The Fireworks Show Is Over: Why This Is An AI Rotation, Not a Bubble Unwind
The Fireworks Show Is Over: Why This Is An AI Rotation, Not a Bubble Unwind
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Note: AI-generated summary based on third-party content. Not financial advice. Read more.
Quick Insights

Investors should consider Eli Lilly (LLY) as a primary play on the AI "application layer," with potential to become the largest U.S. company by the end of the decade through its proprietary AI-driven drug discovery. For infrastructure exposure, Marvell Technology (MRVL) offers significant upside in optical networking and custom chips, with some analysts projecting a long-term path toward a $1 trillion market cap. While Bitcoin (BTC) remains in a technical downtrend, long-term investors can "nibble" at current levels near the 200-week moving average to capture its future role as a settlement layer for AI agents. To hedge against geopolitical volatility and energy-intensive data center growth, look toward defensive energy giants ExxonMobil (XOM) and storage specialist Fluence Energy (FLNC). Conversely, it is wise to reduce exposure to memory stocks like Micron (MU), as the trade has become crowded and AI efficiency gains may eventually reduce demand for high-bandwidth memory.

Detailed Analysis

Based on the analysis of the podcast transcript with Jordi Visser, here are the key investment insights and asset mentions:

Eli Lilly (LLY)

• Visser identifies Eli Lilly as potentially the most important AI company in the world, moving beyond just a pharmaceutical play. • The company is utilizing Lillipod, a specialized AI model trained on their own proprietary data using over 1,000 NVIDIA Blackwell GPUs, rather than general internet data. • He views "peptides" as this decade’s version of API keys—a fundamental building block for value creation.

Takeaways

Bullish Sentiment: Visser predicts Eli Lilly could become the largest company in the U.S. by the end of the decade, surpassing even NVIDIA. • Actionable Insight: Look at LLY as the leader of the "Application Layer" of AI. While hardware is currently volatile, LLY represents the shift toward ROI-driven AI utilization in healthcare and longevity.


Marvell Technology (MRVL)

• Mentioned as a key player in the "optical" side of AI infrastructure. • Visser highlights that as data centers move toward custom ASICs (Application-Specific Integrated Circuits), the demand for optical networking and "co-packaged optics" (CPO) will explode. • He notes that NVIDIA’s Jensen Huang has suggested Marvell could eventually reach a $1 trillion market cap (currently around $250 billion).

Takeaways

Bullish Sentiment: Visser prefers Marvell over memory stocks like Micron because the optical cycle is in its "very early innings." • Actionable Insight: Marvell is viewed as a "double or triple" opportunity. It was recently added to the S&P 500, which may provide further institutional support.


Bitcoin (BTC)

• Visser views Bitcoin as the "only high-quality stock that will exist for certainty in a decade." • He aligns with the thesis that AI agents will need a "crypto rail" (like Bitcoin or major Layer 1s) to transact, settle, and coordinate value at machine speed without human intervention.

Takeaways

Long-term Bullish / Short-term Bearish: He admits Bitcoin is technically in a "bear market" until it crosses back above its 200-day moving average. • Actionable Insight: He is "nibbling" and buying small amounts on the way down, specifically noting that Bitcoin is currently at its 200-week moving average, which historically has been a disciplined entry point for long-term investors.


Memory Stocks: Micron (MU), SK Hynix, Samsung

• Visser is notably cautious on the memory sector despite strong consensus from Wall Street (e.g., Goldman Sachs). • He warns of "Recursive Self-Improvement" (RSI), where AI models may eventually learn to solve their own memory bottlenecks, drastically reducing the amount of High Bandwidth Memory (HBM) needed.

Takeaways

Bearish/Neutral Sentiment: He exited his Micron positions in the $600-$700 range (referring to market cap/pricing levels in his specific tracking). • Risk Factor: Retail and institutional positioning is "all-in," creating a crowded trade. He believes the risk-reward is no longer attractive for "doubles or triples."


Energy Sector: ExxonMobil (XOM) & Chevron (CVX)

• Visser is buying these as a defensive hedge against geopolitical instability, specifically the Strait of Hormuz and tensions with Iran. • He views energy as a "stuck market" that provides safety while AI hardware names experience high volatility.

Takeaways

Bullish/Defensive Sentiment: These are not expected to be "explosive" growers but are necessary for portfolio balance. • Actionable Insight: If oil prices migrate higher due to supply chain disruptions, energy stocks will likely outperform the broader "AI rotation."


Fluence Energy (FLNC)

• A play on the massive energy requirements of AI data centers. • The company recently signed master supply agreements with two major "hyperscalers" (large cloud providers) and has a partnership with Siemens and NVIDIA.

Takeaways

Bullish Sentiment: Visser believes batteries and energy storage are a necessity for the "Mad Max phase" of data center build-outs where companies are forced to go off-grid for power.


Investment Themes & Sector Rotation

The "Fireworks" are Over: The period where any AI-related stock would automatically gap up 10-30% is finished. We are moving from "Discovery" to "Digestion." • Rotation, Not Bubble: Visser argues this is not a 2000-style bubble burst because earnings and profit margins are still hitting all-time highs. Instead, money is rotating out of "Chips" and into Healthcare and Financials. • Compute vs. Energy: The old economic cycle (Labor vs. Capital) is being replaced by a new one (Compute vs. Energy). Digital "employees" (AI agents) consume tokens and electricity, not wages and houses. • Application Layer: The next phase of the market will favor companies that can prove Return on Invested Capital (ROIC) from AI, rather than just those selling the "shovels" (chips).

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Video Description
To Learn More Visit : https://ai.22vresearch.com/ In this week's video, I break down one of the worst week for stocks since Liberation Day, the S&P down 2.6%, the Nasdaq down 4.5%, and make the case that this is a necessary rotation, not the start of a bear market. After nine straight up weeks, none of this should be a surprise. The 20-day finally broke, weekly RSI hit multi-year highs with no divergence yet, and Friday's beta unwind was the sharpest since early 2000s, a genuine cleanse. The bigger message: the fireworks show is over. The buy-anything phase of the agentic AI trade where memory, semis, and infrastructure gapped 10–30% on the way up on good news has moved from discovery to digestion. The agentic buildout itself has just begun, but the next three to six months will be two-sided and choppier; you have to do the homework now and manage through a much more crowded positioning running into bottlenecks. And the macro backdrop is the photographic negative of a sustained bear market: credit spreads near all-time tights, no jobless-claims spike, rising PMIs, record profit margins, and earnings revised up, not down. That's why I'm watching the rotation, not running from it. On Friday the S&P fell nearly 3% while five sectors rose, capital left the chip complex and moved into healthcare and financials. Structurally, we're shifting from labor-vs-capital to compute-vs-energy: the input is electrons, the output is tokens. I think memory has likely topped for now and recursive self-improvement, DeepSeek, and government-stake risk all argue for increased caution moving forward so I prefer Marvell and optical over Micron. I'm adding energy (Exxon, Chevron), batteries (Fluence), Bitcoin near its 200-week, and leaning into the application layer, where Eli Lilly may be the most important AI company in the world. Timestamps • (00:00–02:20) Markets: rotation or bear market? The S&P fell 2.6% and the Nasdaq 4.5%, the worst week since near Liberation Day but after nine up weeks in a row, this looks like a necessary rotation, not a top. • (02:21–06:09) Technicals: the Q's and S&P finally closed below the 20-day; weekly RSI hit multi-year highs with no divergence yet; Friday's Morgan Stanley beta factor fell ~10.5%, the sharpest move since 2000 a real cleanse. • (06:10–07:45) "The fireworks show is over": agentic AI moves from discovery to digestion. The easy gains are done; the next 3–6 months are two-sided, but the agentic buildout has only just begun. • (07:46–12:46) How we got here: CES (Vera Rubin, "tokens per watt," the five-layer cake), the March TMT sentiment shift, and Computex. Google's $85B raise and Meta's equity raise are to fund capex and that looks more like a possible short term capex top than a bottom. • (12:47–18:17) The macro reality: earnings revised up, margins at record highs with no mean reversion, credit spreads at all-time tights, no jobless-claims spike, rising PMIs, "the photographic negative of a sustained bear market." • (18:18–19:59) The rotation in action: Friday the S&P fell ~3% but five sectors rose; capital left chips for healthcare and financials (deGraaf, Parker, Newton). • (20:00–23:30) From labor-vs-capital to compute-vs-energy: the input is electrons, the output is tokens. Digital workers don't buy homes or cars, so the old credit-and-labor cycle no longer applies. • (23:31–27:17) Crypto rails & Bitcoin: agents need layer-1 rails to transact and settle. Buying Bitcoin in pieces near the 200-week MA, "the only high-quality stock that will exist for certain in a decade." • (27:18–34:24) The memory bear case: don't extrapolate token demand into DRAM. Recursive self-improvement could solve the memory bottleneck; DeepSeek/edge substitution and government-stake risk pile on. Marvell and optical/CPO over Micron. • (34:25–55:15) Capex vs. adoption and the application layer: $60–100B of semis per gigawatt while adoption lags; the market shifts from a capacity land-grab to ROI discrimination. Energy (Exxon, Chevron), batteries (Fluence), and Eli Lilly as the most important AI company in the world.
About Jordi Visser
Jordi Visser

Jordi Visser

By @jordivisserlabs

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