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Expertise as a River

Jason's framework for thinking about skill, identity, and career in the age of AI: expertise is not a fixed asset you can shelf and draw down from — it's a fast-moving river that you must constantly paddle through. The professionals most at risk right now are not those with shallow skills, but those who have tied their identity to a specific skill set rather than to their capacity to learn, judge, and apply. The answer isn't defending your craft against AI. It's holding expertise with an open hand.

From newsletter #286 "Expertise is a river" (2026-02-11).

The Situation

It used to be that expertise was earned through extensive study, experience, and reflection. But these days, it seems that hard-fought knowledge and skill has never had a shorter shelf life.

Identity pillars Jason names: physical traits, origins, people we're close to. And what we're good at. The last pillar is the one most under threat. Every week brings another CEO announcement about transforming into an "AI-first company" or declaring that any new hire must first prove AI can't do the task. Each day, the set of things AI cannot do shrinks.

He writes from concrete experience — juggling three AI assistants simultaneously: a Claude Code instance building an art exploration website, a terminal-based agentic AI running from his home computer, and browser Claude as his troubleshooting guide. The vibe is the early internet: downloading things you don't fully understand, running programs, piecing together information from forums, moving fast, never sure what's true. The stakes back then were low (a virus, a bad keygen). The stakes now — bank accounts, a business, protected email addresses — are meaningfully higher. And yet the greatest risk isn't in experimenting. It's in sitting still.

When Your Expertise Becomes a Commodity

The commodification hits programmers especially hard because they are closest to the engine of change. Jason quotes a senior engineer on LinkedIn:

"I am not sure if other developers feel like this. But I feel kinda depressed. AI coding is incredible. I have never found coding more fun. The stuff you can do and the speed you can do it at now is absolutely insane. But at the same time. The skill I spent 10,000s of hours getting good at, programming, is becoming a full commodity extremely quickly. There's something disheartening about the thing you spent most of your life getting good at now being mostly useless."

The same grief shows up in graphic designers watching AI generate images, writers seeing chatbots draft copy, lawyers watching document review get automated. The fear is real. Jason's move is not to dismiss the fear — it's to show that the programmer is misunderstanding the field he is in.

What Technology Has Always Done

Every technology commodifies human labor and expertise in a given domain so more can benefit. The tablet over human memory. The camera over the paintbrush. The spreadsheet over hand calculations. This is not new.

The new adopters of any technology will never have the same appreciation for the history, craft, and edge cases as the old masters. Which means — counterintuitively — you will be able to do more with the technology than they can, assuming you're willing to be less precious about what you do now and act with a beginner's mind.

Jason quotes another engineer answering the question "why do I even exist?":

That's the wrong question. The correct question is "why is my employer paying me?" Your employer is paying you to turn well-defined requirements into working code to either make them money or to save them money. At higher levels you are responsible for taking your $n number of years of experience to turn more ambiguous, more impactful, larger-scoped projects into working implementations that are done on time, on budget and meets requirements.

The reframe: your value was never in typing the magic incantations. Typing was never the hard part. The thinking was. Judgment, context, the ability to navigate ambiguity and make decisions that matter — those are still yours. The technology just strips away the parts that are increasingly mechanical. You're going up an order.

The River

The central metaphor of the piece:

Expertise is not a magic potion you can titrate, keep on your shelf, and pour from when you need it. Expertise is a fast-moving river that can take you to wonderful places, but that you must constantly paddle through lest you are consumed by its currents.

The river doesn't stop flowing because you earned a certification or spent 10,000 hours. It keeps moving. What you built yesterday is upstream; the water you're standing in now is new; downstream is still unknown. Paddling is the permanent condition.

Going to a library and checking out a book used to be how you got information. Now an AI researches 50 websites in 30 seconds. That doesn't mean you're no longer a researcher. It means you can focus on the synthesis, the context, the grappling with what you've found. The job went up a level. The river moved; so did you, if you chose to.

The Day After the Championship

The personal backbone of the essay is Jason's gymnastics career. From age six. Competing nationally by eleven. US Olympic training center. Coach moving him from 25th to 6th in the nation. Junior national team. Fourth-best all-around gymnast under 18. Stanford scholarship. Third place team in 2006. Second place in 2008 after injury. National championship in 2009 as team captain.

But the day after the championship, I was no longer a competitive gymnast.

Sixteen years of training. Joyous and meaningful — got him into college, paid for education, gave him community. But the skillset had no further practical value. A curious part of his background. A fun fact at icebreakers.

The same was true for his biology degree and master's. After five years of study, he evaluated medicine and academic research — neither fit. He went into tech, bouncing from sales to marketing to product management to founding companies. Then traded prestige and mid-six-figure Big Tech income to become an executive coach. Now: three AI assistants at once, being told by Claude he's wasting his time.

Fundamentally, living in the modern world requires you to acquire expertise and then let it go. The era of learning a trade and relying on it for life is over.

What This Means for You

The four operational prescriptions:

Hold your expertise with an open hand.

The tighter you grip what you know, the more brittle you become.

Expertise is a tool, not an identity. The identity-tied version of expertise is what makes AI-era disruption feel existential. Tool-tied expertise feels like a workflow change.

Stay curious about what you don't know.

The experts thriving right now aren't defending their craft against AI. They're experimenting with it, pushing its limits, finding its edges. Curiosity is the antidote to obsolescence. (This connects to antidiscipline — curiosity as one of the 3 C's that sustains effort when discipline can't.)

Prioritize on outcomes, not methods.

Your employer doesn't care whether you wrote the report by hand or generated it with AI. They care whether it's accurate, useful, and relevant. Results matter. Methods are negotiable. This is a quiet challenge to anyone whose identity is built on how they work rather than what they produce.

Honor your intention.

Using AI only makes you less of a programmer / writer / artist if you hand over all intent, effort, and empathy to the computer. If you truly care about your craft, you'll use the very best tools available. The intention is what stays yours.

The Closing Move

Build expertise. Use it. Let it go when it's time. And know that your value was never in the specific skills you mastered — it was in your ability to master new ones.

This is the thesis. The value was never the skill. The value was the meta-skill of acquiring skills. That meta-skill transfers. It's the thing the river can't wash away.

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