I recently watched Brandon Sanderson’s keynote on whether AI is art or not.
It’s a great talk. And I highly recommend you check it out even if you don’t work in the creative industries.
We’ve seen writer strikes in Hollywood as well as a proliferation of AI use cases in creative industries. James Cameron joined the board of Stability AI. The Russo brothers behind Marvel’s superhero sequel prowess have created their own AI studio. Pouya Shahbazian as well, using AI over the next four years to create 30 AI-generated films. The list goes on. As such, the question of “Is AI art?” is an interesting one to answer. And admittedly, harkens to a series of conversations I’ve had with allocators on leveraging AI in investing practices.
From the VC/GP side, there are folks like Yohei, Sarah, and Ben and Matt, just to name a few who’ve all been building and incorporating AI recently into their workflows and deal flow pipelines. Yes, I know I’m missing a lot more names. But you get the point. From the LP side, progress is still slower, but many younger LPs are quickly adopting AI as well. The conversations I’ve had come from senior allocators on whether it makes sense to use AI. And if so, how much?
Which begs the question: If AI can do your job, do you still have a job?
I was at a dinner last year where the CIO of a large endowment shared that the reason she knows what to look for in managers today, how to underwrite funds, and how to build a venture portfolio was due to the fact she made a plethora of mistakes on her way up the allocator ladder. Small mistakes, like mixing up a decimal on the spreadsheet which led to a venture fund needing a $10B outcome instead of a $1B outcome. Or like Jamie Rhode once said on Superclusters, that she failed to check before she made a commitment to a fund if the fund actually had the commitments that the GP advertised, leading to her check being a larger proportion of the final fund size than she anticipated.
A lot of senior leaders in the LP space seem to be quite skeptical of what AI can do for investment decisions in its current state, yet junior team members seem to widely adopt it to write memos, to inform investment decisions, to create portfolio construction models, and so on. And so far, there’s been a general consensus that AI, at least with respect to investment decision-making, has yet to reach its desired state. In one comment at the same dinner, a senior allocator remarked that one of her direct reports submitted a fund construction model that was built via AI and suggested that in order to return the fund, they needed almost a quarter of the companies to become unicorns. And when questioned, the junior allocator saw nothing wrong with the model. Only to further defend their choice. Or as Brandon Sanderson says in the talk, the problem with AI “is because they steal the opportunity for growth from us.”
“The process of creating art makes art of you. My friends, let me repeat that. The book, the painting, the film script is not the only art. It’s important, but in a way, it’s a receipt. It’s a diploma. The book you write, the painting you create, the music you compose is important and artistic, but it’s also a mark of proof you’ve done the work to learn because in the end of it all, you are the art. The most important change made by an artistic endeavor is the change it makes in you. The most important emotions are the ones you feel when writing that story and holding the completed work.
“I don’t care if the AI can create something that is better than what we can create because it cannot be changed by that creation. Writing a prompt for an LLM, even refining what it spits out, will not make an artist of you because if you haven’t done the hard part—if you haven’t watched a book spiral completely out of control, if you haven’t written something you thought was wonderful and then had readers get completely lost because your narrative chops aren’t strong enough, if you haven’t beat your head against the wall of dead ends on a story day after day until you break it down and find the unexpected path—you’re not going to have the skill to refine that prompt. The machine will have done the hard part for you and it doesn’t care.”
Growth comes from making mistakes. It comes from the struggle. The “distance travelled,” to borrow a term Aram Verdiyan used before. This is why investors often prefer partnerships and co-founderships. It’s why many firms have “red teams.”
There is probably a day when AI can do our job. But for now, the art of investing is in the friction it takes to make a decision. The character-building moments. The moments where you question your own priors. So if AI enables you to have more nuanced dialogues with yourself, if it challenges the way you think in ways you hadn’t considered before so that you look for evidence that either proves or disproves the null hypothesis, then there will still be room for the use of AI in investing. Otherwise, if you’re regurgitating scripts based on singular uninspired prompts, then you likely won’t have a job for long.
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The views expressed on this blogpost are for informational purposes only. None of the views expressed herein constitute legal, investment, business, or tax advice. Any allusions or references to funds or companies are for illustrative purposes only, and should not be relied upon as investment recommendations. Consult a professional investment advisor prior to making any investment decisions.
