u/Loose_General4018

Micron dropped roughly 7% despite another strong quarter and an EPS beat. At first glance that looks like the usual “good numbers, expectations were better” reaction. But I think $MU is becoming more useful as a read-through on the entire AI infrastructure trade than as a standalone memory stock.

The first thing I’d watch is memory pricing expectations. The market has already priced in a lot of optimism around HBM, DRAM and AI-server demand. When a company can report very strong growth and still sell off this hard, investors may be saying the question is no longer whether demand is strong, but whether the rate of improvement can continue.

That creates a few second-order implications.

1. AI capex may remain strong while the winners rotate.
Hyperscalers can keep spending heavily on AI without every semiconductor supplier expanding its multiple forever. If memory capacity catches up with demand faster than expected, some of the economic value could shift away from memory manufacturers and toward networking, packaging, power, cooling or other bottlenecks.

That would make the next stage of the AI trade less about “AI demand up = all semis up” and more about identifying where supply is still genuinely constrained.

2. Watch $SNDK, $WDC and $STX.
If Micron’s decline is mainly valuation compression, peers may not tell us much. But if investors are becoming concerned about memory/storage pricing or future supply growth, weakness spreading into adjacent names would be more important.
That would turn today’s $MU move from a company-specific reaction into a broader industry signal.

3. Equipment suppliers could become the hidden tell.
Strong memory pricing eventually encourages capacity investment. More capacity is good for semiconductor-equipment companies, but it can eventually become bad for memory pricing.
So companies supplying deposition, etch, inspection and memory-fab equipment could benefit from the exact capex cycle that later pressures Micron’s margins. That is the kind of second-order relationship I think gets missed when everyone focuses only on Micron’s next EPS number.

4. Lower memory prices wouldn’t necessarily be bearish for AI.
This is the interesting part.
If HBM/DRAM supply expands and pricing eventually moderates, Micron may lose some pricing power, but AI-system builders could see lower component costs. That potentially improves economics further downstream: servers, inference infrastructure and cloud AI deployments become cheaper to scale.
What is bearish for one part of the AI supply chain can actually be bullish for another.
So my read isn’t simply “MU fell 7%, therefore AI trade is weakening.”

The more important question is whether the market is starting to transition from scarcity pricing to capacity expansion.

If it is, the biggest opportunity may no longer be buying whichever company currently has the strongest AI demand. It may be figuring out where the next bottleneck moves after memory stops being one.

That is the thing I watch over the next few quarters.
how others see this: temporary post-earnings profit taking in $MU, or the first sign that the memory cycle is getting closer to peak expectations?

Reddit closed at $164.50 yesterday, down 7.6%, just before officially entering the S&P 500. There’s an obvious short-term story here: index funds now have to own the stock, and JPMorgan estimated that S&P 500 trackers could need roughly 16.7 million RDDT shares, nearly three times the stock’s average daily trading volume since IPO. But that is mechanical demand. It doesn’t tell us whether Reddit is actually worth owning.

The fundamentals are much more interesting. In Q2, Reddit generated $805 million in revenue, up 61% year over year. Advertising revenue reached $762 million, up 64%, while daily active uniques grew 18% to 130.3 million and weekly active uniques rose 24% to 514.6 million. Adjusted EBITDA reached $343 million, giving Reddit a 42.6% margin, while free cash flow came in at $261 million. This was also its eighth consecutive quarter of revenue growth above 60%. That combination matters because Reddit is no longer just a fast-growing social platform. It is starting to show significant operating leverage.

The bull case is that Reddit may still be substantially under-monetized relative to the amount of attention and purchase intent sitting inside the platform. Someone searching Reddit for the best credit card, thoughts on Nvidia earnings or a new gaming laptop is revealing commercially valuable intent. Google has monetized that kind of intent for decades, while Reddit historically has not done it particularly well. If Reddit keeps improving ad targeting, search, shopping discovery and international monetization, revenue could continue growing much faster than its user base. We may already be seeing that, with users growing 18% last quarter while revenue grew 61%.

Then there is the AI angle. Reddit owns something that could become increasingly scarce as the internet fills with AI-generated content: huge amounts of continuously updated human conversation, opinion and experience. That data could become increasingly valuable to search engines, AI companies, advertisers and users themselves. In other words, AI may actually increase the value of Reddit’s underlying content.

But this is also where the risk becomes interesting. Despite all the attention around Reddit’s AI and data-licensing opportunity, $762 million of its $805 million in quarterly revenue still came from advertising. Reddit is overwhelmingly an advertising business today, not an AI-data business. It also remains dependent on outside discovery, particularly search engines, and management has already acknowledged volatility in search-driven traffic.

That creates a genuine contradiction in the investment thesis. AI could make Reddit’s human-generated data more valuable while AI-powered search products simultaneously reduce the number of people who actually click through to Reddit. Both outcomes can happen at the same time.

That is why I wouldn’t use S&P 500 inclusion as the real investment thesis. What matters over the next few quarters is whether monetization continues to outpace user growth, whether Reddit can increase direct traffic instead of relying heavily on Google, whether international monetization keeps accelerating, and whether non-advertising businesses such as AI licensing and commerce become meaningful contributors.

For me question for $RDDT isn’t whether index funds will buy the stock. They will. The real question is whether Reddit can turn one of the internet’s largest collections of human knowledge and commercial intent into a much larger business without AI simultaneously weakening the traffic ecosystem that feeds it.

If Reddit solves that, S&P 500 inclusion may eventually look like a footnote. If it doesn’t, the current growth numbers could prove much harder to sustain than they appear.

Bull or bear on $RDDT around $165? I’d especially like to hear the bear case from anyone who thinks AI search materially damages Reddit’s long-term traffic.

Not talking about the stock price. I mean the whole ecosystem around $NVDA.

Nvidia is not just selling GPUs anymore. They are getting involved everywhere, AI startups, data centres, partnerships, financing, cloud companies etc.

Basically:
More money goes into AI → more data centres get built → more Nvidia GPUs get bought → Nvidia gets even stronger → even more money comes into the ecosystem.

Obviously this is an incredible business if AI spending keeps growing.

But I keep wondering…
How much of this demand is actually organic?

At some point suppliers, customers, investors and financiers all start depending on the same AI capex cycle continuing.

I am still bullish on Nvidia long term, but I think this is one risk people don’t talk about enough.

Maybe Nvidia is simply benefiting from the AI boom.
Or maybe Nvidia is now powerful enough that it is also helping keep the boom alive.

what others think.

Walmart, Target, Home Depot and Lowe’s are reporting, and their commentary could tell us more about the real economy than another move higher in the S&P 500.

What I’d pay attention to:

1. Are consumers trading down to cheaper products?
2. Is discretionary spending weakening?
3. Are higher energy and input costs starting to hurt margins?
4. Are retailers cutting guidance?
5. Is weakness limited to lower-income consumers, or spreading?

The market has been supported by strong tech earnings and AI spending, but that can hide weakness elsewhere.

So my approach would be simple:
Don’t chase strength blindly. Use this week’s retail earnings as a health check on the broader economy.

If consumers remain resilient, the bull case gets stronger.
If spending starts deteriorating while valuations remain elevated, I’d become much more selective about what I own.

Sometimes the most important market signal isn’t the stock everyone is watching, it’s the part of the economy everyone assumes is fine.

What are you watching most closely this week?

I was reading JPMorgan's new $SNDK thesis and honestly the numbers look kind of crazy. They resumed coverage with Overweight + $2,250 price target.

But what caught my attention is not even the target.

Sandisk apparently has around $94B of long-term agreements, with 4+ year average duration and JPM says these contracts could support around 80% gross margins even at floor pricing.

Then there is AI.

JPM estimates NAND market could go from roughly $70B in 2025 → $300B+ in 2026 → ~$500B in 2027, mostly because data centers need much more flash storage for AI inference.

They also estimate $250 EPS in CY27 and think EPS could compound 25%+ longer term.

Basically their argument is that Sandisk is not just another cyclical memory stock anymore. AI inference + long-term contracts could make earnings much more predictable than previous NAND cycles.

This is where I'm little skeptical though.

Memory has always looked amazing near the top of a cycle. If everyone suddenly believes NAND is structurally different this time, maybe thats exactly when you should be careful.

On other hand, if AI inference really creates persistent storage demand at this scale, $SNDK could be one of those second-order AI trades people ignored while everyone was watching $NVDA.

see what people here think.

Is $SNDK actually becoming an AI infrastructure play, or are we putting an AI multiple on another memory cycle?

Foxconn just gave another pretty strong signal that AI infrastructure demand is still not slowing down.

They said they still expect strong full year revenue growth and AI demand should remain one of the main drivers through 2026. Q2 profit was up around 35% to $1.86B and came above expectations.

For me the interesting part is Foxconn is one of the biggest manufacturers behind Nvidia AI servers. So when they are still seeing strong demand, it suggest the AI buildout is not only hype from big tech presentations. Companies are still actually ordering servers, GPUs, networking equipment and building data centres.

Foxconn is also expanding AI server manufacturing in Texas and Mexico, which tells me they are expecting this demand to stay for some time, not only few quarters.
Of course valuation is another question and many AI stocks already moved a lot. But from the demand side, I don’t see much evidence yet that the AI infrastructure cycle is slowing.

I would keep watching $NVDA, $SMCI, $DELL and $ANET.

Do you guys think AI infrastructure still has another 1–2 years of strong growth, or we are already close to peak spending?

Everyone talks about Nvidia valuation, but for me the bigger thing is still AI spending.

Microsoft, Meta, Amazon, Google etc are spending crazy money on AI infrastructure. As long as this continues, Nvidia is sitting exactly where money is flowing.
But this is also the problem.

At this valuation, Nvidia cannot just deliver “good” numbers anymore. Market already expects good. It needs to keep beating those expectations again and again.

What I’m watching:
AI capex still going up = bullish
Margins start falling = be careful
Big tech slows AI spending = bigger problem

Personally I think biggest risk for NVDA is not AMD or another chip company.

It is expectations getting too high.

Would you buy NVDA at current price or wait for correction?

Hi everyone,

My beehiiv account was suddenly deactivated after the compliance team said my account activity did not align with their Acceptable Use Policy.

I had around 1,500 subscribers across my newsletters and did not receive any warning before the account was closed. The email also says the decision is final, although they provided information about exporting subscriber data and content.

I have already contacted support and asked for a manual review, but I am still waiting for a response.

Has anyone here experienced the same situation?

• Was your account restored?
• How long did beehiiv take to respond?
• Did they explain the exact reason?
• Were you able to export your subscribers and content?
• What should I do next if they refuse to restore the account?

I would really appreciate hearing from anyone who has gone through this. I have spent a lot of time building these newsletters and want to understand whether this could be an automated mistake or whether I should start moving to another platform.

Many people think ETF investing is boring, but boring can be good when money is involved.

An ETF gives you ownership in many companies together. If one company performs badly, your portfolio is not destroyed. For investor, this can be better than trying to find the next Nvidia or Tesla every month.

But all ETFs are not safe. A broad market ETF holding hundreds of companies is very different from an AI, crypto, clean energy or cannabis ETF. Some thematic ETFs are risky bets wearing diversification clothes.

Before buying, I check four things: what companies it owns, expense ratio, how concentrated it is, and why I am buying it. Sometimes an ETF looks diversified, but its top five stocks control almost half of the fund.

My own approach is simple. Most long-term money goes into broad market ETFs. A smaller part can go into sector ETFs or individual stocks where I have stronger conviction.

I also prefer investing regularly instead of waiting for the perfect crash. Nobody knows the bottom, and waiting too long can cost money.

ETF does not remove risk. During a market crash, even an ETF can fall 20% or 30%. It only reduces the risk of one company destroying everything.

My advice for beginners: keep it simple, choose low-cost funds, understand what you own, and give it time.

ETF may not make you rich next month, but it can stop stupid emotional mistakes.

Not financial advice. Just sharing my view.

$NVDA closed around $190 after falling about 3.6%, and this is not only one bad trading day. Whole AI and semiconductor trade is getting questioned by market now.

Main fear started after report that Nvidia may guarantee around $250 billion financing for an OpenAI data centre. Investors are asking one uncomfortable question:

Is AI demand fully real, or Nvidia is helping finance customers who will later use this money for buying Nvidia chips?

This is why people are using words like “circular financing.” Nvidia dropped around 5% after this report first came.

Second problem is AI spending.

Microsoft results were more positive, but Meta free cash flow got pressure because AI investment is becoming too big. Market was happy when companies announced billions in AI spending. Now market wants to know when this spending will create actual profit.

Third problem is China competition and chip sector weakness. SK Hynix earnings disappointed, Asian chip stocks dropped, and investors are getting worried that cheaper Chinese AI models and chips can reduce future demand for expensive GPU infrastructure.

Also Fed is not helping. Interest rate stayed same, inflation fear is still alive and long-term bond yields are moving higher. High interest rate is normally bad for expensive growth stocks because future profit becomes less valuable today.

My personal view:

I don’t think Nvidia business suddenly became bad. Nvidia still owns strongest AI hardware ecosystem, software advantage and large customer demand.

But stock and business is not same thing.

A great company can still fall when expectations become too high. Nvidia was priced like almost everything will go perfect. Now market is starting to price some risk.

I would not panic sell only because stock is red. But I also would not blindly buy every dip.

I will watch:

1. Are Microsoft, Meta, Amazon and other companies still increasing AI spending?
2. Are customers paying from their own cash, or depending more on Nvidia-backed financing?
3. Is AI infrastructure producing enough revenue and free cash flow?
4. Can Nvidia protect margins when custom chips and Chinese competition become stronger?

For me this correction is healthy until company fundamentals also start breaking. But position size is important. One stock should not destroy whole portfolio, even when company looks strongest in world.

I may buy slowly in small parts instead of using all cash in one day. Catching exact bottom is mostly luck.

Nvidia is not dead. But market is finally asking whether unlimited AI spending can continue forever.

What you guys think: normal correction or AI bubble starting to break?

Not financial advice. Just sharing my own market view.

Maybe unpopular opinion but I think $PLTR is one of the hardest stocks to understand at current price.

I like the company and I can see why people are bullish because AI demand is strong, government contracts are growing and management is executing better than before. But now it feels like market is not only pricing good growth, it is pricing almost perfect growth for many years.

This is where I am confused. A company can be great but stock can still be too expensive. If earnings are only good and not amazing, I think many people may start taking profit very quickly. At same time, betting against this stock also looks dangerous because every dip is getting bought.

I am not saying buy or sell, just trying to understand what is the real risk here.

Are people buying $PLTR because of fundamentals now, or because everyone believes someone else will pay higher price later?

A few months ago, we shared that our team was building a tool called Edge Alpha Terminal.

Today we are happy to say that we have completed Milestone 2, which was building the investment knowledge graph.

The knowledge graph connects companies, sectors, market events, financial data and investment themes together. It was not easy, and many times we had to change the structure, fix bugs and rebuild some parts again.

There is still lot of work remaining, but now it finally feels like a real product and not only an idea.

Our next step is testing. We will check the accuracy of connections, missing data, wrong relationships and whether the tool is actually useful for investors.

We are not saying it will become a huge startup overnight, but completing this milestone feels like a very important win for our small team.

Thanks to everyone who encouraged us before. Now we are heading toward testing and hopefully Milestone 3 soon. 😊

Check the tool and provide valuable feedback: https://edgealphaterminal.com/