Over the past year, there has been much ado about emerging tech - whether it’s blockchain, the metaverse, or generative AI - all predicted to hold the future of tech at various points (even by yours truly). However, as with most trends within the tech community, they eventually fall out of favor. For example, FTX, BlockFi, and Silvergate and the highly publicized backlash to Meta changing its name from Facebook hurting overall perceptions of blockchain and metaverse.
Even generative AI, the ecosystem’s shiny thing for the past several months, is now losing attention in favor of “spatial computing”, basically the metaverse with a rebrand, in light of Apple revealing the Vision Pro headset at this year’s WWDC keynote. If history is any indication, the AI space is likely a few scandals away from the Tech Twitter graveyard.
I don’t think anything is inherently wrong with these trends, but with how the tech community discusses and treats trends. We hop on new technologies without proper knowledge or research and throw them away when they don’t deliver the vision we’ve imagined. Spend a couple of years on Tech Twitter and you’ll notice how founders, operators, and VCs will favor and forget about trends every 1 to 2 years.
In venture capital trend cycling is driven by low-interest rates and lots of LP money sloshing around. As a result of this frothy market, there has been more focus on winning popular deals than conducting proper diligence, resulting in inflated valuations concentrated on a small number of deals.
Opportunistic deal chasing has proven to be a boon for well-connected, charismatic founders who know how to use VC FOMO to their advantage, but ultimately this method has exposed funds to deals that look good on the surface, but have major issues lying just underneath. Thesis-driven funds have an advantage here because they have committed the time to understand a particular space before investing, allowing them to quickly identify idiosyncrasies when evaluating deals.
Once a handful of VC Twitter darlings get exposed as bad actors or simply unable to turn a profit, venture capitalists write off the entire trend and repeat the cycle with the next trend, learning absolutely nothing. To break this cycle, the venture capital community must make research and diligence cool again. I know this runs counter to many incentive structures that prioritize easy markups over proper deal evaluation, but I hope the current bear market provides an opportunity for funds to slow down, reevaluate, and dedicate the time to proper diligence and research, FOMO be damned.
VCs aren’t the only ones with a FOMO problem. Big Tech companies, particularly Meta, have hopped onto the emerging tech bandwagon as a cynical attempt to maintain market share. While those within the tech industry recognize Meta’s VR era as another in a long list of Zuckerburg’s attempts to Make Facebook Cool Again, they have only miseducated and alienated the public about AR/VR.
Due to Facebook’s brand recognition and audience, Zuckerburg’s drab vision for a 3D walled garden is the public’s only conception of the “metaverse”, undermining much grander use-cases from startups such as GuildFi and Decentraland. This makes it harder for founders to reach product-market fit and ultimately limits the possibilities for what an immersive web could look like.
On the other hand, Apple’s recently announced Vision Pro looks promising. If Oculus is an immersive game console, Vision Pro is a spatial computer that has all the functionality of a regular computer with an immersive user experience. This approach meets the majority of consumers where they are, adapting to 3D what the majority of people already use their computers for such as web browsing, multitasking and entertainment, which shuts down sentiments that AR/VR can only work for a niche gaming audience. I think the Vision Pro is the right kind of hardware to lay groundwork for the metaverse to reach its potential; I might write about this more in a future article.
It’s not a bad thing for Big Tech to experiment with trends - often it’s necessary, especially in instances where new hardware is required. However I think there is a right and wrong way for Big Tech to engage with trends. Foremost, there must be synergies between the trend itself and the core business because the company can bring their existing sensibilities to make a strong entry into the market. For example, much of the reason why the Vision Pro works is due to Apple’s roots as a computer company because of this heritage, Apple approaches VR headsets not as a world apart from the mundanity of the end user’s life, but as a valuable part of it, creating a conceptually more useful and relatable product. The same can be said for Google using generative AI to improve the search experience - it works because generative AI can make search more straightforward for end-users and Google is an expert in search.
The market favors expertise. Whether it’s investing or building, decisions and end products improve, the more base knowledge one has. Though the payoff of expertise is high, it is matched by similarly high opportunity cost. It takes a lot of time to properly evaluate a deal or build a product offering true to your company, time that could be used making more deals or shipping more products. As a result, it’s very possible that you could miss out on the next decacorn or miss your go-to-market window. For that reason, I understand why some builders and developers have taken a more reactive approach, especially under the backdrop of a decade long bull market. However, reactivity comes at the cost of quality - there’s more susceptibility to shitty deals with lots of hype or a cycle of throwing more product offerings and acquisition dollars to the wall hoping that something sticks.
As I touched on above, I think the bear market is a blessing in disguise. Deal activity slowing down and valuations coming down, provide an opportunity for everyone in the tech and venture capital community to look before leaping. Taking the time to understand a trend and how your business or fund can add value before committing resources creates space to take risks that make sense and are more likely to pay off in the end. Maybe this slightly slower approach will add much needed substance to tech discourse going forward.