VC10X Pulse - Micron's Blowout Earnings Report: What it means for the AI trade?

this week micron didn't just beat earnings it may have delivered one of the strongest data points we have seen yet on the durability of the ai infrastructure build out revenue came in at 41.5 billion dollars adjusted eps came in at 25.11 dollars and then management issued guidance that shocked even the bullish investors q4 revenue of 49 to 51 billion dollars q4 earnings of 30 to 32 dollars per share both well ahead of Wall Street expectations. The real story is what Micron just told us about the broader AI economy. Let's dig deeper. When investors think about AI, they usually think about NVIDIA, OpenAI, Anthropic. But every AI workload requires three things. Compute, power, memory. And memory has quietly become one of the biggest bottlenecks in the entire stack. You can have the most advanced GPU in the world. Without enough high bandwidth memory, it doesn't matter. Which is why Micron's results are such an important signal. They're not telling us about one company. They're telling us about demand across the AI ecosystem. Everyone is focused on the revenue beat, but I think the most important takeaway was management's commentary about supply. Micron indicated that memory shortages are expected to persist beyond 2027. Think about that. We are not talking about a shortage next quarter, we are talking about a shortage next year. We're talking about a multi-year imbalance between supply and demand. If that proves correct, it fundamentally changes how investors should think about AI infrastructure. because it suggests their bottlenecks are not going away, at least not anytime soon. They're getting worse. For the last two years, Nvidia has consistently argued that AI demand is still exceeding supply. Many investors assumed that eventually capacity would catch up. Micron's results suggest otherwise. In fact, the memory side of the ecosystem may be becoming one of the bigger constraints. And that's important because memory is harder to scale than most people realize. Building capacity requires capital, packaging, manufacturing expertise, and time. You can simply flip a switch and create years of additional supply. Now, if Micron is right, there are three major implications. First, the AI gaping cycle is far from over. Companies don't lock in multi-year memory demand if they expect AI spending to collapse next year. The hyperscalers are effectively signaling continued infrastructure expansion. Second, the winners may be broader than just NVIDIA. For a long time, investors treated AI as primarily a GPU story. Now it increasingly looks like memory, networking, power, cooling, and data centers, all becoming critical beneficiaries. The AI trade is widening. Third, margins may remain elevated longer than expected. Micron expects cross margins to approach roughly 86% next quarter. Historically, memory has been one of the most cyclical businesses in technology. Those kinds of margins were almost unimaginable a few years ago. The market is beginning to ask what if this cycle is structurally different. Now let's rebalance. One quarter does not eliminate cyclicality. Memory has historically been one of the most dangerous industries for extrapolation.