On a recent episode of the Catalyst with Shayle Kann podcast themed around the “electric supercycle,” energy investor Andy Lubershein laid out a framework that should reshape how investors think about the EV trade. He argues four building blocks form what he calls the “electro-industrial tech stack”: solar photovoltaics, lithium-ion batteries, electric vehicles, and power electronics. Power electronics, he says, is “the lesser-known fourth leg of the stool” and “the connective tissue between all of that stuff.”
The thesis hinges on compounding feedback loops. “Electric vehicles, which I really think are the sort of the keystone species of this ecosystem, mainly because there’s just so much, so many unit sales of electric vehicles,” Lubershein said. EV volume drove the mass manufacturing scale that crushed battery costs, while early solar investment in wide-bandgap semiconductors later piggybacked onto EVs, which then scaled that same tech for grid applications. Host Shayle Kann captured the loop with silicon carbide: “EVs are where silicon carbide reaches its glory,” noting that companies like privately held Heron Power are now taking EV-scaled power electronics back to the grid as solid-state transformers and solar inverters.
Does Tesla Capture the Supercycle?
If EVs are the keystone, Tesla (NASDAQ:TSLA | TSLA Price Prediction) is the apex predator. Tesla just reported Q1 FY2026 revenue of $22.39B (+15.78% YoY), with automotive gross margin expanding to 21.1% from 16.2% year over year and free cash flow of $1.44B, per the company’s Q1 8-K filing. Active FSD subscriptions hit 1.28 million, up 51% YoY, and unsupervised Robotaxi rides launched in Dallas and Houston.
Yet the question of “massive gains” deserves caution. Shares trade near $400.49 against a consensus analyst target of $420.55, with 5 strong buys, 18 buys, 17 holds, 4 sells, and 3 strong sells. Valuation is rich: a trailing P/E of 371 and a forward P/E of 200. Polymarket traders peg the probability of TSLA closing above $400 in late June at just 41.5%, and the stock is down 10.95% YTD.
The clear read: Lubershein’s supercycle is a multi-year, secular thesis about EVs broadly. Tesla is a leading beneficiary, but near term the data points to fair value. Longer term, the Cybercab pilot, Megapack 3, Optimus, and AI5 silicon give Tesla optionality few peers can match.
How to Play It Beyond EVs
The picks-and-shovels angle is the power-electronics “connective tissue” itself. Several names matter across silicon carbide, gallium nitride, and high-voltage power ICs.
Wolfspeed (NYSE:WOLF) is the silicon carbide pure-play, a $2.46B market cap turnaround that emerged from Chapter 11 in September 2025. It has rallied 229.75% YTD, but with EBITDA of negative $273.2M, this remains a high-risk speculation.
On Semicondcuctor (NASDAQ:ON), the S&P 500 supplier of EliteSiC for 900V EV architectures and AI data center power, carries a $46.5B market cap with a $107 analyst target. Shares are up 124.6% YTD, reflecting the AI-plus-EV double tailwind.
Navitas Semiconductor (NASDAQ:NVTS) is the GaN and high-voltage SiC speculation play at a $5.6B market cap, unprofitable with a price-to-sales ratio of 138. Its pivot, “Navitas 2.0,” targets AI data centers and grid electrification.
Rounding out the basket, Power Integrations and STMicroelectronics offer additional picks-and-shovels exposure. Power Integrations is a high-voltage IC maker with PowiGaN technology, capturing grid-and-renewables spend; CEO Jen Lloyd has flagged that EVs and AI data centers “drive growth in renewables, battery storage and DC transmission.” STMicroelectronics is ramping 200mm SiC in Catania and running a Sanan JV for the Chinese EV market as SiC demand reaccelerates.
The keystone-species framing is a long-cycle prediction. The compounding loops between EVs, batteries, solar, and power electronics are real and quantifiable. Yet, the biggest beneficiaries in the coming years may be a group of semiconductor stocks that were all crushed in 2023 when EV expectations plummeted, but are now rebounding thanks to prior investments that are being utilized by the AI industry.
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