@TW_trades_ u used to attack people who do this , now you doing the same ....
English
Afaf
33 posts
Will be posting the same content here on X
You can expect:
> My research and write ups in stocks I invest in
> My live trades (Buys & Sells)
> Deep dives after earnings
> Any new information I find interesting
Join here: x.com/TW_trades_/cre…
TW@TW_trades_
I just shared my entire Portfolio on Substack: Will be doing weekly updates on my positions here If you are interested you can view the article below: open.substack.com/pub/twtrades/p…
English
This is the best read on the AI trade.
All these companies are due for a pump.
In this post, I'll go over why this AI trade is so oversold, and what stocks I'm buying:
Step 1: What actually happened?
SK Hynix is one of the world's largest memory companies.
They announced a $26 billion ADR listing on Nasdaq, which is enormous.
To put it in perspective:
Saudi Aramco IPO: $29B
SK Hynix ADR: $26B
Alibaba: $25B
Institutional investors wanted shares.
But institutions don't magically create cash (they must get the $ from somewhere).
So, they must sell existing positions.
Step 2: Where do institutions get the money?
This is the most important part.
Imagine you're a $40 billion technology fund.
You already own
- Micron
- Sandisk
Kioxia
- Samsung
- SK Hynix Korea
Now you're allocated another $500M into SK Hynix ADR.
You simply sell existing memory names.
This is what we call "portfolio rebalancing."
Nothing changed fundamentally; it's simply that the money rotates around.
Step 3: Why memory stocks specifically?
Because funds want to keep sector exposure.
If they're buying SK Hynix, they're usually selling: Micron, SanDisk, Kioxia, Samsung, and memory suppliers, not Nvidia.
That's why the pressure became concentrated.
Step 4: Why the selling became exaggerated
Imagine every large fund is trying to sell Micron simultaneously.
Nobody wants to be last.
Everyone starts undercutting each other.
That creates crazy selling pressure: we get momentum selling, quant selling, stop losses, CTA selling, and retail panic (along with X panic, lol).
Eventually the stock falls much further than fundamentals justify.
This is natural human psychology.
Step 5: Why the MU earnings reaction looked strange
Micron reported an excellent quarter. They beat on everything.
With this, everyone normally expects:
Strong earnings + higher guidance -> Higher stock.
But instead the stock barely responded (and actually went down).
Why?
Because institutions likely used earnings liquidity to quietly unload stock ahead of the ADR.
That's a great way to exit.
They have lots of buyers, so lots of volume, and nobody will notice.
Step 6: Oversubscription matters
The offering was reportedly 7x oversubscribed.
That means demand exceeded supply by a huge margin.
Institutions likely requested much more than they actually received.
Suppose that the fund requests $700M, but actually receives $100M.
They may have already sold $700M worth of memory exposure.
Now they're underweight.
So what happens?
They buy back.
That creates a mechanical rebound.
Step 7: Why this isn't just a short squeeze
Because nothing about AI memory demand changed.
HBM demand is still exploding. Inference still needs memory. raining still needs memory. Context windows keep expanding. Reasoning models use even more memory. Agentic AI increases memory usage.
Everything still points toward a higher memory consumption (and the AI trade continuing to take place).
Step 8: The market confused a stock price with fundamentals
This happens constantly. It's human psychology 101.
People saw Micron down and assumed "Demand must be collapsing." Instead, price caused the narrative (natural in the short term). Not the other way around.
Once people believe "memory is broken" everyone sells.
But it's not true, so it accelerates the disconnect.
Step 9: Why AI actually strengthens memory
Every major AI bottleneck today involves memory.
Examples include 1) training (which needs enormous HBM stacks), 2) inference (which needs fast DRAM), 3) Long-context models (which need more memory), 4) Reasoning models (Need more memory), 5) multi-agent systems (Need more memory).
Basically every GPU sold requires memory.
Memory scales almost at a 1/1 ratio with AI compute.
Step 10: Why memory shortages likely continue
Everyone focuses on GPUs.
But GPUs without memory don't work ofc. So HBM capacity remains constrained.
Packaging remains constrained, yield improvements are slow, new fabs take years, demand is growing faster than supply, the same thesis everyone knows and loves has stayed the same.
So which stocks benefit (and which ones am I buying in here?
I would separate them into four groups.
Tier 1: Direct memory winners
1) Micron Technology: $MU
This is still the highest quality public memory company.
It is HBM leader, it has AI exposure, and the balance sheet is insane.
I have a lot of conviction here.
2) SanDisk: $SNDK
This is pure NAND exposure. It benefits from enterprise SSDs, the AI storage, hyperscalers, so it is more volatile than $MU, but potentially higher upside.
Tier 2: Memory equipment
These don't make memory (clearly).
They enable memory production.
Think of selling shovels to the miners in the gold rush. Besides this is selling the parts to make the shovels.
Often they outperform memory makers during capex cycles.
$OPTX is my favorite small cap AI infastructure play here.
If memory capex accelerates, inspection demand rises.
These companies often have enormous operating leverage.
$SHMD is another great one. It has strong exposure to semiconductor manufacturing equipment, and benefits from increasing fab investment.
Higher beta type of play here.
$ASYS is financially set and is in a perfect set up here.
This is perhaps the cleanest value equipment name. It has historically traded at surprisingly low multiples, yet it still benefits from:
- semiconductor capex
- advanced packaging
- AI manufacturing
If memory spending rebounds,
$ASYS should participate very well.
Tier 3: Memory infrastructure
$SIVE is the most interesting one here. It has recently been sold off over 60%.
And rather than directly making memory, it benefits from increasing semiconductor infrastructure spending.
It is smaller, less discovered, but potentially much larger percentage upside if execution continues.
Well all know about this name ofc.
Tier 4: Picks and shovels
These benefit regardless of which memory maker wins.
Examples include companies involved in: advanced packaging, thermal management, wafer handling
testing, photonics, substrates, etc..
Examples include (but are not limited to):
- $AAOI (my personal favorite out of these)
- $COHR
- $ACLS
- $CAMT
- $MKSI
- $ONTO
- $AMKR
These are often lower-risk ways to play memory capex because they sell to multiple manufacturers.
So which stocks have the highest upside?
If you're looking for asymmetric upside rather than the largest companies, I'd rank them:
1) $OPTX
2) $ASYS
3) $SIVE
4) $SHMD
5) $MU (safest bet here though).
Just my 2c on what happens next.
What are your guys thoughts?
plur daddy@plur_daddy
The 2nd biggest IPO in history is happening under your nose and it has created a unique buying opportunity in memory stocks. SK Hynix is listing its ADR on the Nasdaq and offering shares to institutional investors. What many have missed is the giga size of $26bn, which would have made it the 2nd largest IPO of all time, after SpaceX. As we saw, markets traded down into the SpaceX IPO. This is mechanical, as funds buying into the offering need to sell other shares to make room. What is unique about the SK Hynix ADR is that the funding sources are narrow and obvious: Korea-listed SK Hynix as well as Micron, Sandisk, Kioxia, and other similar memory names. The greatest pressure would be on Korea-listed SK Hynix, and my work suggests it could have been up to 20-25% of ADV per day since the offering was announced. Note that foreigners net sold Korean shares for 13 days in a row since the offering was announced, which helps confirm these flows. My sharp friends and I have been searching for the last week to explain the extreme sell-off in memory stocks, as while it felt natural for there to be a cleansing of froth amidst the rolling bull market in AI stocks we’ve seen since last year, it also felt unusually aggressive. This means it is quite possible $15-20bn of memory stocks have been sold into a narrow exit door, which explains their stunning declines, but also setting up the deck for reversion once these flows cease. You can’t forget that memory is the most important capex ingredient for AI, and everything points towards greater memory demand as LLM can more used, with bigger models and longer context windows. As the offering was over 7x oversubscribed, which is surprising for such a large secondary offering, it is probable that funds oversold and are now underexposed and will have to buy back once allocations are known during the trading day Thursday (likely in the afternoon). Of course, these flows lined up with exogenous factors that exacerbated the sell-off: frothy and overextended positioning, fears around memory efficiency gains, glimmers of the war restarting, Warsh coming in and being subtly hawkish. All of this came after SpaceX and the end of Q2 rebalance sucked out a lot of flows, which had made the market more fragile. After the stunningly good MU print, I was confused at how poorly it was trading, but now in hindsight it makes sense that is when the institutional VWAPs began. It is logical they would take advantage of the liquidity and demand created post-print to begin exiting in advance of the share offering, and as the negative factors accumulated, they got more aggressive on the offer to try to beat each other out. The offering is more than 7x oversubscribed: $26bn x 7 = $182bn. This does not mean that $182bn of memory stocks were sold, but there is some relationship between the amount that funds submit for, and the room they need to create. Especially for a secondary offering where it would be more normal to get better allocations versus a hot IPO where getting close to nothing is to be expected. The greatest amount of pressure would have been on SK Hynix (given the ADR will likely trade at a premium), which appears to have then created downwards momentum in Korea, which has been very leveraged, and already seeing other negative factors such as margin increases for retail trading accounts, and rumors of market negative government actions such as unrealized capital gains taxes (which I view as unlikely). If $15-20bn in the stocks were sold, that is a huge amount of flows to be hitting a few stocks, even if they are large in market cap. As I have explored in a past post about the right tail QQQ leaps, in the current market paradigm, even if market caps are large, free floats are deceptively small as passive flows have crowded them out. On the efficiency gains, I don’t have any particular insight into the claims although it is very possible they are true. The reality is that efficiency gains around memory are being constantly made. This is not a binary where any efficiency gains mean the end of the trade, rather you can view it as the way that extremely undersupplied buyers of memory are coping with a difficult situation. So even with constant efficiency gains, the situation remains undersupplied, and has a high probability of staying undersupplied. If you look at the memory supply/demand model created by my brilliant friend @AlexCorrino, who has gone deep on these technical nuances, there are good odds the supply deficit will widen much further over the coming years, despite assumptions of significant efficiency gains. Thus it became an excuse to sell, as memory was already acting very badly due to the pre-ADR mechanical flows, and then when the rumors hit, it created a setup where everyone felt like the efficiency gains were a big deal because the stocks had been acting so bad, and then sellers with different motivations were competing aggressively on the way out. It was a perfect storm, and it was a perfect storm that you are now poised to benefit from. Generally, these mechanical flows wash out stocks and set them up for reversion, because the baby was thrown out with the bathwater. In this case it is likely there was overselling so those funds will have to buy shares back. And many other holders have sold, and knowing this thesis will give them the confidence to buy it back. It is also probable that some funds that were aware of these flows shorted or sold memory stocks as a trade into that, and will have to buy them back as well. It’s a good setup, and while I can't say that prices will immediately make new highs now, it feels like a strong and defensible entry point into one of the most important trades of the year, an opportunity that does not come around often. Build medium-to-long term positions and be patient, I suspect it will be rewarding. Disclaimer: This is not financial or investment advice, it is not personalized to you, and it does not account for your objectives, risk tolerance, or situation. Nothing here is a recommendation, solicitation, or offer to buy or sell any security, private investment, or related asset, and nothing creates an advisory, fiduciary, or client relationship. The author holds positions in some of the companies discussed here. Positions can change at any time without notice, and there is no obligation to disclose, update, or correct them. The author is not paid by, and has no affiliate or sponsorship relationship with, any company mentioned. Assume a real, built-in conflict of interest, assume the content may be self-serving, and read it that way. Do your own work, check the primary sources, and consult your own licensed financial, legal, and tax professionals before you act on anything. Any decision you make is yours alone and made at your own risk.
English
@TW_trades_ he will be cutting loses again and taking a shitty swing trade
English
Sorry for such a long read guys (and sorry for not being able to post so much).
I'm travelling all over Europe, like I previously said.
So forgive me, please.
Also, I do think some of these AI enablers really have strong run ups soon (even stronger than we've seen) + the energy/power players look primed to gap up higher too.
Just my 2c.
*I forgot to add: credit goes to @mkfilko for the enabler/beneficiary term creation. Sorry for the late creds...
English
Some stock fields will perform better than others.
We got 5 areas of interest.
Here's how I'm playing this rotation:
Firstly, we are clearly in an AI enabler run up. These companies have been going up like crazy (look at $NVDA, $NBIS, etc.).
These will have the biggest run here imo.
So this is mainly where I'm positioned right now.
The top stocks I'm invested in are: $SHMD, $ASYS, $OPTX, $BRUN, $HIVE (some other notable ones I'm in are $MU, $IREN, $CRWV, $AAOI, etc.).
No, I'm not buying $NVDA or $NBIS here (I've stated why before, but not the best r/r here).
Along with AI enablers, I think power/energy stocks will have a major run soon.
Maybe at the same time.
Money flows to these two first and hardest because these are the binding constraints.
You can't scale AI without chips, interconnects/optics, memory, cooling, data center capacity, and reliable power.
Hyperscalers are guiding sustained massive capex; power shortages and grid delays are repeatedly cited as top risks by tech CEOs (and just logically thinking about it, probably are).
Some stocks I'm in for power/energy are: $SMR, $OKLO, $CEG, $VST, etc..
These are where I'm mostly positioned in here right now.
Maybe 75% of my holdings are between these 2 fields.
The rest are in the rest below.
So, third, I think AI beneficiaries will run.
After we get that AI enabler and energy/power run up, we will finally be able to see which AI beneficiaries will remain here.
Beneficiaries need the compute to be available and affordable at scale, plus proven ROI.
Mainly imo, we need to see that these AI models won't take over their business model.
We should see earnings growth continuing (while price decreases, or stays the same). This would make me very bullish.
I think the fear on these stocks is a lot, and so I'm positioning around 10% of my portfolio in these right now.
And will rotate more over if AI enablers run up even crazier.
Here are my top stocks for this niche: $ZETA, $DUOL, $NOW, $SOFI, $RDDT (we also got some other names that are good here too, in this field $WDAY, $INTU , $CRM, $TEAM, $SAP).
Now, fourth in line is robotics.
I do think this will be one of the biggest fields to change our world in 2027 and beyond.
Right now, early money is buying into some of these.
I am too (with a small %).
But, until we ride the other wave, this is more of a long-term position, and will perform great once we start seeing traction + tech advancing (so we can consolidate to actual winners).
My favorites here are: $VPG, $AMBA, $OUST, $HSAI, etc..
This makes up around 10% of my portfolio.
And lastly, we move onto Crypto.
I do think Bitcoin sentiment, and overall sentiment on crypto has been terrible.
Of all my time being here, this is like bottom of the bottom forming.
I'm not much into $MSTR here (this might be cooked long-term).
My main picks here are: $HOOD, $COIN, $HYPE, $ZEC, $PURR, $ZEC, $SOL, $CYPH, etc..
I think these will be transformative in the future, but I think these will need some time to officially bottom out.
Not some crazy run up.
But time so a bottom can form (I think it started to here).
This makes up around 5% (this includes other undervalued plays that I think are great here too: $NIO, $LYFT, $RIVN, $HIMS, $VKTX, etc.).
Hope this helps you all with understanding where I'm positioning myself over the course of these few months/years.
So TLDR:
AI enablers and Energy/Power -> AI beneficiaries -> Robotics -> Crypto.
In that order.
What are your guys' thoughts?
*Yes, I believe "smart money" is positioning themselves into crypto, AI beneficiaries, and robotics here. But, I don't think on the short-term they will have the best returns. That's why I'm in these enablers and energy stocks, and I'll rotate to the rest later on.
Con@__Con_
This post will go over exactly how I'm positioning myself in today's market. From my reasoning behind why I think certain sectors will run, to the stocks I'm holding. Here's my market outlook: There are a few niches worth investing in here. I think we can group them in 5 sectors: 1) Companies that enable AI growth (called AI enablers) 2) Companies that grow when AI grows (called AI beneficiaries) 3) Crypto (and companies that do well when $BTC and other cryptocurrencies perform well, called "betas") 4) Robotics (not just humanoid robots, I mean everything robotics) 5) Power/Energy (companies that will fuel the function of AI enablers) Here are a few reasons, and how I'm playing this: Firstly, we are in an energy world. We need energy. It is the new gold, as it powers everything. We got the U.S. government spending money on AI growth, and businesses with 0 clue how it works wanting to get in. I'm not going to say this is a once in a lifetime opportunity, but it's close to it lol. So it makes sense to bet on the companies producing this energy. Think: $SOLS, $OKLO, $SMR, $CEG, $VST, and $QS are a few. My top 3: $SOLS, $OKLO, and $SMR I have further theses for why I like these specifically, but you can just search them up on my profile though. Now, as we said, this is the base later: energy/power stocks. As we work our way up, we're getting closer and closer to "the source" = where the money is rotating to first. The next layer is "AI enablers," think data centers, photonics, semiconductor equipment, etc.. These should all continue to go up as business + government spending increases (seems like a clear trend, and nobody wants to be left behind). So I'm buying some names here: $OPTX, $ASYS, $SHMD $BRUN, $AAOI, $DGXX, $IREN, $NBIS, $MU and $CRWV. Again, my top 3 here are $OPTX, $ASYS, and $SHMD. You can read my reasoning by just searching these tickers up on my profile lol. Next, we got the "AI beneficiaries" or the stocks that will go up as AI continues to grow on its metrics. Right now, investors think AI will take over these businesses, but they don't realize AI is actually aiding them instead. If we look at the earnings of all of these companies it is increasing like wild, yet the price is down. Margins are also much better, but investors don't care, YET. So I'm buying in here. Some names: $ZETA, $RDDT, $NOW, $TEAM, to name a few. There are more, but that's a good list. Ok, now time for Robotics. We all know Robotics will be a world changing industry in the future. Legit. From cleaning, cooking, to humanoid robots. It's definitely worth having some $ in this sector. Here are my favorite ones: $OUST, $AMBA, $VPG, and even $TSLA. Yes, Tesla. And lastly, we got Crypto. Everyone is screaming $BTC to 40k, $ZEC is now worthless, $SOL is cooked. But I don't believe it. Every cycle there is some sort of FUD, and every cycle, we come out higher. Things seem to be bottoming out here. Nobody is buying in, and chart seems bottomed on the HTF. So, I'm positioning myself in a few of these for crypto exposure (I'm fine with being a bit early, since these are long-term): Think $COIN, $HOOD, $CYPH, $ZEC, $BTC, etc.. Of course, we can get some stocks in the middle of these: $CLSK, $MARA, $HUT, $HIVE (all which I think will be good). And some more undervalued companies: $NIO, $RIVN, $LYFT for the long-term. But this is just my 2c on where I'm investing in next. Any sectors I should look at, in which you guys are investing in here? What are your guys thoughts?
English
@afafmellaha This is for my main portfolio.
The 1k -> 100k is only in $BRUN (since it's an all in challenge ofc).
English
Yes, I sold my $NBIS.
But no, I'm not bearish on the market overall.
Here are the names I'm buying:
1) $OPTX
2) $ASYS
3) $SHMD
4) $BRUN
5) $GLXY
6) $HIVE
7) $PDYN
8) $MRLN
I'll write my thesis + TA review later, but I like these stocks a lot.
I think they're much better bets here.
Yes, this is specifically to companies enabling the AI build out. I'm in other companies that are in different niches.
Do with this information what you want, but I think this rotation will be very wise in the months to come.
What are your thoughts?
Con@__Con_
People are going to hate me for this: But now is not the time to buy $NBIS. I do think it's worth selling here. Let me explain why: 1) $NBIS operates in the AI data center / GPU cloud hosting layer ofc. Basically, selling compute capacity. This segment is becoming increasingly crowded and competitive: - Hyperscalers ($GOOGL, $AMZN, $MSFT, $META, etc.) are aggressively building their own internal capacity at massive scale. - Multiple specialized neoclouds and traditional providers are chasing the same constrained resources (power, land, GPUs, and interconnection). - As capacity comes online across the industry, utilization rates and pricing power can compress for pure hosting plays. 2) $NBIS has outlined multi-GW data center buildout plans. This creates elevated binary risks: - Power procurement and grid interconnection delays (a major industry bottleneck). - Construction and permitting timelines. - Actual customer utilization ramp after facilities come online. - High ongoing capex intensity to stay competitive. 3) $NBIS has geopolitical risk (origin overhang): - As a carve out from Yandex, $NBIS carries residual geopolitical perception risk (Russian origins, sanctions history), which can affect trust and long-term contracts with Western hyperscalers: Even as it focuses on US/Europe assets. 4) $NBIS valuation seems pretty high here: - In Q1 2026 earnings were decent. Revenue $399M (strong beat, massive YoY growth) and narrower EPS loss than expected. But it's still unprofitable. - They have crazy 2026 guidance ($3B–$3.4B+ revenue/ARR range discussed) which seems pretty aggressive and requires close to flawless execution on new capacity imo. - Insane Trailing Multiples: TTM P/S: 80x, EV/Revenue (TTM): 77x, Trailing P/E: 102–108x (on $2.60–2.92 EPS). Even high-growth AI names rarely sustain 50x+ trailing sales for long without massive profitability or clear path to it. - Still Losing Money on a Normalized/Operating Basis: Operating income TTM: –$619M (op margin deeply negative), EBITDA TTM: –$38.6M, normalized net income is negative; the big positive GAAP net income ($817M TTM / $621M in Q1) is also heavily boosted by unusual/one-time items (likely spin-off gains, investments, or fair value adjustments from the Yandex restructuring). - Forward P/S on Guided Revenue Is Still Premium (22x). At $71B mkt cap and $3.2B midpoint FY2026 guidance -> 22x forward sales. This is pretty crazy. 5) $NBIS technical analysis wise looks massively overbought): - We seem to be hitting the top of the 5 wave (out of the 1-2-3-4-5) on the HTF. On the LTF, we also seem to be hitting the wave 5, adding confluence to this resistance area. - We ran through the 1.618 level and 2.618 level showing a high sign of aggressive buying. Now we're at the 3.618 level, which means very aggressive buying has just occured. This is why, overall, I'm bearish $NBIS. "What are some other names worth buying then, and what should be my game plan?" I gotchu. $OPTX, $ASYS, and $SHMD are 3 great stocks. It's worth buying these right now imo. It's just not worth the risk holding $NBIS here, compared to them. Now, I don't fully dislike $NBIS (for a couple reasons), so here's how I'm going to play this out though: I'm going to sell my shares here (that I bought at 90). If $NBIS goes to 310, then uses the 3.618 level as support, then I will look to get in again, because that means we're going fully parabolic. It would mean losing a 5% move to the upside, on the potential of a large 20% move downward. That's why I'm doing this. Hope this makes sense on what I'm doing, and why. Of course, there are counter takes to these arguments (I'm not denying that). But, it's all about if those counterarguments make more sense. Right now, it seems we are very overbought, with a very high valuation. If we continue to run, and this "bubble" continues to grow, I'd happily join that (after losing out on a 5% run lol). If you enjoyed, pls lmk your guys' thoughts. And if you have any other sort of reasoning you guys want to come to me with, feel free to comment it below (I try to read everyone's comments, and respond ofc). Just my 2c and what I'm doing here.
English
Afaf retweetledi
ALL IN TRADE (1k-100k challenge):
We played this perfectly...
After a 5% gain on $BRUN the first trade, and 10% gain on $OPTX the second trade, I'm going for a bigger % gain this time.
Back in $BRUN.
Here's what I'm seeing:
BRUN/OPTX looks bottomed here (means BRUN should outperform OPTX here).
$BRUN also just consolidated over ATH levels, finished its A-B-C wave lower, and is looking like it wants to go much higher.
It also just survived massive FUD.
TLDR; I just bought $BRUN and closed my $OPTX here.
Trade receipts posted below...
@kevinxu @CKCapitalxx @bmthofficial you guys might like this post.
*This is a very, very small percent of my portfolio. My long-term positions are in $BRUN, $OPTX, and the other AI stocks such as $ASYS, etc., which are active.
Con@__Con_
Ok, I closed my $BRUN position at 35.40 (a 5% gain) and bought into $OPTX at 13.23. This is my new all-in trade idea (the second trade I'm taking). Here's why I switched: First, I will say both of the charts here ($OPTX and $BRUN look very good). So I think both will go up. I just think $OPTX will go up more here. Here's why: we got some extreme FUD on $BRUN here. It'll take some time to clear through the fog. If we take a look at BRUN/OPTX here (chart below), we did a bearish retest on the previous support (as resistance) and it looks like it wants to go lower. This means OPTX will outperform BRUN here. If we also look at OPTX/BRUN here (another chart below), we can see it looks like it has bottomed out after a retest and local higher low. Meaning OPTX should outperform BRUN here (showing more confluence). I like both of the theses for these stocks. And I'm holding both of these for my long-term portfolio, but for short-term trading, the simple % gains make a difference. Let me know your guy's thoughts, and tickers I should look at for short-term trades. @kevinxu I'm coming for you...
English
@afafmellaha @mkfilko Niceee...
Rn I'm almost at 1.5k, will aim for around upper 2ks maybe 3k on this trade...
I'm hoping we get you up there crazy too.
English
Will you look at that:
Since then, $BRUN is up 10%, while $OPTX is down 9%.
Perfect trades.
The all in challange from 1k to 100k will come sooner then expected.
Don't fade my calls next time.
Con@__Con_
ALL IN TRADE (1k-100k challenge): We played this perfectly... After a 5% gain on $BRUN the first trade, and 10% gain on $OPTX the second trade, I'm going for a bigger % gain this time. Back in $BRUN. Here's what I'm seeing: BRUN/OPTX looks bottomed here (means BRUN should outperform OPTX here). $BRUN also just consolidated over ATH levels, finished its A-B-C wave lower, and is looking like it wants to go much higher. It also just survived massive FUD. TLDR; I just bought $BRUN and closed my $OPTX here. Trade receipts posted below... @kevinxu @CKCapitalxx @bmthofficial you guys might like this post. *This is a very, very small percent of my portfolio. My long-term positions are in $BRUN, $OPTX, and the other AI stocks such as $ASYS, etc., which are active.
English
@mkfilko @afafmellaha LMAO
I agree itll go higher long term, but for the all in challenge we needa turn this 1k to 100k in 6 months...
English
App Store Screenshots (App Store Preview) Design
English
@onlinedopamine the question is how much they spend on those UGC formats ? where to find cheap ugc creators ?
English
this alarm clock app was launched just a month ago and already hit $50k in revenue & 2.7k app store ratings
they seem to have been running tons of ugc campaigns like the one shown below, with multiple accounts and videos hitting millions of views
the genius aspect about this app is that it was likely created with viral formats in mind because the alarm only stops when a given task is finished
so, instead of just pushing one format (e.g., alarm stops when doing pushups), they can scale this across almost any viral format / action the user has to perform
this is how you do apps in 2026
English
@mamkindesigner @screenshotfirst any suggestion on how to learn to design such screenshots ? thanks
English
I've designed screenshots for 350+ apps over 2 years.
The App Store is full of vibe coded lookalikes. Same layouts. Same gradients. Users scroll right past.
Every app needs its own visual language. One that stands out and converts.
Here are my favorites.
w/ @screenshotfirst
GIF
English
Tested a new App Store screenshot generator on my app screencut.app
Here’s the result – what do you think?
> screenfast.app
English
This is how much it cost to build 9 apps
to make over $50k/mo revenue
> Rork ( for building ): $20/mo
> Firebase( Database ): $5/mo
> Superwall ( payments ) $125/mo
> Apple dev $99/yr
Total: $170/mo
would you make this investment?
English