To The Moon

When a stock is already up 200%+, the instinct is to “take profits and move on.” With Micron, that might be the exact mistake people made with Nvidia in early 2023 — right before the real leg of the rally. $Micron Technology(MU)$

Congrats to these Tigers for catching the dip:

• 👏 @bluesea520 — bought the Micron bottom and is up $290,000

• 👏 @wywy — bought the Micron bottom and is up $43,000

Micron has surged because AI isn’t just a GPU story. It’s a memory story. Training and, even more importantly, inference at scale forces companies to store and move ridiculous amounts of data — parameters, activations, intermediate results, cached context. As models get bigger, the memory footprint can scale faster than compute. That’s why Micron’s DRAM + NAND sit right in the blast radius of AI spend.

The “bottleneck” matters here. When memory is tight, Micron doesn’t only sell more bits — it can often sell them at higher prices. That shows up in segments like cloud memory, where demand growth has been exceptionally strong.

Why This Isn’t a Normal Memory Cycle

Yes, memory has always been cyclical. But the difference this time is the demand driver: AI inference is sticky. Once enterprises deploy AI workloads, they don’t “undeploy” them. They optimize, expand, and run them 24/7. GPUs enable the compute, but AI cannot run at scale without memory.

And unlike many semiconductor markets, memory supply doesn’t appear overnight. DRAM and NAND are brutal businesses: massive capex, extreme precision, and only a handful of players can operate at the frontier. That oligopoly structure is exactly why pricing can stay firm longer than bears expect when demand spikes.

Micron: Like Nvidia, But “Earlier” in the Pricing

The Nvidia pattern is simple: the stock ran hard, people called the top, then earnings compounded so fast that the “expensive” P/E compressed while the stock kept climbing.

Micron’s setup rhymes with that. MU is around 30x P/E, which scares value investors at first glance. But if earnings really quadruple as projected — and continue growing at strong double digits after that — today’s multiple can look very different a year from now. That’s the key point: the market often anchors on the current P/E and underweights how violently the “E” can change in an AI-driven upcycle. On that view, PEG ratios below 1 matter more than the headline helpfully-scary P/E.

What Comes After GPUs?

If 2024–2025 were “GPU shortage” years, the next phase is about system balance.

HBM limits per GPU, cluster architecture, and real-world inference costs all push the industry toward adding more memory capacity and bandwidth across the stack. As AI moves from demos to daily operations, “memory-first” design starts to win — because latency, throughput, and total cost of ownership depend on data being available instantly, not just on raw compute.

That’s why Micron isn’t simply “a cyclical chip stock that got lucky.” It’s increasingly a pick-and-shovel name for AI infrastructure.

Still Cheap?

After a 200%+ run, “cheap” sounds ridiculous. But valuation is always relative to future earnings power, not past price action.

If analyst estimates are even close — earnings quadruple, then keep growing — Micron’s forward multiple collapses without the stock needing to fall. Add in attractive metrics like Price/Cash Flow, and you get the core bull case: the rally might be the beginning, not the end, if execution holds. $Micron Technology(MU)$

So the real question isn’t “Is MU up too much?” It’s: Is AI memory demand still early?

👉 What’s your take — is Micron the next “Nvidia 2023-style” compounder, or is the cycle about to bite?

💬 Drop your position or watchlist below. $Micron Technology(MU)$

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