Alex Kruglov is co-founder and CEO of pop.in.
Artificial intelligence (AI) is transforming one industry after one other, and shortly we’ll see not only the automation of tasks but additionally the proliferation of mediocrity—a tidal wave of “good enough” AI products flooding markets at an astonishing rate. This relentless pace of disruptive imitation will do greater than just increase productivity—it’s going to spawn a cottage industry where constant self-disruption by doppelgängers is the norm and the standard enterprise capital model struggles to stay relevant.
In this brave recent world, any revolutionary idea will immediately discover a legion of followers, blurring the lines between breakthrough and uncharted territory and reshaping the startup ecosystem as we realize it.
The steep rise of AI competence
In lower than a decade, AI has gone from handling complex tasks to being like a human being doing them with increasing ease. AI Index Report from Stanford University provides a surprising snapshot of the explosion in AI performance over the past decade. AI capabilities show not only gradual improvement, but additionally a major leap toward human-level performance on various tasks and beyond. These models are approaching human baseline levels at such a rate that it underscores the exponential pace at which AI technology is advancing.
Consider the transformation of AI-generated imagery. As recently as 2022, AI’s prompt renderings were unimpressive, fuzzy approximations at best. Fast forward lower than two years, and the photographs will not be only recognizable, but strikingly detailed, surpassing the artistic flair of many human illustrators. The result’s astonishing. Even more astonishing is how briskly and simple it’s to get it. This recent form of art has immediately redefined the baseline for what is predicted.
And we’re only originally. Large corporations are investing billions in learning models and are achieving excess of just improving performance – they’re transforming entire business models of their competitors into mere features.
More importantly, these organizations are driving a critical development generally known as “AI agents.” These agents enable AI to not only handle single complex tasks, but additionally orchestrate multiple parallel and sequential tasks concurrently. As Mustafa Suleiman put it in his seminal book The coming wave“an AI that is able to successfully execute the instruction ‘Earn $1 million on Amazon in a few months with an investment of just $100,000.'”
Consider the implications of this development. Suleyman describes tasks that will typically take teams months and even years to finish and have a low probability of success. We’re not there yet, but Suleyman predicts it’s going to be soon. When and if what he calls the “modern Turing test” is passed, Marc Cuban’s response to any pitch on Shark Tank will likely be something like, “Why can’t I just let my AI agent do this while I take a nap? For these reasons, I’m out!”
The traditional enterprise capital model will soon now not make sense
For a long time, enterprise capital has been the lifeblood of innovation, fueling the fires of startups looking for to disrupt markets and redefine industries. Investors poured money into young firms within the hope of guiding them through the perilous journey from idea to product-ready market. The path from startup to scale-up was fraught with risk, however the rewards were potentially astronomical.
This model relied heavily on finding, funding, and scaling human ingenuity—a costly and sometimes inefficient process. Startups burned money to develop products and conquer markets, all the time with the looming threat of failure. The long-awaited payoff, represented by the steep climb after the initial dip of the J-curve, was every enterprise capitalist’s dream: a startup that finally turns the corner and generates lucrative, ever-increasing profits.
Once the fashionable Turing test is passed, the emergence of AI agents will fundamentally change the entrepreneurial landscape. Solo entrepreneurs equipped with advanced AI capabilities will have the option to implement and scale business ideas at unprecedented speeds and with significantly lower overheads, changing the standard role of enterprise capital and difficult its necessity.
Furthermore, if these AI-driven ventures prove successful, their strategies shall be quickly analyzed and copied by competitors who even have advanced AI capabilities. This could lead on to a hyper-competitive market environment where the first-mover advantage disappears and business lifecycles are drastically shortened. The path to positive money flow shall be shorter, but margins will likely be worn out inside months, if not weeks.
Forget the J-curve. Instead, the money flows resemble a “ribcage curve,” where each “rib” is a brand new project with its own J-curve that the solo entrepreneur exploits until it now not generates money flow.
If you are a enterprise capitalist investing in vertical SaaS solutions, consumer products, content farms, B2B sales, or marketing technology, you’ll need to pivot or tell your limited partners you are closing up shop. If the entrepreneurs aren’t constrained by capital, why would they take your money and dilute themselves? And more importantly, if the lifespan of each idea they implement is minimal, they may as well close up shop and begin a brand new company without you.
The market is flooded with an abundance of superb mediocrity. For every good idea, a cottage industry of equally good or higher imitators will almost immediately spring up.
So who will profit most from this massive shift? Today it’s Nvidia, whose graphics processing units (GPUs) are used only to develop learning models as a result of limited availability. Tomorrow it’s going to be those learning models that, after spending tens of billions of dollars, will form the backbone of agent-driven production for many solo entrepreneurs. Just as Apple makes a fortune charging for each app that generates revenue in its App Store, so too will the educational models whose agents do all of the work of constructing those firms. Today’s market leaders could well reap huge advantages in the event that they play their cards right.
And what about individuals? A decade or two ago, you were told to learn to code. Tomorrow’s best-performing solo entrepreneurs could also be those that know easy methods to ask essentially the most interesting and artistic questions. We could see a serious comeback of the liberal arts. Maybe it’s price reading all that Atwood, Nabokov and Marx write?
And what about enterprise capitalists? Is enterprise capital dead? Not yet—however it must adapt. Venture capitalists might want to take larger risks and concentrate on potentially transformative technologies which are outside the reach of current AI capabilities, reminiscent of cold fusion or room-temperature semiconductors.
The landscape is changing rapidly, driven by the unstoppable advancement of AI. As we stand on this precipice, the challenge for today’s investors and entrepreneurs is just not just to maintain pace, but to anticipate and shape the long run. The age of “sublime mediocrity” is approaching, which makes it all of the more vital to ask: what could be truly exceptional on this recent world?
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