.
The world has been fixated on software for decades. Every company, every startup, every ambitious solo founder wanted to build the next winning product, the next killer feature. It was all about making, shipping, and deploying code.
But look again.
AI has shifted the ground beneath our feet. The real game is no longer being played at the level of code. It’s now played at the level of knowledge, wisdom, purpose, and meaning.
Xiaoyin Qu, Founder at heyBoss.ai, put it bluntly on Linkedin recently:
“AI products have no moat. You build a new feature today, someone prompts it into existence tomorrow. Innovation isn’t defensible anymore—it’s just… temporary attention. Only a few products (like ChatGPT) have real stickiness—data, scale, habit. Most AI tools? They’re just single-use utilities between a human and a model. No network effect. No real retention. And the truth is: Once everything can be built, nothing feels special anymore. That’s why every founder (including me) is on Twitter, TikTok, or LinkedIn, performing for attention. We’re not building products anymore—we’re running content circuses. Because what we sell is no longer scarce. The next gold rush isn’t AI software—it’s AI-powered human service.” —Xiaoyin Qu
And the highly influential Stanford professor, Andrew Ng, told Business Insider that AI has made the coding part easy:
“Coding is no longer the challenge. Things that used to take six engineers three months to build, my friends and I, we’ll just build on a weekend... The bottleneck is deciding what do we actually want to build.” –Andrew Ng
In the age of generative AI, building software is nearly instant and universally accessible. The unique technical advantage that once belonged to a handful of engineers now sits inside every browser tab. We’re not just using software anymore. We’re turning our deepest knowledge, expert judgment, and lived experience into living organizational systems.
You, your company, your teams and workflows, are becoming a kind of Living Software — encoding all the tacit know-how that used to reside in a few minds and scattered notes. This is the true revolution of AI.
What’s Changing? Everything (And it’s internal)
The first mistake is thinking the revolution is external to you (ex - smarter models and acquiring tech stacks). This is how we are used to thinking of software and technology.
But AI is different. It’s not just another monthly SaaS subscription you’re buying into. It’s much deeper.
Most of what gave organizations their edge — that rare know-how, creative intuition, the unwritten culture of “how we do things” — is now extractable, combinable, and scalable using Gen AI.
Your deepest value used to be what only you (or your team, or your culture) could do. Now, your edge comes from surfacing, encoding, and recombining that logic into living, learning systems that can far exceed the sum of their original parts.
Living Software is about transforming organizational knowledge into adaptive systems. When you do this, you’re not just saving what’s precious—you’re making it scalable, robust, and always improving.
This is institutional memory remixed as living code: strategic insights, best practices, judgment calls, and decisions are captured, coordinated, and actionable across your entire organization and brand touchpoints.
As Matt Wood (PwC’s Global Tech Officer) described to Nicholas Thompson (Atlantic CEO) on a recent podcast:
“The biggest shift is that [AI and expertise] compound and move the technology closer to expertise... The opportunity to amplify that identity with artificial intelligence, in my opinion, is once in a generation. And it is in my opinion where the invention is going to happen; where the innovation is going to happen. It’s not going to happen at the technology layer, [it’s] going to happen inside the organizations. It’s going to happen inside the firm.” –Matt Wood
Wood adds that this isn’t just a matter of efficiency or workflow improvement; it’s a black swan event, he says. It’s where the capacity for problem-solving rapidly grows, while the technical expertise shrinks.
The result?
Organizations become Living Software, where deep (often hidden) wisdom can be extracted, recombined, and scaled throughout systems, communities, and ecosystems.
This gives rise to a paradox: AI makes building software easy, but it also makes lasting value harder to achieve. As software features become copyable overnight, margins collapse and differentiation evaporates.
So, what remains scarce?
Your human responsibility, judgment, unique expertise, and trust. AI can do many things, but it cannot take responsibility or make nuanced judgment calls in the face of uncertain outcomes.
Knowledge: The Cosmic Perspective
The revolution at hand is larger than business or even technology. David Deutsch, famed physicist and philosopher, talks about the cosmic significance of human knowledge:
“In the first 14 billion years of the cosmos, the rule was that big things affect small things and small things do not affect big things much. After the phase change, everything is determined by small things. The determining factor is not mass or power or energy, but information. And specifically, the kind of information that has physical effects—namely knowledge.” –David Deutsch
Generative AI may well be the most potent technology ever created because of this. A small model, an encoded insight, a single piece of living wisdom can ripple through industries, be combined and recombined with other knowledge, and tear through entire economies now, thanks to Gen AI.
Framed this way, Deutsch might even call the era of Gen AI a phase change in the universe itself. Knowledge, according to Deutsch — especially the explanatory, causal knowledge humans create — is the ultimate force in the cosmos.
In other words, Generative AI is not just a new tool — it’s the grand shift from matter and energy to information and knowledge. If knowledge is causal, creative, and world-shaping, then we’re now in an era where what you know — and how expertly you encode and refine it — can literally shape the world (and beyond).
Generative AI isn’t just about “automating jobs” — that’s just its most obvious utility based on our current understanding of what we’re dealing with. The deeper read is that Gen AI is helping organizations and societies climb Deutsch’s “cosmic ladder,” moving from brute force to the kind of knowledge that lets you rewrite not just your business processes, but your place in history.
“Creativity marks a pivotal turning point in cosmic history, representing a phase change that fundamentally alters the universe’s trajectory. It introduces the possibility of intentional influence, innovation, and the generation of new information—elements that can profoundly affect the universe’s evolution.” –David Deutsch
Transitioning From Individual Genius to Systemic Wisdom
Deutsch sees knowledge as “information with causal power.” It’s not just what’s in your head—it’s what changes a system, what shapes reality. The power of explanatory knowledge, the kind only humans (for now) can generate, is the fact that it explains the seen in terms of the unseen.
Generative AI lets organizations move from tacit, individual know-how to distributed, remixable expertise. The hard part — surfacing, testing, encoding —now becomes the main game.
“We can let our ideas die in our place.” — David Deutsch, quoting Karl Popper
In biological evolution, as Deutsch points out, every failed idea meant a failed organism. However, when it comes to human innovation, the ability to criticize, discard, and improve ideas—without fatal risk—creates exponential liftoff. The differences between these two outcomes are profoundly radical.
The lesson? Build systems and cultures that embrace a tradition of criticism, remixing, and error correction.
What This Means For You
Don’t let this moment pass you by while waiting for AI products to mature. It doesn’t matter how smart models get from here. They are already smart enough to do what really moves the needle: how you encode, capture, and curate expertise — the contexts, mental models, and frameworks that allow your human creativity soar alongside the machine.
You shape the new currency.
Your team, your org, your community—their wisdom, traditions, rituals, and improvisational know-how—now have a chance to become immortal, alive, compounding.
The “killer app” is organizational knowledge, made visible, networked, and always improving.
Framework: Encode What’s Alive in You
Start where value is moving:
Start with your purpose: Think of a challenge where your unique judgment matters—something others get wrong.
Surface what’s hidden: Ditch the formal job description. What do you really do when things get tough? What do you notice or question that no one else does?
Pre-Gen AI was about what was visible. Now it’s about what you can’t see. Codify your paths: Diagram your logic tree, narrate your decision stories, or design prompts you wish your apprentice would use.
Iterate with AI: Give your encoded insight to digital systems. See what they misunderstand. Re-explain. Prune. Refine.
Connect and remix: Invite peers to critique, remix, and extend (or do it yourself if you’re self-reflective). For each round, add more context so the deeply tacit becomes shareable, alive, scalable, and collaborative.
Focus on talent: Develop talent for judgment, curation, coordination, and risk—not just technical execution.
Redesign roles: Move roles toward orchestration and decision-making.
Build criticism: Foster continual feedback, critique, and abandonment of bad ideas—let learning compound.
The “Why Should People Care” Test
If you can’t say why people should care about your Living Software — why it’s different, unique, and urgent in the marketplace, you aren’t ready for what’s next.
Remember: The true bottleneck is not building product anymore, it’s building purpose, encoding insight, and compounding wisdom at scale.
Who Will Win?
It’s not the fastest coder or the biggest AI lab. It’s the people and teams who can turn what’s uniquely alive in them— judgment, story, purpose — into systems that learn, adapt, and leap past what any one mind could do alone.
Think about how, in 2022, a small, no-named AI lab called OpenAI scooped the monstrous Google, the undisputed king of AI at the time.
Generative AI is the cosmic shift inside every business shaped by knowledge. The next frontier isn’t in how well you use software—it’s in how well you become it, encoding your best insights and shaping them into connection, curation, and growth.
“Optimism is not blind hope, but the explanation that all failures are due to lack of knowledge—which is, in principle, attainable. Thus, progress is always possible unless we give up or stop seeking knowledge. Knowledge is infinite and self-expanding. Each advance in understanding opens new realms of inquiry, making the journey of knowledge never-ending and of boundless potential” –David Deutsch
The revolution is not outside you, it’s within you — encoded, remixed, and reborn. Will your Living Software be part of the phase change?
If you’re a subscriber, let’s continue this deep conversation in the chat area of my Substack. BYOK (Bring Your Own Knowledge!)
So, a few thoughts:
1. ChatGPT has achieved a bunch of scale, but in terms of sheer model performance, Claude has wider adoption in the tech industry, the Alpha Arena investment test is being dominated by other models (https://nof1.ai/). I think each model and / or tool is achieving something different but there are multiple killer apps out there which are likely to iterate fast and improve fast.
2. That is the reason why I feel solo vibe-coding-based entrepreneurship, especially for those of us with no computer science and no founder experience, is unlikely to be the best way into the AI-driven economy. I know I can't out-solution or out-iterate Aravind Srinivas. And I don't want to, but I want to develop enough AI literacy to speak the language, uncover truths, and be a good role model to others.
3. Humans scale together. Agree that individual knowledge premiums may go down, but there are significant biases still in the information that AI is trained upon. Leading-edge scholarship and journalism are sitting in places where training algorithms aren't going to touch. We've got to engage with AI wisely and yes, not hoard info but use judgement, stay curious, be prepared to look for insights in places that aren't easy to find, and combine voices / scale perspectives to get better results together.
Fascinating article Corrales. I really like your idea of Living Software, baed on our ability to encode our knowledge and expertise into AI.
I am curious to ask you, how do you see the practical development of what you suggest at point 6. "Focus on talent: Develop talent for judgment, curation, coordination, and risk—not just technical execution."