Have been quiet on here for the past few months after some live deal sprints and a busy recruiting season. Am transitioning from my MM PE seat to a MF Special Situations role and would love to connect with folks over the next month before I start - DMs open.

Come through

Would encourage anyone interested to reach out on this one.

Friend at a top AI platform received this in the mail along with a PlayStation 5… will be very interesting to see how much value will be captured directly from the frontier model deploycos vs captive teams.

Stamford, Harlem 125th, Grand Central Terminal

Channeling this spirit.

Why hasn’t there been more financialization of human capital income streams — athletes, musicians, creators? Feels like a natural opportunity for a fund to acquire minority stakes (10-40%) at early career stages and enter into assignment of income agreements in exchange for upfront liquidity. Venture model with a diversified portfolio of positions and a power law orientation, further its high FCF which makes it well-suited for back leverage. What am I missing?

I understand that there is Mercor, however these marketplaces don’t feel as prolific as they should be? Why aren’t there people in third world countries taking thousands of pictures of construction sites or filming the lines at food processing facilities for $5 an hour? I know it sounds like I’m saying this in jest - I am not.

Seems like there would be a large opportunity for a firm to serve as a broker / intermediary between 1099s and LLMs to sell personal data or perform tasks for model training - does this not exist?

Odd hill for Dario to die on. This is a man who dedicated his life to building what he openly admits is an existential risk to humanity, while making himself and his ilk very rich in the process. The philosophical inconsistency is glaring - Dario apparently cares about human life when his product is directly in the kill chain, but civilizational risk, driven by the very movement he’s leading, that he has no qualms about. This isn’t a principals stand, but rather moral comfort-seeking. The version of ethics he’s chosen just happens to be the one that lets him sleep at night without actually grappling with the bigger question his life’s work raises.

Cope, this track is still possible (i) at meritocratic firms, look at the 30 year old PMs at Coatue, a16z / GC Partners, 3G CEOs, etc. and (ii) for exceptional performers - the new Brookfield CEO (38 years old) comes to mind.

I would not touch anything in white collar labor for LBOs at this time. Margin for error is limited in these businesses given high relative multiples where you are inherently assuming multiple arbitrage from tuck-ins, platform multiple sustainability, and strong operational execution. While I think AI disruption is likely delayed, the potential headwind introduces too much volatility and equity risk. Relatedly, I think there is going to be a re-rating of industrial and hard asset businesses as both private equity and private credit firms rotate out of software and tech-enabled services to more durable end markets.

The biggest issue I take with Citrini and similar reports is the bias baked into the author’s vantage point, knowledge workers writing about knowledge worker displacement, and the timeline over which they assume it happens. I’ve compiled BLS data below to show the composition of the domestic labor market. Broadly, one can classify the US job market as 32.2% by headcount / 32.7% by wage bill / 27.7% of total cash income in displaceable competitive white collar careers with high AI disruption risk, 9.5% / 18.9% / 16.1% in partially insulated high-value knowledge work with moderate risk, and 58.3% / 48.2% / 40.9% in in-person and blue collar jobs with minimal risk. The remaining 15.2% of total cash income ($1.85 trillion) already flows to roughly 55 million Americans outside the labor force entirely through Social Security, SSDI, SSI, and TANF. The roughly 51 million workers in high-risk categories, represent only $3.4 trillion in wages or 27.7% of total US cash income. Realistically, perhaps half of those roles face genuine structural risk and, further, AI will create net new categories at scale: automation transition, workflow supervision, model governance, and most importantly, expanded demand for the tradespeople and clinicians needed to maintain the physical layer an AI-driven economy will depends on. If 25 million workers (midpoint of a realistic displacement range) lose, or are forced into materially lower-paying roles, the direct income at risk is approximately $1.4 trillion per year at the BLS mean wage for high-risk occupations; around 5% of current US GDP stripped out of the consumer economy on a recurring basis. That is worth taking seriously, but is a gross number and far lower than one would be led to believe after reading the Citrini piece. The timeline matters as much as the total, and the Citrini scenario compresses a 10-15 year transition into 2-3 years. The velocity of money argument assumes displacement hits instantly and self-reinforces before any response can land. The more likely mechanism is a slow bleed concentrated in specific geographies, demographics, and income bands, accumulating gradually enough that wage growth among the remaining workforce, fiscal transfers, and new job creation provide meaningful offset along the way. The $13 trillion mortgage market doesn’t reprice because 25 million workers are displaced over ten years; it reprices if they are displaced in two, with no policy response and no offsetting income creation. Finally, what the scenario additionally underweights is human friction. Large organizations are political organisms governed by sclerotic compliance requirements, union contracts, regulatory cycles, and procurement processes that routinely take 18 to 36 months to execute even straightforward technology decisions. The most disruption-prone sectors (healthcare, finance, law) are also the most heavily regulated, where every workflow change triggers legal review and liability assessment. Beyond institutional inertia, there is a stubborn human preference for other humans in high-stakes decisions that erodes slowly regardless of what the technology can do. The Citrini piece is a useful tail-risk exercise, but it requires the reader to believe that all of these frictions go to zero simultaneously, in two years, across an economy of 160 million workers. The BLS data suggests the actual story will be smaller in scale, history and human friction suggest it will be slower in pace, and the net jobs calculation, once you account for what AI creates, suggests the displacement story is more complicated than a simple subtraction.

The only thing that I’ve been convinced of from reading the Citrini article and seeing the aftermath is how reflexive the current markets are and how incapable PMs are of forming an opinion on the second and third order implications of AI while still feeling the need to do something.

Being an Anthropic dev / product manager presents the opportunity for more information asymmetry than being in congress. Would consider joining for the benefit of my PA alone.

Sorry for not laughing, you’ve caught me in an incredibly replaceable period of my career

“Ya’ll mind if I grab something before we go? Just the essentials”

The only way to be truly stuck in life is never making the upfront time and effort investment in your career to create optionality. Worse than golden handcuffs is reaching a point where you haven’t hit your potential and no longer have the means to…