The Tesla PsyOp

The Pattern Starts Early

The Roadster was mostly a marketing stunt. Rich people could show the world how much they cared about the environment while driving something fast. It proved electric cars could be desirable. That was the point.

The Model S was not the first electric car. It was the first one you didn’t have to be embarrassed to drive. That’s a different achievement entirely, and a more important one.

Both were expensive, low-volume, targeted at people who could afford to signal. But they established something: Tesla is cool. That perception would become load-bearing for everything that followed.

The Cost Cut as Feature

The Model 3 is where the psyop matures into something genuinely impressive.

The interior is sparse. Tesla fanboys will tell you it’s minimalist and futuristic. It’s a cost-saving measure. Tesla succeeded in producing a cost-saving measure on four wheels and convinced people to see the savings as features.

The giant touch screen is cheaper than a dashboard full of buttons. The electronically controlled air vents are actually cheaper to mass-produce than traditional ones. Every “design choice” that reads as bold and modern is also the cheaper option.

But here’s the thing: it’s not cheating. Coolness is subjective. If you convince people that minimal is futuristic, then it is. Teslas are genuinely cool cars now. The psyop was a success.

Where the Psyop Met Its Limits

The Cybertruck is the most revealing example of this. Tesla designed it around a new manufacturing process (giga-casting) that couldn’t produce curves, but would be dramatically cheaper at scale. The angular look wasn’t a vision; it was a constraint. The plan was to leapfrog what electric trucks could cost, then put Elon on stage to tell his followers the brutalist thing was actually badass.

Electric trucks are genuinely hard, by the way. Higher power demand means higher fuel usage. With gasoline you just make the tank larger; it’s a cheap, empty container. With electric you have to add batteries, which are expensive and add weight even when empty; more weight means more power needed, which means more batteries, which means more weight. It compounds.

The psyop part worked. People bought it. But the engineering didn’t deliver. The giga-casting process had problems, the Cybertruck ended up closer to traditional manufacturing than planned, cost reductions didn’t materialize, and the result combines the worst of both: expensive to build and looks like a dumpster.

Psyop worked. Engineering failed. Net result: failure.

That’s the limit. The psyop can prime demand and attract capital, but it can’t substitute for the underlying technology actually arriving.

The Capital Markets Consequence

Look at Tesla’s stock chart over the last decade. The shape of it is not what you’d expect in an efficient market. Efficient markets price in information gradually as it arrives. What Tesla’s chart shows is something different: massive anticipatory jumps, years ahead of the technology actually materializing.

Tesla first promised FSD by end of year in 2016. It’s now 2026. The market re-believed that promise roughly every eighteen months for a decade. The most striking example: Tesla’s stock went from ~$30 in early 2020 to ~$400 by year end; a 1,200%+ run in twelve months, almost entirely on FSD narrative. Waymo had already been doing driverless rides in Phoenix for two years by then, with zero comparable stock market fanfare. The psyop, not the technology, drove the capital.

That capital flooded into Tesla. Cheap equity, the best engineers, infrastructure competitors couldn’t match; all funded by a future that hadn’t arrived yet.

That’s not fraud. That’s a structural advantage. Cheap capital, years early, directed at a real problem. The technology is now genuinely closer. The overallocation funded the progress.

Did you know a lot of the Tesla YouTubers are paid by Tesla? Guerrilla marketing. Edward Bernays would be proud. The guy in the TikTok at the top of this post has no idea he’s the product of a fifteen-year influence operation.

Don’t Misread This

I’m not trying to reduce Tesla to just a psyop. The engineering is real. Tesla makes the best electric cars. They are ahead on autonomy. The long-term vision is probably correct.

The psyop is one of Tesla’s most important moats. It gives them cheaper capital, the most competent engineers, and demand for products before they’re actually superior. It lets them leapfrog. And the technological edge that results is genuine.

Tesla is still a good investment. But the 1,000%+ run that peaked around 2021 is over. That was the market pricing in a future that is now mostly priced in. What’s left is a solid company at a full valuation, with high volatility in both directions as autonomy either arrives or doesn’t, on schedule or not.

The easy money was made. The interesting question now is just: how early does FSD actually land?

What’s Next: Optimus

Tesla is now running the same playbook on humanoid robots. Optimus is the new hype vehicle.

The hardware is not the problem. We could have built humanoid bodies a long time ago. The reason nobody did is that without software to make them useful, nobody wants them in sufficient numbers to allow the economies of scale that would make the cost acceptable.

The software is not here. And it’s not visible on the horizon.

Consider how long autonomous cars took. Carnegie Mellon drove a van 2,850 miles across the US mostly autonomously in 1995. Credible demo, real technology, serious researchers. It took until roughly 2023 to become a real commercial product. Thirty years from impressive demo to product you can actually use.

Humanoid robots are at the impressive-demo stage. They can do remarkable things in marketing videos shot in controlled lab environments, cut so you only see the take that worked. Outside the lab they can dance, do basic tasks at roughly the speed of someone who has never done that task before, or occasionally kick someone by accident. The more impressive ones are often remotely operated by humans, which produces exactly zero benefit beyond looking cool.

It is completely unclear when the underlying AI will get there. Personal opinion: we are looking at decades, not years.

Though VLAs (Vision-Language-Action models) might actually have a shot. ~30% chance they make sufficient progress in the next 5 years. Mostly depends on whether we can get the underlying LLM to develop more robust long-range agentic behavior and coherent models of the physical world. But that’s a topic for a future post.

But the psyop is working again. Capital is flowing. Tesla is attracting the engineers who will actually solve it. If the psyop holds long enough for the technology to catch up, Tesla will be first.

The psyop might be the most important technology accelerant of the last twenty years. Investment decisions shouldn’t be driven by it. But understanding it might be the most useful thing you can do before deciding whether to buy in.