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AI’s Messy Phase Is Where The Money Is Made
2026-04-16 · via Forbes - Business
Depositphotos_707076952_L

In the early days of the automobile, the edge belonged to early adopters. AI presents a similar opportunity.

Deposit Photos

Speed to market has long been a winning business strategy. Likewise, beating the competition to the punch has historically paid dividends. Take the automobile sector as an example. Before Henry Ford pioneered mass production, there was a brief window in the early 20th century in which early adopters churned out custom vehicles.

“Most early automobile companies were small shops, hundreds of which each produced a few handmade cars….,” explains Encyclopaedia Britannica.

“It was possible to begin building motor vehicles with a minimal investment of capital by buying parts on credit and selling the finished cars for cash; the cash sale from manufacturer to dealer has been integral in the marketing of motor vehicles in the United States ever since.”

That first mover window closed soon after, never to fully reopen. With it went the early adopter advantage. Soon after, car production became an economy of scale play, the winners being the few large companies that could pump out standardized products on a vast scale that was difficult to imitate.

Could we be living through a similar fleetingly opportunistic moment?

This is the contention of author and speaker on the future of work Jurgen Appelo with whom I recently spoke with for an interview. “We are living through a moment of rare opportunity with AI. It’s analogous to the ‘pre-assembly line’ phase of car production. Today’s systems are clunky, fragmented and often frustrating to use. But that is also what makes this time so special.”

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What’s happening in the market bears out this reality. Much like pre-mass produced cars, creating anything truly productive with AI agents like Clawbot still requires non-standard approaches. This means frankensteining disparate tools, tweaking them until you achieve something valuable.

Tolerating failure is a big part of that gamble. You could spend weeks, if not months, tinkering with an AI-based project that goes nowhere. If you do crash and burn, it doesn’t pay to lick your wounds for long. Like widespread car adoption in the early 20th century, today’s AI revolution is not slowing down. Not for a second. According to Gartner, “C-level executives at software organizations have a crucial three- to six-month window to define their agentic AI product strategy, as the industry is at an inflection point. Organizations that do not plan to develop agentic capabilities risk falling behind their peers.”

This reality speaks to a capability gap. For now, no one organization owns the agentic AI space. To use another historical analogy, it’s akin to the Wild West with all of its messiness and lack of structure. “If AI orchestration were simple and polished, everyone would already be doing it. There would be no advantage left. Instead, we’re living through a period where capability is not yet evenly distributed, and that gap is where leverage lives,” says Appelo.

Appelo points out another gap: the varying ways AI is being used to achieve business goals. Alex Finn offers one interesting path. The Agentic AI entrepreneur has built his own autonomous AI agents to work 24-7 for him. Here’s how he describes his approach to using these tools. “Over the past week my ClawdBot Henry has: designed, built, and shipped apps by itself, sent me morning briefs totally customized to everything I’ve been doing on the computer, wrote me YouTube scripts that have gotten over a half million views, [and] kept an eye on content competitors, alerting me via text when their content outperforms…” he also adds: “ZERO technical experience was required to do any of this.”

The last statement is especially poignant. Back in the early 1900s no boutique car manufacturer could directly ask the very cars he was building in his garage for advice on how to produce better vehicles. The notion would have been laughably preposterous. But as I describe in this recent Forbes article, we are living in the Intelligence Age.

This means for the first time ever, we have a synthetic thought partner, one that can collaborate alongside us, shining a light along the dusky trail. Don’t know how to program your agentic AI to work for you? No matter. You don’t have to consult field experts, if they exist. You can go to AI itself to teach you. Even better, you can ask your artificially intelligent docent to explain things to you like you are a beginner with scant technical experience.

Enticing as this prospect is, again, today’s window for such experimentation is closing fast. In this way, the situation we are in resembles another, more recent opportunity that has come and gone. Early web developers once enjoyed their own first mover advantage in the late twentieth century.

Long before tools like vibe coding or Google Stitch, an intuitive website builder that talks back to you, internet pioneers enjoyed a digital moat. It was hard to break into using the web for business if you didn’t know what you were doing. Early developers had to hand-code HTML to craft the first wave of sites, back when the zeitgeist was still abuzz about “the information superhighway.”

In time, of course, once arduous tools became easier to use, enabling mass adoption. That led to the flattening of proprietary acumen prized by the market. Historical precedent suggests something similar will happen with AI. Today’s obtuse, unwieldy tools will give way to cleaner, easier to manage resources packaged and sold as turnkey solutions from a handful of leviathan-sized players.

When that happens, the playing field will flatten, according to Appelo. “Those people who waited, observing from the sidelines will finally enter the game. But by then, early builders will already be miles ahead, employing the Hyperdrive Advantage.”

Much like Han Solo and his Wookie co-pilot were able to make the jump to light speed, “outrunning imperial cruisers—and not the local bulk type either”, these first movers will be galaxies away before their competitors can look up and say, “I have a bad feeling about this.”

However the future shakes out, Appelo is wise to emphasize the importance of speed to leverage these unchartered times. Before the big car companies got involved in automobile production, small, enterprising outfits enjoyed the ability to nimbly seize the moment. In a similar way, small teams and even solopreneurs can act fast and decisively now, outrunning large organizations to capitalize on a window that will be closing fast.

This begs a pressing question: in that case, what are we waiting for?