Precursor’s Charles Hudson wants to be cautious but not too cautious. The venture capitalist was at an AI confab last month, but he has not yet made a new AI investment during the current hype cycle.
He’s one of many investors who have seen an inflection point take over a sector before, bringing in boatloads of capital, new founders and, at times, speedy and FOMO-driven deals. Historically, Hudson hasn’t minded sitting out. “With crypto, for example, I was OK being at almost zero,” he said. “I don’t think I’m OK with zero as the answer for AI. The question is where and how.”
While the “ChatGPT for X” companies are certainly interesting, Hudson says that he’s out on them for now because they are just “wrapper” companies stitching together different preexisting companies. “I might regret that, but I think I would just say, my imagination didn’t provide the answer.” He said a founder recently pitched him an exciting product, but when asked how long it would take someone else to build the same tool, the entrepreneur said “two weeks.”
Hudson’s interest in crypto reflects what’s happening inside of every generalist firm right now: Are VCs backing net new startups, or are they letting their existing portfolios lead them to AI, either through seemingly magical pivots or via a shared love and validation for low-flying AI companies in the space?
For example, Jason Lemkin says he hasn’t yet invested in a pure-play AI startup. “I’m not sure there is a rush, but I could be wrong,” he said. Most of the investor’s portfolio companies are adding an AI component to their businesses. Then there is Sapphire’s Cathy Gao, who invests in late-stage startups, allowing her to take time to make her investment decisions. During a recent conversation, she described the “arms race” between big companies launching massive products and startups integrating AI to differentiate.
“It’s all about getting a lay of the land in terms of all the different companies, waiting and seeing which ones pop,” Gao said. “Is it going to be one company taking all or a long-tail of companies that accrue value?”
The question being hard to answer isn’t turning investors such as Hudson or Lemkin away, per se, but it does add a layer of due diligence around defensibility, which can be hard to prove in the early stages of company building.
Mayfield’s Navin Chaddha has seen his firm invest in around 30 AI companies over the last seven years — and just raised $955 million to back more early-stage startups in the space and beyond. He thinks it’s a watershed moment for the subsector. When asked if the firm is spinning up anything new to jump into the refreshed exuberance, he said yes, but declined to comment further on what they’re cooking up.
Clearly some people in the market are ready to shout their new plans from the rooftops. Spark Capital, for example, hired a former OpenAI executive to lead investments in early-stage AI companies. The firm is also hiring a part-time “hacker in residence” for AI who will be tasked with building internal AI tools for the firm, meeting with founders and “contributing back to the ecosystem in open source,” according to a job posting.
It looks like a bet that having in-house, technical talent could help the firm land new deals, and better yet, good ones.
“This is an experiment for us, but if you are already coding away on nights and weekends with AI tools and want a front row seat thinking about startups, venture, and the world of AI please consider joining us,” Spark partner Nabeel Hyatt tweeted.
Clearly, VC firms are landing on different conclusions while debating how to jump into AI: Some are hiring talent to jump headfirst, others are happy to back the “ChatGPT for X” spin-outs, and many are sitting in awe, watching their existing investments spark an AI debate of their own, no due diligence needed.