Surya

everyday I spend 4 million tokens coding, 2 million on research (gemini, claude), and my claude computer agent spends 8-20m tokens scrolling and emailing me in 2019 i vividly remember opening up a colab notebook to finish my last HS essay with gpt2 frustrated that teachers never cared about the writing but rather quantity and later made a gpt2 news site that went viral during the 2020 election because ppl dont read in each year since ive spent increasingly more time with gpt3, gpt4, now with sonnet which I believe is the best base model marginally over gemini 2. and in each project ive had since 2019; gpt3 or 4 had played some part I say this because the next era of work will increasingly leverage cs and technical skill than anything else. If cs teaches you anything it’s being able to take memetic representations of ideas and meaningfully translate that into model computational representations. It used to be for loops and now it’s text and ideas for instance you cant tell a LLM to write you a website. you still need to know end to end how to deploy, languages, libraries, styling, and all the little things that it still cant do. if I told you to build a house for me, id be paying you 2x times BOM since you’d know zoning, permitting, hvac, architecting, and lastly building the actual home. You can tell devin to build you a website but it’ll take 2x+ the cost and time if you dont know exactly what you want to be done. Political science, education, finance, etc. degrees are the ones at risk. I would like to see if a CICERO diplomacy agent can beat a political science degree 5/10 times, would probably bet on yes. Capital markets are human speculative but on a weekend using o1 i got to #1 on a prediction market since the humans on that site aren’t smart. I am optimistic about trading firms started by ppl who have no degrees since every <21 y/o leverages llms in ways that the people making them simply dont see yet. other degrees cannot compute that there's always a tradeoff for doing things — math majors hide behind moral frameworks instead of shipping, history majors are blind to the fact that anyone with advanced voice mode+search can absorb their major in a week. the 2020s belong to the ones who execute fast and break things while everyone else is still debating if they should. If you use over 1m tokens a day and show me proof I’ll interview on the spot, dm me.

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Solving the science of asset selection in a future (or indeed the present) where every company is a "Context Acquisition Company" is the real frontier. I love that everyone is getting around to the idea that the secrets (scarce context) currently illegible to/hidden from computers (human or machine) are everything. Now the next leap for people to make is that the science of sourcing, selecting, and monopolizing that context (really THE ASSETS that produce it) is everything. If AI progress is a function of compute and data (most algorithmic progress is really just data progress; h/t @BerenMillidge, @_kevinlu, @mentalgeorge, @GarrettLord, etc.), then every company is going to have a context desk just like they will (or already do) have a compute desk. The difference is, CONTEXT IS NOT FUNGIBLE. Most context (both that exists right now and that will be created in the future) will be completely commodity beta. Winning will be about getting to and instrumenting the right asset (context production factory) first. And yes, there are right and wrong answers. To do this kind of asset selection well requires an extremely scarce meta-capability: the ability to coordinate the right kind of access and the right kind capital at the right time. These assets (and the secrets within them) are structurally difficult to access, evaluate and instrument. They are not floating around in banked processes, to be frictionlessly purchased on listed exchanges, or willingly coming through Mercor or Handshake's expert portal. (Yes, a context production asset can be (very often is) a single person or collection of people.) When @WillManidis talks about a Deal Guy Yuga, what he means is that there are people who have deeply internalized the fact that at the limit, in a world of infinite intelligence, access to/monopoly on the right permissioned data streams is all that matters. Getting yourself to a position (meta-access, meta-capital) where you have the ROFR on those permissioned data streams, means being a generational Deal Guy. This is a very different and specific kind of "Deal Guy" though. Knowing which asset(s) are going to give you the right context to create, compound, and commercialize the best vertical world model now and into the future is the new form of security analysis. But the triple-exceptional combination of domain expertise, meta-access, and technical ability that’s required to execute this new security analysis effectively is scarcer than the talent at quant firms, YC combined, and dare I say, the labs, combined. Palantir understood this and it's why they focused on getting root-access (or something close) to the "highest-status" institutions, and the data streams they produce, first. If you have the talent that can get access to and create value within those institutions, everything else should be a forgone conclusion. If you want examples of the teams that (I believe) actually understand this new science of asset selection and long term value capture in a world of infinite intelligence, study Long Lake and @formationbio. They know and have known that it's all about being able to get the right asset (context), in the right market, with the right team (machine and human) first. These two companies are very far ahead on the scientific frontier of context acquisition. GC backed Long Lake last year. Do you think it’s a coincidence that Long Lake chose to work with General Catalyst? My bet is that Long Lake knew they wanted to acquire Amex GBT before they partnered with GC, and that they partnered with GC because Ken Chenault (the ex-CEO of Amex) is General Catalyst’s Chairman. That gave them the right access at the right time to a very valuable context asset (Amex Global Business Travel) A superhuman vertical-specific Elon operating every company means market leading monopolies in every single slice of the unstructured economy. The thing is you have to build this superhuman Elon while flying the plane. You can't build this superhuman Elon without the very specific context that operating specific assets in the real world gives you. In fact, there's only one stream of context that was able to produce human Elon! Knowing which context stream is likely to do the same a priori is so extremely difficult, but probably possible. I’ll let you intuit why Amex GBT is both most likely to be the market leading monopoly if it were operated by the superhuman Elon of business travel and why it’s also the most likely to produce the context to build that superhuman Elon. The labs of course are very large acquirers of context at present and I think they will continue to play and improve their capabilities here. Through their deplyoment companies, they have already chosen the PE funds that they deem to be the best Context Acquisition Funds. Through in-house deployment focus on Life Sciences they have chosen the vertical they see as containing the most valuable context producing assets. They will acquire very seemingly unrelated companies and will acquihire very interesting people just to get tokens, they will create a Context Acquisition Fund of Funds. But it's not a foregone conclusion that they become the best performing context acquisition companies. Or that they even view it this way. And that presents an opportunity for anyone that does.

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the AI roll-up is only getting started Long Lake CEO @alextaubman has bought 30+ real-economy, non-tech companies and just took the largest corporate travel platform private (Amex GBT, $6.3B) its a bet that AI can better transform legacy industries and that someone has to turn capex into real economic growth "You see the hundreds of billions of CapEx the labs are investing. Somebody's got to take that and turn it into GDP growth. That's what Long Lake was formed to do."

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