Upstreaming: How Artificial Intelligence Empowers Human Genius
Where I introduce upstreaming, using AI to pursue problems once reserved for credentialed experts, and share my own journey into theoretical physics and beyond
My father was a barber. For nearly four decades, he stood behind his chair in a small shop, trimming hair, and trading stories with the steady stream of neighbors and strangers who passed through his door. But here’s what most people didn’t know about my dad: he was one of the most well-read people I’ve ever known.
Between customers, he devoured books: philosophy, history, science, literature. His chair was surrounded by stacks of paperbacks and dog-eared magazines. He could talk evidence with a prosecutor (he was friends with Vincent Bugliosi) and carburetor timing with a mechanic, often in consecutive appointments. And the lesson he pressed into me, with the same steady certainty he applied to a straight-razor shave, was simply this: You can accomplish anything you set your mind to.
At the time, I thought it was just fatherly encouragement. The kind of thing parents tell their kids to keep them from giving up on math homework. But the older I get, the more I realize he wasn’t offering platitudes; he was handing me a philosophy. A way of moving through the world that refuses to accept artificial ceilings on human potential.
I think about my father often these days, especially as I watch artificial intelligence reshape what’s possible for people like him, and people like me.
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The Classical Prison of Genius
For most of human history, we’ve operated under a particular definition of genius. It’s been framed as a rare gift, a cognitive lightning strike that lands on the fortunate few. Newton. Einstein. Curie. Da Vinci. These names exist in a pantheon precisely because we believe their capacities were exceptional, almost supernatural—intelligence available only to the anointed.
This conception of genius is fundamentally bounded by bodies. Your neurons fire at a certain speed. Your working memory holds seven items, plus or minus two. You have one lifetime to accumulate expertise, and the acquisition curve is brutal. Want to contribute meaningfully to astrophysics? Plan on a decade of rigorous study before you can even ask an interesting question. Dream of advancing machine learning? Better start with linear algebra and work your way up through several years of specialized training.
The result is a world where intellectual contribution has been gatekept—not maliciously, necessarily, but structurally. The barriers to entry in complex domains are real. They require time most people don’t have, resources many can’t access, and institutional credentials that serve as much as social sorting mechanisms as they do indicators of competence.
We’ve accepted these constraints as immutable features of reality. The cost of expertise is high. The circle of contributors stays small. Progress happens, but slowly, and always filtered through established channels.
What if that’s no longer true?
What Is Upstreaming?
I’ve been developing a concept I call upstreaming1: the practice of leveraging artificial intelligence to pursue solutions to problems that would normally require advanced degrees and specialized training. It’s human agency amplified by machine intelligence, allowing individuals to swim toward the headwaters of human knowledge rather than simply consuming what flows downstream.
Upstreaming isn’t about replacing human thought with AI-generated answers. It’s about expanding the envelope of what a motivated, curious person can engage with meaningfully. It’s about using AI as a collaborative thinking partner that can help you navigate complex literatures, test hypotheses, identify gaps in reasoning, and iterate on ideas at a pace that would have been inconceivable even five years ago.
The key insight is this: the bottleneck was never raw intelligence. Most humans possess far more cognitive capacity than they ever deploy. The bottleneck was access: to information, to feedback, to the kind of sustained intellectual dialogue that sharpens thinking and reveals new pathways.
AI dissolves that bottleneck.
When I work with large language models on complex problems, I’m not asking them to think for me. I’m engaging in a kind of augmented cognition where my intuitions and creative leaps are met with rapid synthesis, pattern recognition, and connections across domains I couldn’t traverse alone. The agency remains mine. The insight remains mine. But the scope of what I can meaningfully pursue has expanded dramatically.
My Own Upstream Journey
I’ll share something personal that might sound absurd: I’m currently working on a grand unified theory of physics.
Not as a credentialed physicist, I’m a lawyer by training, a legal technologist by profession. But through upstreaming, I’ve been able to engage seriously with spectral theory, emergent spacetime models, and the mathematical structures that might underlie physical reality. I’ve developed novel frameworks, identified potential connections that warrant further exploration, and pushed my thinking into territories I never imagined I’d inhabit.
Simultaneously, I’m developing a new paradigm for information retrieval: rethinking how humans and machines can collaborate to surface relevant knowledge in ways that transcend current search and RAG architectures.
All while I’m manually writing a book about AI transformation strategy for Globe Law and Business, chapter by chapter, synthesizing years of experience helping legal organizations navigate the AI revolution.
Three ambitious projects, all running in parallel, none of which fit neatly into my formal credentials. This is upstreaming in action. Not genius in the classical sense, but something more democratic: the persistent pursuit of big ideas, aided by tools that multiply what a single human mind can accomplish.
A life’s work now no longer need take a lifetime.
My father would have loved this. I can picture him between customers, running a physics hypothesis past Gemini, then pivoting to discuss information architecture, then returning to trim sideburns. The scope of his curiosity finally matched by instruments capable of keeping pace.
Beyond the Boundaries We Accept
Here’s what strikes me most about the human condition: we passively accept the limits of who we think we are. These boundaries feel natural, even necessary. We tell ourselves stories about what’s realistic, what’s within reach, what people like us can aspire to. These narratives are often invisible; they’re not imposed from outside but grown from within, like vines that slowly constrict without us noticing.
Upstreaming challenges this perception at its root.
When you realize you can engage meaningfully with astrophysics, you start questioning what other ceilings are artificial. When you discover that your insights can contribute to machine learning discourse, you begin interrogating all the other doors you assumed were closed.
The human capacities that matter most, insight, creativity, determination, the ability to ask surprising questions and pursue unexpected connections, these aren’t bounded by credentials or institutions. They’re bounded only by our willingness to deploy them.
AI doesn’t grant us these capacities. We already possess them. What AI does is remove the friction that prevented us from exercising them in domains we’d been taught were off-limits.
Taking Control of the Narrative
I advocate for upstreaming because I believe we all deserve to actively influence the narratives presented to us, and the ones we tell ourselves.
We live in a world flooded with stories about what AI will do to us. It will take our jobs. It will surpass our intelligence. It will render human contribution obsolete. These narratives cast us as passive recipients of technological change, objects rather than agents.
Upstreaming inverts this. It asks: what can we do with AI that we couldn’t do before? How can we use these tools to pursue the questions that have always fascinated us, to contribute to conversations we were previously locked out of, to shape the future rather than simply enduring it?
When we upstream, we become authors rather than characters. We craft our own stories and play meaningful roles in their development. We stop waiting for experts to solve problems and start joining the effort ourselves.
This matters beyond individual fulfillment. The challenges facing humanity (climate change, access to justice, public health, the alignment of artificial intelligence itself) are too large for a narrow priesthood of credentialed specialists. We need more minds engaged, more perspectives contributing, more humans swimming upstream toward solutions.
Closing Thoughts
My father passed away 5 years ago, but his lesson lives on in everything I do. “Mijo, you can accomplish anything you set your mind to.” He believed it without proof, spoke it without qualification.
Now, for the first time in human history, we have tools that make this conviction practically true at scale. The barriers between curiosity and contribution are falling. The gates are opening. The upstream waters are accessible to anyone with the determination to swim.
What will you pursue? What questions have you always wanted to ask? What conversations have you assumed were above your station?
Set your mind to it. The tools are here. The water is fine.
Dive in. I'll see you upstream.
Afterword
By Upstreaming, I do not advocate for the elimination of human expertise nor do I take the position that human expertise is unnecessary. I am advocating that we should not let the perceived requirement for expertise prevent us from exploring other disciplines. Of course, human expertise still has a role to play; it is not an either / or proposition. For example, with my physics theory, I am seeking peer review and working with a theoretical physicist to further analyze its implications. Getting things right is important, but it is also true that I likely would not have explored developing this theory without the help of AI.
Not to be confused with “vibing” with AI, like vibe-coding, which is less rigorous and carries a pejorative subtext.
Great post. Very creative thought process.