The “Apple of Agriculture”

The third and final “forever stock” in Porter Stansberry’s “Artificial Illusion” presentation was Deere & Co. (DE), teased under the label “The Apple of Agriculture.” The comparison was deliberate. Just as Apple built a closed, integrated ecosystem around hardware and software, the argument went, Deere was building one around farm equipment and field data. The tease price was $363.94 in late November 2023.

The mechanism is precision agronomy. Deere’s tractors and sprayers carry cameras and algorithms that can tell a weed from a crop, letting a farmer apply herbicide only where it is needed rather than blanketing a whole field. Stansberry’s specific claim was that this technology can cut chemical use by up to 80%. That is the concrete machine-learning application the other two picks in the trio lacked.

Of the three “AI Railroad” names, this was the one where the AI story was both real and measurable. The scorecard reflects it.

The Best Score of the Three

Here is the number that separates Deere from its siblings. Teased at $363.94, Deere closed on September 25, 2026 at $690.46, up about 90% over three years. That is a genuine winner, and it came with the clearest, most concrete machine-learning use case of the entire pitch.

Put it next to the other two and the pattern is obvious. PayPal was down about 5% over the same period. Ulta Beauty was up about 30%. Deere roughly doubled. The one pick whose AI story translated directly into a better product, a product farmers would actually pay for, delivered the biggest return.

Credit where it is due. Stansberry did not pick a speculative story stock here. He picked a profitable, established equipment maker with a defensible moat, a deep dealer network, and a technology angle that showed up in the real farming business rather than staying confined to a slide deck.

What Precision Agronomy Actually Is

It helps to understand exactly what Deere sells, because it is the reason the thesis worked. We walk through the mechanics in our precision-farming explainer, but the short version is this: cameras mounted on the equipment capture images of the field in real time, and onboard software identifies individual plants as the machine moves.

When the system sees a weed, it triggers a targeted spray. When it sees a crop, it leaves it alone. The result is dramatically less chemical input for the same yield, which saves the farmer money and eases the regulatory pressure around chemical use. That is a real, sellable benefit, not a vague promise about the future of intelligence.

It is also worth being clear about what drove the stock. Farming fundamentals, crop prices, and equipment replacement cycles move Deere far more than any single software feature. The precision-agronomy story helped, and it gave the pitch a concrete spine, but the return tracked Deere’s overall business rather than an AI multiple.

There is a clear difference between this and the other two picks. Deere’s machine-learning story is something a customer can see and touch. A farmer can watch the sprayer skip a weed-free patch in real time. That visibility is rare in AI marketing, and it is a big part of why the pitch, and the stock, held up better than the more abstract fintech and retail stories.

The Honest Read on the Label

The “Apple of Agriculture” framing is catchy, and it is not entirely wrong. Deere does own an integrated hardware-plus-software stack that its competitors find hard to match. A farmer who buys into the Deere ecosystem gets equipment, telematics, and data services that are designed to work together.

But the label still oversells in one specific way. Apple’s returns were driven by a software-and-services margin story layered on top of hardware. Deere’s returns over these three years were driven far more by the strength of the agricultural cycle and by a well-run equipment business. The AI layer was real and valuable, but it was one contributor among several, not the whole story. The pitch’s own framing, that Deere would “play the critical role” in the convergence of AI and farming, turned out to be mostly right in direction and modestly overstated in emphasis.

The Bottom Line

Deere is the pick that worked, and it worked for the most honest reason: it had the most concrete machine-learning application, and it paired that with a profitable, capital-efficient business. That combination is exactly what the “AI Railroad” idea was supposed to reward.

The lesson is not that every AI-adjacent farm equipment company will double. It is that when an “AI” label is attached to a real product that saves customers real money, the label has a chance to show up in the returns. Deere is the exception that proves the rule across this trio, and it is the reason the overall portfolio, if you had held all three from the tease, finished comfortably in the black.

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