正在加载视频...

视频加载失败

返回首页

This Perplexity usecase blew my mind. I've always wanted a tool that tracks all S&P500 earnings and key things said by executives in their earnings calls. I simply do not have the time and bandwidth to read all 500. Prompt: I want an interactive dashboard that tracks every single...

TedHZhang's profile picture

Ted Zhang

68,270 subscribers

253,871 次观看 • 5 个月前 •via X (Twitter)

科学技术财经
LIVE

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

Chamath reveals that the real ROI of AI is just 0-2% for companies in the S&P 500 "The problem with enterprise revenue is that at some point, the person who's spending it has to see an ROI. I asked Fable, what is the lift of the S&P 500 earnings per share growth since 2024 from AI?" "Fable answered, oh it's 50%. Then I looked through it and I said well no, you're including the money that NVIDIA makes from selling chips." "I asked a different question; what was the EPS growth of the S&P 493? The answer was 9%. The overwhelming majority of that was from pricing power sitting on top of inflation, and then the other 3% was from buybacks." "So the answer, as far as all publicly available data shows, was that the actual ROI was somewhere between zero and 2%."
1:09

Chamath reveals that the real ROI of AI is just 0-2% for companies in the S&P 500 "The problem with enterprise revenue is that at some point, the person who's spending it has to see an ROI. I asked Fable, what is the lift of the S&P 500 earnings per share growth since 2024 from AI?" "Fable answered, oh it's 50%. Then I looked through it and I said well no, you're including the money that NVIDIA makes from selling chips." "I asked a different question; what was the EPS growth of the S&P 493? The answer was 9%. The overwhelming majority of that was from pricing power sitting on top of inflation, and then the other 3% was from buybacks." "So the answer, as far as all publicly available data shows, was that the actual ROI was somewhere between zero and 2%."

dnap

124,778 次观看 • 1 个月前

Josh Brown stripped every tech company out of the S&P 500 to see what was actually left: "even if you pull tech out, you're looking at 28.3% earnings growth. if you add tech back, it's 32%. it's outrageous" this is him explaining why every bearish narrative on this market is a money losing one, why the multiple everyone quotes makes no sense, and what the people running these companies have survived to get here "ten out of eleven sectors are getting profit growth. a lot of the narratives about it's all AI, or it's so narrow, it's concentrated - throw them all in the garbage. they're money losing narratives" "net income margin has been revised up to 15.6% from 15. sales growth is 15.2% - that's 300 plus basis points above what was expected as recently as two months ago" "is 20 times earnings cheap? no. but why would it be less? why would the multiple on this crop of companies be 16 times earnings because it was in 1994? it makes no sense - these companies are the Michael Jordan of every sector" "record inflation spike, the pandemic and all the difficulty hiring, then the tariff stuff - these are absolute warriors, the people running these companies" bookmark & watch the full conversation, then read the article below ↓
7:22

Josh Brown stripped every tech company out of the S&P 500 to see what was actually left: "even if you pull tech out, you're looking at 28.3% earnings growth. if you add tech back, it's 32%. it's outrageous" this is him explaining why every bearish narrative on this market is a money losing one, why the multiple everyone quotes makes no sense, and what the people running these companies have survived to get here "ten out of eleven sectors are getting profit growth. a lot of the narratives about it's all AI, or it's so narrow, it's concentrated - throw them all in the garbage. they're money losing narratives" "net income margin has been revised up to 15.6% from 15. sales growth is 15.2% - that's 300 plus basis points above what was expected as recently as two months ago" "is 20 times earnings cheap? no. but why would it be less? why would the multiple on this crop of companies be 16 times earnings because it was in 1994? it makes no sense - these companies are the Michael Jordan of every sector" "record inflation spike, the pandemic and all the difficulty hiring, then the tariff stuff - these are absolute warriors, the people running these companies" bookmark & watch the full conversation, then read the article below ↓

Сarm1ne

173,299 次观看 • 3 天前

About a month ago I built a new portfolio around the companies that make AI chips possible. Not the designers, but the infrastructure behind them. The stocks: $AMKR, $PLAB, $CLS, $ASX, $FN, $ONTO The portfolio is up 19% in ONE month. Everyone talks about $NVDA, but the real picks and shovels of the AI chip boom are in packaging (AMKR, ASX), contract manufacturing (CLS, FN), photomasks (PLAB), and process control equipment (ONTO). People keep asking why I chose these, so I had Perplexity Computer run a deep dive analysis on all six... 8 quarters of financials, gross/operating/net margin trends, debt and liquidity ratios, institutional ownership changes, insider buying and selling, full earnings call transcripts, beat/miss history, analyst price targets and recent upgrades, current valuation multiples vs 3 year historical averages, supply chain and geopolitical risk, capacity expansion stress tests, and a composite undervaluation ranking with the math shown. This is not financial advice, just a deep look at a sector I believe will outperform the broader market for the next decade.
8:49

About a month ago I built a new portfolio around the companies that make AI chips possible. Not the designers, but the infrastructure behind them. The stocks: $AMKR, $PLAB, $CLS, $ASX, $FN, $ONTO The portfolio is up 19% in ONE month. Everyone talks about $NVDA, but the real picks and shovels of the AI chip boom are in packaging (AMKR, ASX), contract manufacturing (CLS, FN), photomasks (PLAB), and process control equipment (ONTO). People keep asking why I chose these, so I had Perplexity Computer run a deep dive analysis on all six... 8 quarters of financials, gross/operating/net margin trends, debt and liquidity ratios, institutional ownership changes, insider buying and selling, full earnings call transcripts, beat/miss history, analyst price targets and recent upgrades, current valuation multiples vs 3 year historical averages, supply chain and geopolitical risk, capacity expansion stress tests, and a composite undervaluation ranking with the math shown. This is not financial advice, just a deep look at a sector I believe will outperform the broader market for the next decade.

Pepe Invests

1,091,473 次观看 • 4 个月前

I just built one of the greatest insider buying tracker tools of all time with Perplexity Computer. I wanted to find out one question: Which stocks actually have a high correlation of share price appreciation and insider buying? What Perplexity Computer built to answer this was truly amazing. Here's what it did: It pulled 1,301 real SEC Form 4 insider purchases across 184 S&P 500 stocks over the last 5 years. Then it tracked what happened to each stock AFTER insiders bought, measuring forward returns, win rates, and purchase frequency. It combined all of that into a single "Alpha Score" that ranks every stock by how reliably it goes up after insiders buy. The results? $COIN: 100% win rate. +187% average return after insider buys. $ET: 100% win rate. 52 purchases. $514M in total insider buying. $VST, $LUV, $CAT, $LLY, all 100% win rates. 73% of ALL insider purchases across the S&P 500 led to share price gains. But it didn't stop there. It also built: - A live purchase feed tracking every new SEC filing - Cluster buy detection (multiple insiders buying the same stock within 14 days) - A sector heatmap showing where insiders are putting their money - Top conviction buys (Berkshire's $2.1B OXY position, Musk's $1B TSLA buy) The whole thing looks like a Bloomberg terminal. Dark theme. Real time data. Fully interactive. I didn't write a single line of code. I just told Perplexity Computer what I wanted, and it researched the data, ran the analysis, and built the entire dashboard from scratch. This is the future of building things with AI. The best part was that it created a proprietary "Alpha Score" for every stock. This was a composite ranking from 0 to 100 that weighs four factors: 1. How often insiders bought (frequency) 2. How much money they put in (total value) 3. What percentage of buys led to gains (win rate) 4. How big those gains were (average forward return) The higher the Alpha Score, the stronger the correlation between insider buying and share price appreciation. It revealed insights you would've never expected. The energy sector ended up having the highest Alpha Score, meaning insiders buying energy stocks is very correlated with energy stocks surging. I have paid for data on insider buying in the past. I literally built a better tool with Perplexity Computer than the insider buying tools I have been using for the last 3 years.
0:24

I just built one of the greatest insider buying tracker tools of all time with Perplexity Computer. I wanted to find out one question: Which stocks actually have a high correlation of share price appreciation and insider buying? What Perplexity Computer built to answer this was truly amazing. Here's what it did: It pulled 1,301 real SEC Form 4 insider purchases across 184 S&P 500 stocks over the last 5 years. Then it tracked what happened to each stock AFTER insiders bought, measuring forward returns, win rates, and purchase frequency. It combined all of that into a single "Alpha Score" that ranks every stock by how reliably it goes up after insiders buy. The results? $COIN: 100% win rate. +187% average return after insider buys. $ET: 100% win rate. 52 purchases. $514M in total insider buying. $VST, $LUV, $CAT, $LLY, all 100% win rates. 73% of ALL insider purchases across the S&P 500 led to share price gains. But it didn't stop there. It also built: - A live purchase feed tracking every new SEC filing - Cluster buy detection (multiple insiders buying the same stock within 14 days) - A sector heatmap showing where insiders are putting their money - Top conviction buys (Berkshire's $2.1B OXY position, Musk's $1B TSLA buy) The whole thing looks like a Bloomberg terminal. Dark theme. Real time data. Fully interactive. I didn't write a single line of code. I just told Perplexity Computer what I wanted, and it researched the data, ran the analysis, and built the entire dashboard from scratch. This is the future of building things with AI. The best part was that it created a proprietary "Alpha Score" for every stock. This was a composite ranking from 0 to 100 that weighs four factors: 1. How often insiders bought (frequency) 2. How much money they put in (total value) 3. What percentage of buys led to gains (win rate) 4. How big those gains were (average forward return) The higher the Alpha Score, the stronger the correlation between insider buying and share price appreciation. It revealed insights you would've never expected. The energy sector ended up having the highest Alpha Score, meaning insiders buying energy stocks is very correlated with energy stocks surging. I have paid for data on insider buying in the past. I literally built a better tool with Perplexity Computer than the insider buying tools I have been using for the last 3 years.

Dividendology

184,157 次观看 • 5 个月前

🚨 THIS LOOKS REALLY SCARY We've seen this before: Dot-Com crash & 2008 crisis 1. The S&P 500 saw strong growth from 1995 to 1999 1995: +37.6% 1996: +23.0% 1997: +33.4% 1998: +28.6% 1999: +21.0% 5 year and then came a 50% CRASH 2. Later, since 2003, the S&P 500 rallied for another 5 straight years 2003: +28.68% 2004: +10.88% 2005: +4.91% 2006: +15.79% 2007: +5.49% 5 year and then came a 52% CRASH 3. Here's what the S&P 500 has done since 2023: 2023: +24.2% 2024: +23.3% 2025: +17.1% 2026: already +7.7% 2027: ??? Doesn't any of this concern you? Does it all really seem normal? Let's assume the S&P 500 is trading around $8,500-9,500 by the end of 2026 The market will have posted strong gains for 4 straight years, and most of that growth will have been driven by the tech sector But you're smart people - you understand that electricity demand from data centers, largely driven by AI, is growing extremely fast Many new data center projects in the U.S. are already being delayed or canceled because of grid capacity constraints, transformer shortages, and long connection wait times And if that continues, companies like Nvidia, Microsoft, Google, Amazon, and Meta could start issuing weaker AI revenue growth guidance for 2027-2028 That could force investors to reprice tech giants lower The market is already pricing in extremely aggressive AI growth expectations, so any slowdown could be painful On top of all that, SpaceX ( $SPCX ) starting trading today on Nasdaq, and it's also considered part of the tech sector Then later this year, the market could see IPOs from Anthropic and OpenAI as well Large IPO waves have historically impacted liquidity and investor sentiment Read this twice if you want to understand why I'm concerned about what's coming next I've said this before, and the cycle is still playing out exactly according to plan Turn on notifications and drop your thoughts below The next phase is gonna be very important
0:36

🚨 THIS LOOKS REALLY SCARY We've seen this before: Dot-Com crash & 2008 crisis 1. The S&P 500 saw strong growth from 1995 to 1999 1995: +37.6% 1996: +23.0% 1997: +33.4% 1998: +28.6% 1999: +21.0% 5 year and then came a 50% CRASH 2. Later, since 2003, the S&P 500 rallied for another 5 straight years 2003: +28.68% 2004: +10.88% 2005: +4.91% 2006: +15.79% 2007: +5.49% 5 year and then came a 52% CRASH 3. Here's what the S&P 500 has done since 2023: 2023: +24.2% 2024: +23.3% 2025: +17.1% 2026: already +7.7% 2027: ??? Doesn't any of this concern you? Does it all really seem normal? Let's assume the S&P 500 is trading around $8,500-9,500 by the end of 2026 The market will have posted strong gains for 4 straight years, and most of that growth will have been driven by the tech sector But you're smart people - you understand that electricity demand from data centers, largely driven by AI, is growing extremely fast Many new data center projects in the U.S. are already being delayed or canceled because of grid capacity constraints, transformer shortages, and long connection wait times And if that continues, companies like Nvidia, Microsoft, Google, Amazon, and Meta could start issuing weaker AI revenue growth guidance for 2027-2028 That could force investors to reprice tech giants lower The market is already pricing in extremely aggressive AI growth expectations, so any slowdown could be painful On top of all that, SpaceX ( $SPCX ) starting trading today on Nasdaq, and it's also considered part of the tech sector Then later this year, the market could see IPOs from Anthropic and OpenAI as well Large IPO waves have historically impacted liquidity and investor sentiment Read this twice if you want to understand why I'm concerned about what's coming next I've said this before, and the cycle is still playing out exactly according to plan Turn on notifications and drop your thoughts below The next phase is gonna be very important

Leni

81,430 次观看 • 2 个月前

quant at aqr sat next to me at a conference and said something that rewired how i think about markets "we don't analyze 500 stocks. we run 5 factors that explain all 500 at once" i asked him to draw it out take your entire stock universe - 500 names, 3 years of daily returns - and run PCA the 500 collapse into 5 factor 1: broad market momentum - explains 58% of all price movement by itself factor 2: sector rotation - where institutional money is actually flowing factor 3: rate sensitivity - duration risk bleeding across the equity curve factor 4: momentum tilt - which names are accelerating vs mean-reverting factor 5: credit spread stress - signal hiding inside equity vol if you know these 5 numbers, you know what 500 stocks are about to do retail watches 500 charts and sees noise. quant desks watch 5 eigenvalues and see structure math is called Principal Component Analysis, in every intro stats course on earth data to run it is free. python implementation is ~120 lines renaissance, two sigma, aqr - running this since before most retail traders could name a stock reason nobody told you isn't that it's proprietary it's that telling you costs them their edge Bookmark this market was never 500 moving parts it was always 5 - hiding inside 500
0:49

quant at aqr sat next to me at a conference and said something that rewired how i think about markets "we don't analyze 500 stocks. we run 5 factors that explain all 500 at once" i asked him to draw it out take your entire stock universe - 500 names, 3 years of daily returns - and run PCA the 500 collapse into 5 factor 1: broad market momentum - explains 58% of all price movement by itself factor 2: sector rotation - where institutional money is actually flowing factor 3: rate sensitivity - duration risk bleeding across the equity curve factor 4: momentum tilt - which names are accelerating vs mean-reverting factor 5: credit spread stress - signal hiding inside equity vol if you know these 5 numbers, you know what 500 stocks are about to do retail watches 500 charts and sees noise. quant desks watch 5 eigenvalues and see structure math is called Principal Component Analysis, in every intro stats course on earth data to run it is free. python implementation is ~120 lines renaissance, two sigma, aqr - running this since before most retail traders could name a stock reason nobody told you isn't that it's proprietary it's that telling you costs them their edge Bookmark this market was never 500 moving parts it was always 5 - hiding inside 500

Livsun

22,073 次观看 • 1 个月前

I JUST BUILT AN ENTIRE APP IN 10 MIN THAT PEOPLE WOULD PAY $100/MO TO ACCESS i gave perplexity computer one prompt and it built me an app that scans X, reddit, and forums for people literally asking for what you sell stuff like “anyone know a good…”, “looking for help with…”, “what’s the best tool for…” you drop in keywords and it tracks all of it in real time, then ranks each post based on how likely that person is to actually buy it turns every post into a lead with a summary, link, and intent score so you instantly know what’s worth responding to then you click once and it writes the DM, the reply, the cold email, even a content idea based on that post so instead of searching, thinking, rewriting, switching tabs… it’s just see signal → click → send i can save leads, track what i’ve responded to, and run multiple keyword streams at once i can’t code and this thing is basically a full lead gen engine + content machine in one dashboard comment "COMPUTER" and i'll send the exact prompt I used
1:23

I JUST BUILT AN ENTIRE APP IN 10 MIN THAT PEOPLE WOULD PAY $100/MO TO ACCESS i gave perplexity computer one prompt and it built me an app that scans X, reddit, and forums for people literally asking for what you sell stuff like “anyone know a good…”, “looking for help with…”, “what’s the best tool for…” you drop in keywords and it tracks all of it in real time, then ranks each post based on how likely that person is to actually buy it turns every post into a lead with a summary, link, and intent score so you instantly know what’s worth responding to then you click once and it writes the DM, the reply, the cold email, even a content idea based on that post so instead of searching, thinking, rewriting, switching tabs… it’s just see signal → click → send i can save leads, track what i’ve responded to, and run multiple keyword streams at once i can’t code and this thing is basically a full lead gen engine + content machine in one dashboard comment "COMPUTER" and i'll send the exact prompt I used

Ryan Hart

32,149 次观看 • 4 个月前

Wall Street is rewriting the rules of the S&P 500. And that not to protect your retirement. But to fast-track trillion-dollar money-losing AI companies into your portfolio. Let me explain what's about to happen. SpaceX, OpenAI, and Anthropic are all preparing to go public THIS YEAR. Combined expected market cap: roughly $3 TRILLION. SpaceX is targeting a June IPO at a $1.5-1.75 trillion valuation. It merged with xAI in February and plans to raise up to $50 billion - the largest IPO in American history. OpenAI is targeting Q4 2026. It just raised $110 billion at a $730 billion valuation from Amazon, SoftBank, and Nvidia. It projects a $14 billion LOSS this year. It doesn't expect to turn a profit until 2029 or 2030. It trades at 65 times revenue. Anthropic is valued at $380 billion. Also expected to list this year. Now here's where it gets dangerous for passive investors: From 2016 to 2025, the ENTIRE US IPO market raised $469 billion total. These 3 companies alone want to raise more than that in a single year. But it gets WORSE. S&P Dow Jones, Nasdaq, and FTSE Russell are ALL considering fast-track rules that would shove these companies into major indexes within DAYS of going public - bypassing the standard 12 month seasoning period. Roughly $24 trillion in passive funds is tied to the S&P 500 alone. Those funds MUST buy whatever gets added. So a company like OpenAI that's burning $14 billion a year, valued at 65x revenue, with no path to profitability for four years could become a mandatory holding in your 401k before it even reports a single quarterly earnings as a public company. Nasdaq is proposing a "Fast Entry" rule: inclusion after just 15 trading days. SpaceX reportedly made early index inclusion a CONDITION of choosing Nasdaq over the NYSE. The inmates are running the asylum. Index providers aren't rewriting rules because these companies earned their place. They're rewriting rules because SpaceX is too big to ignore and too lucrative to lose to a competing exchange. If all 10 of the largest venture-backed companies go public and get fast-tracked, their combined weight could reach 4.5% of the S&P 500 - more than the ENTIRE energy sector. Think about that. Companies that collectively lose billions per year could outweigh every oil and gas producer in America inside the most important retirement index on Earth. This is the passive indexation trap I've been warning about. You don't get to choose. You don't get to vote. The index committee decides, the ETFs execute, and your retirement savings follow orders. When the index is being engineered to absorb trillion-dollar speculative bets, the smartest move is to stop blindly following it. Own what you understand. Own what makes money. Own what's priced for reality, not fantasy. GOT GOLD?
0:50

Wall Street is rewriting the rules of the S&P 500. And that not to protect your retirement. But to fast-track trillion-dollar money-losing AI companies into your portfolio. Let me explain what's about to happen. SpaceX, OpenAI, and Anthropic are all preparing to go public THIS YEAR. Combined expected market cap: roughly $3 TRILLION. SpaceX is targeting a June IPO at a $1.5-1.75 trillion valuation. It merged with xAI in February and plans to raise up to $50 billion - the largest IPO in American history. OpenAI is targeting Q4 2026. It just raised $110 billion at a $730 billion valuation from Amazon, SoftBank, and Nvidia. It projects a $14 billion LOSS this year. It doesn't expect to turn a profit until 2029 or 2030. It trades at 65 times revenue. Anthropic is valued at $380 billion. Also expected to list this year. Now here's where it gets dangerous for passive investors: From 2016 to 2025, the ENTIRE US IPO market raised $469 billion total. These 3 companies alone want to raise more than that in a single year. But it gets WORSE. S&P Dow Jones, Nasdaq, and FTSE Russell are ALL considering fast-track rules that would shove these companies into major indexes within DAYS of going public - bypassing the standard 12 month seasoning period. Roughly $24 trillion in passive funds is tied to the S&P 500 alone. Those funds MUST buy whatever gets added. So a company like OpenAI that's burning $14 billion a year, valued at 65x revenue, with no path to profitability for four years could become a mandatory holding in your 401k before it even reports a single quarterly earnings as a public company. Nasdaq is proposing a "Fast Entry" rule: inclusion after just 15 trading days. SpaceX reportedly made early index inclusion a CONDITION of choosing Nasdaq over the NYSE. The inmates are running the asylum. Index providers aren't rewriting rules because these companies earned their place. They're rewriting rules because SpaceX is too big to ignore and too lucrative to lose to a competing exchange. If all 10 of the largest venture-backed companies go public and get fast-tracked, their combined weight could reach 4.5% of the S&P 500 - more than the ENTIRE energy sector. Think about that. Companies that collectively lose billions per year could outweigh every oil and gas producer in America inside the most important retirement index on Earth. This is the passive indexation trap I've been warning about. You don't get to choose. You don't get to vote. The index committee decides, the ETFs execute, and your retirement savings follow orders. When the index is being engineered to absorb trillion-dollar speculative bets, the smartest move is to stop blindly following it. Own what you understand. Own what makes money. Own what's priced for reality, not fantasy. GOT GOLD?

George Noble

29,435 次观看 • 4 个月前

🚨 THE S&P 500 IS MORE DANGEROUS RIGHT NOW THAN IT LOOKS The illusion of safety is what makes people poor. I keep seeing people say the same thing: “It probably won’t crash. It always goes up. Just buy the index.” That is exactly what concerns me. When you buy an individual stock, you understand you can lose money. But with the S&P 500, it is different. Most people do not even consider the possibility of a real crash anymore. Just look at the Dot-Com Bubble: Back then, everyone also thought everything was fine. The internet was real. The companies were real. The index kept climbing, and people convinced themselves it would keep climbing for years. But the final stage of every bubble begins when prices become absurd and fear disappears. And prices right now are absurd again. The S&P 500 is printing new highs with barely any meaningful pullbacks. AI-related stocks are carrying the index. Capital is concentrated in a small group of companies. And retail confidence is once again moving into extreme territory. That is where we are now. People are not buying because the setup is cheap. They are buying because they believe the S&P 500 cannot fail. Remember: the market becomes most vulnerable when the majority stops seeing any risk. For the record: I’ve called all the market tops and bottoms for the last 15 years, including the Bitcoin bottom at $16,000 and the top at $126,000. The next call will be even more important. When I exit the markets completely, I’ll post it here publicly like I always do. Turn notifications on. If you’re not following yet, you’ll understand why that was a mistake later.
0:30

🚨 THE S&P 500 IS MORE DANGEROUS RIGHT NOW THAN IT LOOKS The illusion of safety is what makes people poor. I keep seeing people say the same thing: “It probably won’t crash. It always goes up. Just buy the index.” That is exactly what concerns me. When you buy an individual stock, you understand you can lose money. But with the S&P 500, it is different. Most people do not even consider the possibility of a real crash anymore. Just look at the Dot-Com Bubble: Back then, everyone also thought everything was fine. The internet was real. The companies were real. The index kept climbing, and people convinced themselves it would keep climbing for years. But the final stage of every bubble begins when prices become absurd and fear disappears. And prices right now are absurd again. The S&P 500 is printing new highs with barely any meaningful pullbacks. AI-related stocks are carrying the index. Capital is concentrated in a small group of companies. And retail confidence is once again moving into extreme territory. That is where we are now. People are not buying because the setup is cheap. They are buying because they believe the S&P 500 cannot fail. Remember: the market becomes most vulnerable when the majority stops seeing any risk. For the record: I’ve called all the market tops and bottoms for the last 15 years, including the Bitcoin bottom at $16,000 and the top at $126,000. The next call will be even more important. When I exit the markets completely, I’ll post it here publicly like I always do. Turn notifications on. If you’re not following yet, you’ll understand why that was a mistake later.

Alex Mason 👁△

92,005 次观看 • 1 个月前

I built this CEO dashboard for my client. And it changed how they run their entire business. 1/ Before this dashboard, they were making decisions in the dark. Revenue, profit, and marketing spend scattered across spreadsheets and platforms. - No single source of truth. - No real-time profit and loss visibility. - No way to see which channels were actually driving growth. 2/ Here’s what this dashboard delivers: Executive Overview: → $102K total revenue tracked live → $79.8K gross profit and 78% gross margin calculated automatically → 15% contribution margin, updated in real time → $5,880 revenue this week, always visible Profit & Loss Clarity: → Visual breakdown of revenue, COGS, transaction costs, and marketing spend → Instantly see contribution margin and where profit is made (or lost) Revenue & COGS by Type: → Instantly compare new vs. returning revenue and costs → Know exactly what’s driving growth and what’s eating margin Marketing Spend by Channel: → Compare Meta vs. Google spend → See which channel is delivering the best ROI Revenue vs. Marketing Spend Trends: → Visualize how every marketing dollar translates to revenue over time Conversion & Order Insights: → Track sessions, orders, conversion rates, AOV, MER, CPA, and more live Dark mode or light mode? → This dashboard looks stunning with these two options. No more squinting at numbers. Details are always crystal clear. 3/ The transformation was instant: Before: → Hours spent pulling numbers from different platforms → Guessing at profit and loss → No clarity on which channel was working After: → 10 minutes daily reviewing live insights → Real-time, data-driven decisions → Confident budget allocation and growth planning 4/ The business impact: → Faster decisions → Smarter optimizations → A client who finally feels in control of their numbers This isn’t just a dashboard. This is executive intelligence. Every metric tells a story. Every trend reveals an opportunity. Every insight drives profit. Want a dashboard that makes your business look (and run) like a million bucks? I build custom dashboards & AI automation systems that give you real-time clarity and control. - Real-time data - Predictive insights - Automated reporting - Intelligent alerts Ready to stop guessing? Like + Comment "CEO DASHBOARD" and I’ll DM you a free resource to help you track the top 5 metrics every CEO should monitor.
0:43

I built this CEO dashboard for my client. And it changed how they run their entire business. 1/ Before this dashboard, they were making decisions in the dark. Revenue, profit, and marketing spend scattered across spreadsheets and platforms. - No single source of truth. - No real-time profit and loss visibility. - No way to see which channels were actually driving growth. 2/ Here’s what this dashboard delivers: Executive Overview: → $102K total revenue tracked live → $79.8K gross profit and 78% gross margin calculated automatically → 15% contribution margin, updated in real time → $5,880 revenue this week, always visible Profit & Loss Clarity: → Visual breakdown of revenue, COGS, transaction costs, and marketing spend → Instantly see contribution margin and where profit is made (or lost) Revenue & COGS by Type: → Instantly compare new vs. returning revenue and costs → Know exactly what’s driving growth and what’s eating margin Marketing Spend by Channel: → Compare Meta vs. Google spend → See which channel is delivering the best ROI Revenue vs. Marketing Spend Trends: → Visualize how every marketing dollar translates to revenue over time Conversion & Order Insights: → Track sessions, orders, conversion rates, AOV, MER, CPA, and more live Dark mode or light mode? → This dashboard looks stunning with these two options. No more squinting at numbers. Details are always crystal clear. 3/ The transformation was instant: Before: → Hours spent pulling numbers from different platforms → Guessing at profit and loss → No clarity on which channel was working After: → 10 minutes daily reviewing live insights → Real-time, data-driven decisions → Confident budget allocation and growth planning 4/ The business impact: → Faster decisions → Smarter optimizations → A client who finally feels in control of their numbers This isn’t just a dashboard. This is executive intelligence. Every metric tells a story. Every trend reveals an opportunity. Every insight drives profit. Want a dashboard that makes your business look (and run) like a million bucks? I build custom dashboards & AI automation systems that give you real-time clarity and control. - Real-time data - Predictive insights - Automated reporting - Intelligent alerts Ready to stop guessing? Like + Comment "CEO DASHBOARD" and I’ll DM you a free resource to help you track the top 5 metrics every CEO should monitor.

Lian Lim | Dashboard & AI Automation Expert

115,718 次观看 • 10 个月前

David Friedberg: The AI Jobs Panic Is a Crock of Sh*t Why? The revenue potential outweighs the cost savings by 100x. “There is no job loss with AI. I've said it a thousand times, and I will say it again, and again, and again. What I see on the ground, and what I've seen at dozens of companies, including my company that I run, there are two sides to a business. There is revenue and there’s costs. On the cost side of the equation, AI can be used to reduce humans doing things that cost money, to some extent. The effect there, I would argue, is nominal. The real opportunity with AI is on the revenue side, where suddenly one engineer can do 100x or 1000x what they used to be able to do, meaning you can make more products at your company, whether those are agricultural seed products, or boats and ships, or software for companies, or clothing, or what have you. Because of AI, everyone has the ability to expand their revenue base to create more products, and that is the foundation of good economic prosperity. It is called productivity. We can grow productivity in this country with AI. So where I see AI being used is on the revenue side 100x more than the cost side. And in that equation, people are hiring like crazy. We cannot hire enough people. I just had a review meeting with my product and engineering team two days ago, and they're like, ‘We want to add an extra 15 headcount to our engineering squads because we have all this opportunity to do stuff that we couldn't otherwise do.’ So we are going to hire more people. And to Sacks' point, we are seeing that show up in the jobs numbers. The idea that AI is going to destroy jobs is a Luddite idea that is being disproven every single day, and I see it on the ground. It is only a matter of time before people wake up to this and they realize that this narrative that they've all been sold is a crock of sh*t.”
1:42

David Friedberg: The AI Jobs Panic Is a Crock of Sh*t Why? The revenue potential outweighs the cost savings by 100x. “There is no job loss with AI. I've said it a thousand times, and I will say it again, and again, and again. What I see on the ground, and what I've seen at dozens of companies, including my company that I run, there are two sides to a business. There is revenue and there’s costs. On the cost side of the equation, AI can be used to reduce humans doing things that cost money, to some extent. The effect there, I would argue, is nominal. The real opportunity with AI is on the revenue side, where suddenly one engineer can do 100x or 1000x what they used to be able to do, meaning you can make more products at your company, whether those are agricultural seed products, or boats and ships, or software for companies, or clothing, or what have you. Because of AI, everyone has the ability to expand their revenue base to create more products, and that is the foundation of good economic prosperity. It is called productivity. We can grow productivity in this country with AI. So where I see AI being used is on the revenue side 100x more than the cost side. And in that equation, people are hiring like crazy. We cannot hire enough people. I just had a review meeting with my product and engineering team two days ago, and they're like, ‘We want to add an extra 15 headcount to our engineering squads because we have all this opportunity to do stuff that we couldn't otherwise do.’ So we are going to hire more people. And to Sacks' point, we are seeing that show up in the jobs numbers. The idea that AI is going to destroy jobs is a Luddite idea that is being disproven every single day, and I see it on the ground. It is only a matter of time before people wake up to this and they realize that this narrative that they've all been sold is a crock of sh*t.”

The All-In Podcast

152,225 次观看 • 2 个月前

$PLTR alright folks superbowl coming up after the bell regardless of what happens to the stock, being part of this community and getting to cover Palantir's journey has been one of the greatest blessings in my life. i really can't express my gratitude for people trusting me as a source for their Palantir news and coverage. it's been 4 years, 2k videos, 200 episodes of a weekly Palantir podcast...and I wouldn't have changed a single thing. having said that, we've got a ton of storylines going into earnings that can affect the stock: - is the SARs expense priced in or not? how bad is the hit? - does Palantir need to guide upwards of 35% YoY growth in 2025 for the street to be happy given the multiple its trading at or can they be at 30% and below? - if topline growth isn't as strong, are FCF growth, operating income margins, rule of 40, etc. enough to allow the street to feel Palantir will continue to grow into their potential? - if DeepSeek proved that LLMs are commodities and an LLM company like OpenAI is about to raise at $340B, what does that mean for a company like Palantir that's profitable and growing in the public markets? - what does government growth look like now with DOGE and can Palantir guide for some type of catalyst because of the government's willingness to spend more on software? Overall, I think Dr. Karp, Shaym Sankar and the entire team are going to crush it by essentially making the same argument they have made for 2 years: Palantir creates outcomes and that is what their customers pay for, not LLMs that can be found a dime-a-dozen and simply plugged into AIP, which is the software layered on Foundry that Palantir believes can create such incredible and transformative use cases (and we've seen many case studies of this already) that lead to them becoming one of the most important companies in the world. The stock will likely see algos and headlines that can move it, but this quarter is going to be determined by guidance, their ability to show continued growth and the market's overall interpretation of where Palantir lies in the broader AI sector. TIME TO EMBRACE ANOTHER CHAPTER IN THE ONGOING STORY OF ONE OF THE MOST EXCITING COMPANIES ON PLANET EARTH. & the best part is, we get to all embrace that chapter together, as a community. LFG.
1:58

$PLTR alright folks superbowl coming up after the bell regardless of what happens to the stock, being part of this community and getting to cover Palantir's journey has been one of the greatest blessings in my life. i really can't express my gratitude for people trusting me as a source for their Palantir news and coverage. it's been 4 years, 2k videos, 200 episodes of a weekly Palantir podcast...and I wouldn't have changed a single thing. having said that, we've got a ton of storylines going into earnings that can affect the stock: - is the SARs expense priced in or not? how bad is the hit? - does Palantir need to guide upwards of 35% YoY growth in 2025 for the street to be happy given the multiple its trading at or can they be at 30% and below? - if topline growth isn't as strong, are FCF growth, operating income margins, rule of 40, etc. enough to allow the street to feel Palantir will continue to grow into their potential? - if DeepSeek proved that LLMs are commodities and an LLM company like OpenAI is about to raise at $340B, what does that mean for a company like Palantir that's profitable and growing in the public markets? - what does government growth look like now with DOGE and can Palantir guide for some type of catalyst because of the government's willingness to spend more on software? Overall, I think Dr. Karp, Shaym Sankar and the entire team are going to crush it by essentially making the same argument they have made for 2 years: Palantir creates outcomes and that is what their customers pay for, not LLMs that can be found a dime-a-dozen and simply plugged into AIP, which is the software layered on Foundry that Palantir believes can create such incredible and transformative use cases (and we've seen many case studies of this already) that lead to them becoming one of the most important companies in the world. The stock will likely see algos and headlines that can move it, but this quarter is going to be determined by guidance, their ability to show continued growth and the market's overall interpretation of where Palantir lies in the broader AI sector. TIME TO EMBRACE ANOTHER CHAPTER IN THE ONGOING STORY OF ONE OF THE MOST EXCITING COMPANIES ON PLANET EARTH. & the best part is, we get to all embrace that chapter together, as a community. LFG.

amit

180,612 次观看 • 1 年前

🚨 WARNING: SOMETHING VERY WIERD IS HAPPENING. The S&P 500 keeps printing new highs. Everyone is celebrating. Nobody is looking at what's actually holding it up. Semiconductor stocks are now worth $13.4 trillion. 19.7% of the entire index. Five years ago that number was closer to 5%. It quadrupled in a single cycle on a single bet. AI. And here's the number that should concern everyone. AI chips generate 50% of all semiconductor revenue. They represent less than 0.2% of total chip shipments. Half the revenue, a fraction of the volume, trillions in market cap sitting on top of a sliver of actual production. Three companies are carrying all of it. Nvidia. Broadcom. TSMC. The same names in every major institutional portfolio simultaneously. Everyone owns them, nobody can afford to be the first one out. And the way the money moves inside this system should sound familiar. Big players fund AI startups. AI startups spend that money on Big Tech infrastructure. Big Tech reports record AI revenue. Valuations justify the next round, the same dollar completes the loop and gets counted as growth every time. We watched this exact dynamic play out once before. 2000. A handful of tech companies carried the entire market. Valuations made no sense, narratives did the work that fundamentals couldn't. Then one company missed earnings, then another, then the S&P lost 50% and the Nasdaq lost 78%. The current setup is more concentrated, the valuations are more extreme. And one cut in AI spending is all it takes to start the unwind. I called the $16K Bitcoin bottom. I called the $126K top. Every major turn for 15 years public, before the move. The next call is already forming. Follow now and turn on notifications, you'll understand why that matters sooner than you think.
0:34

🚨 WARNING: SOMETHING VERY WIERD IS HAPPENING. The S&P 500 keeps printing new highs. Everyone is celebrating. Nobody is looking at what's actually holding it up. Semiconductor stocks are now worth $13.4 trillion. 19.7% of the entire index. Five years ago that number was closer to 5%. It quadrupled in a single cycle on a single bet. AI. And here's the number that should concern everyone. AI chips generate 50% of all semiconductor revenue. They represent less than 0.2% of total chip shipments. Half the revenue, a fraction of the volume, trillions in market cap sitting on top of a sliver of actual production. Three companies are carrying all of it. Nvidia. Broadcom. TSMC. The same names in every major institutional portfolio simultaneously. Everyone owns them, nobody can afford to be the first one out. And the way the money moves inside this system should sound familiar. Big players fund AI startups. AI startups spend that money on Big Tech infrastructure. Big Tech reports record AI revenue. Valuations justify the next round, the same dollar completes the loop and gets counted as growth every time. We watched this exact dynamic play out once before. 2000. A handful of tech companies carried the entire market. Valuations made no sense, narratives did the work that fundamentals couldn't. Then one company missed earnings, then another, then the S&P lost 50% and the Nasdaq lost 78%. The current setup is more concentrated, the valuations are more extreme. And one cut in AI spending is all it takes to start the unwind. I called the $16K Bitcoin bottom. I called the $126K top. Every major turn for 15 years public, before the move. The next call is already forming. Follow now and turn on notifications, you'll understand why that matters sooner than you think.

Hanzo ㊗️

18,356 次观看 • 1 个月前

The November jobs number supports a 25 basis point rate cut, but the data is soft and slightly inaccurate because of the 43-day shutdown. If that hadn’t happened, the trend would point toward higher unemployment, which is one of the Fed’s key mandates. Inflation is still at 3.1%, though, and that puts the Fed in a very difficult position. Every rate cut from here will be heavily scrutinized and debated, and you’re already seeing dissent inside the Fed. That’s what the market is focused on, whether we get more cuts into year end. I look at this purely through the lens of an investor. I invest across all 11 sectors of the S&P, mostly in companies with 5 to 500 employees, so I hear their concerns directly. Input costs are a major issue, especially unresolved tariffs on goods we don’t produce in America, things like bananas, pineapples, and potash. Why tariff things we don’t have? Those costs show up in housing, manufacturing, and across the economy, and that’s a big reason inflation stays elevated. This isn’t just theory, it’s what companies are actually paying.
2:32

The November jobs number supports a 25 basis point rate cut, but the data is soft and slightly inaccurate because of the 43-day shutdown. If that hadn’t happened, the trend would point toward higher unemployment, which is one of the Fed’s key mandates. Inflation is still at 3.1%, though, and that puts the Fed in a very difficult position. Every rate cut from here will be heavily scrutinized and debated, and you’re already seeing dissent inside the Fed. That’s what the market is focused on, whether we get more cuts into year end. I look at this purely through the lens of an investor. I invest across all 11 sectors of the S&P, mostly in companies with 5 to 500 employees, so I hear their concerns directly. Input costs are a major issue, especially unresolved tariffs on goods we don’t produce in America, things like bananas, pineapples, and potash. Why tariff things we don’t have? Those costs show up in housing, manufacturing, and across the economy, and that’s a big reason inflation stays elevated. This isn’t just theory, it’s what companies are actually paying.

Kevin O'Leary aka Mr. Wonderful

59,069 次观看 • 8 个月前

SpaceX is reportedly moving toward an IPO — and investors are starting to ask which public-market tickers stand to benefit most as the commercial space sector draws fresh capital. This is what Aerospace Catalyst Tracker is built to answer. The Play tracks the operational signals that drive stock-level repricing — launch cadence, Starlink deployment, and competitive dynamics — across the companies most exposed to space-sector catalysts. Here's what the Play covers today: Launch Cadence & Multi-Operator Tracking Every orbital launch is tracked in real time — operator, vehicle, payload, outcome, and schedule changes. The Play covers SpaceX (Falcon 9 / Starship), Rocket Lab (Electron / Neutron), ULA (Vulcan Centaur), and Blue Origin (New Glenn) — the four operators defining the current competitive landscape. For each, we monitor launch frequency trends, success rates, manifest backlogs, and quarter-over-quarter share shifts. SpaceX booster reuse and turnaround cadence are tracked separately as a leading indicator of cost-curve compression. Starlink Deployment & Constellation Growth A dedicated module tracks Starlink satellite launches, orbital deployment counts, and multi-country pricing. We map deployment cadence against constellation build-out milestones — useful for investors sizing the revenue trajectory ahead of any IPO filing. Alert System The Play monitors large-value aerospace contract awards as they are disclosed — flagging dollar amounts, recipient tickers, and related news signals in real time. Recent alerts include multi-billion-dollar awards to LMT and BA, and NASA infrastructure contracts. When a contract hits that moves a name in the supply chain, it surfaces immediately in your feed. Aerospace Catalyst Tracker is now live on FUNDA for institutional clients. For a limited time, all paid Substack subscribers can access the full set through June 15, 2026.
0:39

SpaceX is reportedly moving toward an IPO — and investors are starting to ask which public-market tickers stand to benefit most as the commercial space sector draws fresh capital. This is what Aerospace Catalyst Tracker is built to answer. The Play tracks the operational signals that drive stock-level repricing — launch cadence, Starlink deployment, and competitive dynamics — across the companies most exposed to space-sector catalysts. Here's what the Play covers today: Launch Cadence & Multi-Operator Tracking Every orbital launch is tracked in real time — operator, vehicle, payload, outcome, and schedule changes. The Play covers SpaceX (Falcon 9 / Starship), Rocket Lab (Electron / Neutron), ULA (Vulcan Centaur), and Blue Origin (New Glenn) — the four operators defining the current competitive landscape. For each, we monitor launch frequency trends, success rates, manifest backlogs, and quarter-over-quarter share shifts. SpaceX booster reuse and turnaround cadence are tracked separately as a leading indicator of cost-curve compression. Starlink Deployment & Constellation Growth A dedicated module tracks Starlink satellite launches, orbital deployment counts, and multi-country pricing. We map deployment cadence against constellation build-out milestones — useful for investors sizing the revenue trajectory ahead of any IPO filing. Alert System The Play monitors large-value aerospace contract awards as they are disclosed — flagging dollar amounts, recipient tickers, and related news signals in real time. Recent alerts include multi-billion-dollar awards to LMT and BA, and NASA infrastructure contracts. When a contract hits that moves a name in the supply chain, it surfaces immediately in your feed. Aerospace Catalyst Tracker is now live on FUNDA for institutional clients. For a limited time, all paid Substack subscribers can access the full set through June 15, 2026.

FUNDA

12,777 次观看 • 2 个月前

Listen to me. I've MADE you millions and now, I will SAVE you millions. You NEED to stay careful here. The next timing cycle is a week away. While retail is trying to PUSH the markets higher, we (smart money) are TRIMMING out and locking in some gains. What's happening? 1. Dollar $DXY - is breaking out, this is not a good sign for equities 2. High-yield bonds $HYG - they are a leading indicator, it's breaking down ahead of $SPY 3. S&P 500 $SPY - buying momentum is starting to fade 4. Volatility Index $VIX - the VIX is at support, not the best time to go big into equities What should you do? 1. I've been telling you to TRIM your top winners 2. No need to sell FULLY, just 20% - 30% so you can lock-in those gains 3. Keep it BALANCED for the next 5 months, high growth + defensive stocks Where's the opportunities? 1. Buy the DIP on AI - it will happen $MU, $ARM, etc. 2. Position some into consumer defense $WMT, $KO, $MCD, $HD, etc. 3. Get STRONG companies at lows - not CRAP companies at lows $ADBE, $NOW, etc. 4. Relative strength winners in space $RKLB, $PL, $BKSY, $LUNR, etc. 5. Healthcare and financials - they will go down, but down less that tech $V, $MA, $LLY I share all my buy and sell signals, follow my every move so you never lose any money.
2:24

Listen to me. I've MADE you millions and now, I will SAVE you millions. You NEED to stay careful here. The next timing cycle is a week away. While retail is trying to PUSH the markets higher, we (smart money) are TRIMMING out and locking in some gains. What's happening? 1. Dollar $DXY - is breaking out, this is not a good sign for equities 2. High-yield bonds $HYG - they are a leading indicator, it's breaking down ahead of $SPY 3. S&P 500 $SPY - buying momentum is starting to fade 4. Volatility Index $VIX - the VIX is at support, not the best time to go big into equities What should you do? 1. I've been telling you to TRIM your top winners 2. No need to sell FULLY, just 20% - 30% so you can lock-in those gains 3. Keep it BALANCED for the next 5 months, high growth + defensive stocks Where's the opportunities? 1. Buy the DIP on AI - it will happen $MU, $ARM, etc. 2. Position some into consumer defense $WMT, $KO, $MCD, $HD, etc. 3. Get STRONG companies at lows - not CRAP companies at lows $ADBE, $NOW, etc. 4. Relative strength winners in space $RKLB, $PL, $BKSY, $LUNR, etc. 5. Healthcare and financials - they will go down, but down less that tech $V, $MA, $LLY I share all my buy and sell signals, follow my every move so you never lose any money.

AskLivermore

500,055 次观看 • 3 个月前

This is the biggest irony in tech history. Microsoft beat revenue estimates. Stock plunged 11%, wiped out $400 BILLION in market cap. Salesforce reported growth. Stock fell 5.6%. ServiceNow beat earnings. Stock crashed 11%. SAP beat projections. Stock dropped 16%. Entire software sector entered bear market territory. Down 22% from peak. These are the companies everyone said would WIN from AI. They spent billions BUYING AI companies. ServiceNow: $7.75 billion for Armis. Salesforce: $8 billion for Informatica. They launched AI products. Built AI workflows. Hired AI teams. And the market said: You're all dead. Because investors just realized something nobody wanted to admit: AI doesn't make software companies stronger. AI makes software companies OBSOLETE. Morgan Stanley: "In an environment of heightened investor skepticism, stable growth falls short of shifting the narrative." Good earnings aren't enough anymore. The market is pricing in a world where AI replaces the software these companies sell. ServiceNow CEO tried defending on the earnings call: "AI needs workflow orchestration. ServiceNow is the gateway to this shift." Market response: 11% crash. Because here's what he didn't say: If AI can write code, automate workflows, and generate apps at a fraction of the cost, why would anyone pay $50,000 per year for enterprise software licenses? The per-seat pricing model that made SaaS companies rich is getting murdered by AI efficiency. One AI agent replaces 10 seats. One prompt replaces months of custom development. One LLM call replaces entire software categories. Klarna already proved it. CEO said they pulled Salesforce out of their stack. Built everything themselves using AI. And that's just the beginning. The software apocalypse hit hardest on companies that INVESTED IN AI: Atlassian: down 12.6% Intuit: down 7.8% HubSpot: down 11.5% Zscaler: down 6.3% Meanwhile, the companies ENABLING AI made money: Nvidia: up Semiconductor stocks: surging Memory firms: rallying The divide is brutal. Hardware companies print cash. Software companies get destroyed. Because in an AI-first world, you need GPUs to build the models. But you don't need software subscriptions when the AI builds the software for you. Jim Cramer called it the "P/E multiple compression crisis." Translation: Investors don't care about earnings anymore. They care about whether your business model survives the next 5 years. And right now software business models look doomed. They're literally stuck: If they DON'T invest in AI, they fall behind. If they DO invest in AI, they cannibalize their own products. It's a death spiral with no exit. ServiceNow spent $12 BILLION on acquisitions in 2025 alone. Trying to buy their way into relevance. And yesterday the market cooked them. The craziest thing to me tho... Most software companies beat earnings. Revenue was solid. Growth was fine. But it didn't matter. Because the market stopped pricing software on what it earns TODAY. It's pricing software on what it's worth in a world where AI does the job for free. And in that world these companies are worth nothing. This is the biggest sector repricing since 2008. $500 billion in market value gone in ONE DAY. And it's not stopping. Because every company watching this is thinking the same thing: "If I can replace ServiceNow with 3 AI agents and save $10 million per year, why wouldn't I?" The answer used to be: "Because you need enterprise-grade reliability." But now? AI agents are getting reliable. Fast. Software companies just realized they're competing with open-source models that cost $0.02 per 1,000 tokens. You can't win a pricing war against free. The companies that spent BILLIONS preparing for AI are getting killed BY AI. What an irony.
1:54

This is the biggest irony in tech history. Microsoft beat revenue estimates. Stock plunged 11%, wiped out $400 BILLION in market cap. Salesforce reported growth. Stock fell 5.6%. ServiceNow beat earnings. Stock crashed 11%. SAP beat projections. Stock dropped 16%. Entire software sector entered bear market territory. Down 22% from peak. These are the companies everyone said would WIN from AI. They spent billions BUYING AI companies. ServiceNow: $7.75 billion for Armis. Salesforce: $8 billion for Informatica. They launched AI products. Built AI workflows. Hired AI teams. And the market said: You're all dead. Because investors just realized something nobody wanted to admit: AI doesn't make software companies stronger. AI makes software companies OBSOLETE. Morgan Stanley: "In an environment of heightened investor skepticism, stable growth falls short of shifting the narrative." Good earnings aren't enough anymore. The market is pricing in a world where AI replaces the software these companies sell. ServiceNow CEO tried defending on the earnings call: "AI needs workflow orchestration. ServiceNow is the gateway to this shift." Market response: 11% crash. Because here's what he didn't say: If AI can write code, automate workflows, and generate apps at a fraction of the cost, why would anyone pay $50,000 per year for enterprise software licenses? The per-seat pricing model that made SaaS companies rich is getting murdered by AI efficiency. One AI agent replaces 10 seats. One prompt replaces months of custom development. One LLM call replaces entire software categories. Klarna already proved it. CEO said they pulled Salesforce out of their stack. Built everything themselves using AI. And that's just the beginning. The software apocalypse hit hardest on companies that INVESTED IN AI: Atlassian: down 12.6% Intuit: down 7.8% HubSpot: down 11.5% Zscaler: down 6.3% Meanwhile, the companies ENABLING AI made money: Nvidia: up Semiconductor stocks: surging Memory firms: rallying The divide is brutal. Hardware companies print cash. Software companies get destroyed. Because in an AI-first world, you need GPUs to build the models. But you don't need software subscriptions when the AI builds the software for you. Jim Cramer called it the "P/E multiple compression crisis." Translation: Investors don't care about earnings anymore. They care about whether your business model survives the next 5 years. And right now software business models look doomed. They're literally stuck: If they DON'T invest in AI, they fall behind. If they DO invest in AI, they cannibalize their own products. It's a death spiral with no exit. ServiceNow spent $12 BILLION on acquisitions in 2025 alone. Trying to buy their way into relevance. And yesterday the market cooked them. The craziest thing to me tho... Most software companies beat earnings. Revenue was solid. Growth was fine. But it didn't matter. Because the market stopped pricing software on what it earns TODAY. It's pricing software on what it's worth in a world where AI does the job for free. And in that world these companies are worth nothing. This is the biggest sector repricing since 2008. $500 billion in market value gone in ONE DAY. And it's not stopping. Because every company watching this is thinking the same thing: "If I can replace ServiceNow with 3 AI agents and save $10 million per year, why wouldn't I?" The answer used to be: "Because you need enterprise-grade reliability." But now? AI agents are getting reliable. Fast. Software companies just realized they're competing with open-source models that cost $0.02 per 1,000 tokens. You can't win a pricing war against free. The companies that spent BILLIONS preparing for AI are getting killed BY AI. What an irony.

Ricardo

1,814,969 次观看 • 6 个月前

Making Sense Of Bitcoin Treasury Companies If you've been following me on X you’ll know that I have recently been floating a lot of my updated thoughts on the Bitcoin Treasury space. Here I have synthesised all of my ideas and distilled them into a single video. If you prefer YouTube, you can find the link in the comments. If you prefer written format, continue reading. The first thing we need to do is acknowledge an important fact which is that Strategy, as a Bitcoin Treasury Company, is an anomaly. What do I mean by that? Strategy’s success has been defined by a number of unique factors and circumstances, most of which cannot be replicated again by other Bitcoin Treasury Companies. Specifically, there are 6 things that stand out to me. 1. Before adopting Bitcoin, Strategy was a billion dollar company with an operating business that was generating roughly $50M in cash a year. 2. Until the introduction of the ETF's in January 2024, Strategy was the only way for the average investor to gain passive exposure to Bitcoin. 3. Until this year, Strategy was the only way for the average investor to gain leveraged exposure to Bitcoin. 4. Strategy was issuing multiple, billion dollar, zero coupon, unsecured convertible notes at +50% conversion premiums. 5. Strategy has Michael Saylor, who, you don’t need me to tell you, is in a league of his own. 6. For many reasons, including those I’ve just mentioned, Strategy has benefitted disproportionately from the broader sentiment around Bitcoin. In other words, for the best part of 4 years, Strategy had zero competition for either capital or attention. As a result, it became a magnet for capital from anyone who wanted exposure to Bitcoin and it attracted inflows that were beyond what fundamentals alone would maybe justify. Therefore, using Strategy as a blueprint for the performance that you can expect from other Bitcoin Treasury Companies is a bad idea. Using Strategy as a blueprint for how to operate a Bitcoin Treasury Company is a good idea. Now let’s break down what’s unfolded over the last 6 months or so. Between May and June of this year, when we witnessed a flood of new Bitcoin Treasury Companies, we entered what I refer to as the frenzy phase. The frenzy phase was driven almost entirely by sentiment. By sentiment I simply mean emotion. Since then, as sentiment has slowly faded, the market has increasingly priced Bitcoin Treasury Companies based more on fundamentals. By fundamentals I simply mean facts. So where as sentiment is driven by emotion and hype, fundamentals are driven by facts and reason. The problem is that when you price Bitcoin Treasury Companies on fundamentals, you realise that many of them are almost entirely dependent on sentiment in order to expand mNAV so they can raise capital via the common stock ATM to buy Bitcoin and generate Bitcoin Yield. However, for me, raising capital via the common stock ATM and recycling it into Bitcoin is not genuine value creation — it’s value transfer. That’s not to say you shouldn’t leverage the ATM as and when necessary — you should. However, if your business model as a Bitcoin Treasury Company no longer works when “sentiment is low” then you have neither a business model nor a business. You’re the equivalent of a meme stock except with Bitcoin on your balance sheet. On that basis, companies shouldn’t expect to trade at a premium if the common stock ATM is the only way they raise capital. I’m not saying they won’t trade at a premium — I’m saying that companies shouldn’t expect to. Now, between July and now, we’ve obviously seen mNAVs compress substantially and so the frenzy phase is over which means that the days of automatically being granted generous mNAV multiples is also over. So now we are in the maturity phase. The maturity phase is going to be defined by being able to offer a differentiated value proposition and having a sustainable business model that can generate Bitcoin Yield in any environment independent of sentiment. In other words, they can generate Bitcoin Yield when trading at or below 1 mNAV. So essentially now, Bitcoin Treasury Companies have to work for their mNAV multiples — as it should be. Following the maturity phase will be the consolidation phase where capital, Bitcoin and ultimately market share will converge towards a small number of Bitcoin Treasury Companies that will dominate the entire industry. I should clarify that I am referring predominantly to pure-play Bitcoin Treasury Companies — companies who are valued based solely on their Bitcoin strategy. Now, with everything that I’ve said, how should you evaluate Bitcoin Treasury Companies? Hopefully over the next few weeks I’m going to string together a video with my valuation framework. In the meantime, a basic test is that I use is this: How much Bitcoin Yield can the company generate over X period of time — you decide what that period of time is — if it traded at 1x mNAV over that entire period? If the answer is 0, then they are probably entirely dependent on raising capital via the common stock ATM which means they likely don’t deserve a premium. If the answer is >0, then they are probably innovating through the use of other instruments — like converts and preferred products — which means they likely do deserve a premium and so whatever number you come up with should be used as the base for your valuation. Now, don’t be fooled. The Bitcoin Treasury Company space is, not entirely, but to a large degree, a zero-sum game. Every Dollar raised by one Bitcoin Treasury Company is at the expense of every other Bitcoin Treasury Company. Every Bitcoin purchased by one Bitcoin Treasury Company is at the expense of every other Bitcoin Treasury Company. It’s only because we are early that everyone is incentivised to essentially hold hands and cheer each other on. However, make no mistake, everyone involved is tacitly well aware that they are all competing for the same finite amount of capital and the same fixed amount of Bitcoin. Thus, the reality is that, by definition, not every Bitcoin Treasury Company is going to succeed. So choose your horses and jockeys wisely. As a side note, with the amount of Bitcoin Treasury Companies now desperately chasing and competing for the same capital from institutions, who do you think has the leverage; the Bitcoin Treasury Companies or the institutions? I’ll let you decide. Before I close, I want to leave you guys with this. There is a small subset of people invested in Bitcoin Treasury Companies who are desperately clinging on to their bags because they believe “sentiment will return.” These people are completely missing the point. My friends, if your investing philosophy is based on sentiment, you are simply not going to last. You want to base your decisions, as far as possible, on fundamentals. As investors, you either adapt and update your mental models based on how things are and not how you want them to be — or you get left behind. With that in mind: Never get caught up in tribalism. Never get attached to your beliefs. Always think critically. Always think independently. Always seek Truth.
10:20

Making Sense Of Bitcoin Treasury Companies If you've been following me on X you’ll know that I have recently been floating a lot of my updated thoughts on the Bitcoin Treasury space. Here I have synthesised all of my ideas and distilled them into a single video. If you prefer YouTube, you can find the link in the comments. If you prefer written format, continue reading. The first thing we need to do is acknowledge an important fact which is that Strategy, as a Bitcoin Treasury Company, is an anomaly. What do I mean by that? Strategy’s success has been defined by a number of unique factors and circumstances, most of which cannot be replicated again by other Bitcoin Treasury Companies. Specifically, there are 6 things that stand out to me. 1. Before adopting Bitcoin, Strategy was a billion dollar company with an operating business that was generating roughly $50M in cash a year. 2. Until the introduction of the ETF's in January 2024, Strategy was the only way for the average investor to gain passive exposure to Bitcoin. 3. Until this year, Strategy was the only way for the average investor to gain leveraged exposure to Bitcoin. 4. Strategy was issuing multiple, billion dollar, zero coupon, unsecured convertible notes at +50% conversion premiums. 5. Strategy has Michael Saylor, who, you don’t need me to tell you, is in a league of his own. 6. For many reasons, including those I’ve just mentioned, Strategy has benefitted disproportionately from the broader sentiment around Bitcoin. In other words, for the best part of 4 years, Strategy had zero competition for either capital or attention. As a result, it became a magnet for capital from anyone who wanted exposure to Bitcoin and it attracted inflows that were beyond what fundamentals alone would maybe justify. Therefore, using Strategy as a blueprint for the performance that you can expect from other Bitcoin Treasury Companies is a bad idea. Using Strategy as a blueprint for how to operate a Bitcoin Treasury Company is a good idea. Now let’s break down what’s unfolded over the last 6 months or so. Between May and June of this year, when we witnessed a flood of new Bitcoin Treasury Companies, we entered what I refer to as the frenzy phase. The frenzy phase was driven almost entirely by sentiment. By sentiment I simply mean emotion. Since then, as sentiment has slowly faded, the market has increasingly priced Bitcoin Treasury Companies based more on fundamentals. By fundamentals I simply mean facts. So where as sentiment is driven by emotion and hype, fundamentals are driven by facts and reason. The problem is that when you price Bitcoin Treasury Companies on fundamentals, you realise that many of them are almost entirely dependent on sentiment in order to expand mNAV so they can raise capital via the common stock ATM to buy Bitcoin and generate Bitcoin Yield. However, for me, raising capital via the common stock ATM and recycling it into Bitcoin is not genuine value creation — it’s value transfer. That’s not to say you shouldn’t leverage the ATM as and when necessary — you should. However, if your business model as a Bitcoin Treasury Company no longer works when “sentiment is low” then you have neither a business model nor a business. You’re the equivalent of a meme stock except with Bitcoin on your balance sheet. On that basis, companies shouldn’t expect to trade at a premium if the common stock ATM is the only way they raise capital. I’m not saying they won’t trade at a premium — I’m saying that companies shouldn’t expect to. Now, between July and now, we’ve obviously seen mNAVs compress substantially and so the frenzy phase is over which means that the days of automatically being granted generous mNAV multiples is also over. So now we are in the maturity phase. The maturity phase is going to be defined by being able to offer a differentiated value proposition and having a sustainable business model that can generate Bitcoin Yield in any environment independent of sentiment. In other words, they can generate Bitcoin Yield when trading at or below 1 mNAV. So essentially now, Bitcoin Treasury Companies have to work for their mNAV multiples — as it should be. Following the maturity phase will be the consolidation phase where capital, Bitcoin and ultimately market share will converge towards a small number of Bitcoin Treasury Companies that will dominate the entire industry. I should clarify that I am referring predominantly to pure-play Bitcoin Treasury Companies — companies who are valued based solely on their Bitcoin strategy. Now, with everything that I’ve said, how should you evaluate Bitcoin Treasury Companies? Hopefully over the next few weeks I’m going to string together a video with my valuation framework. In the meantime, a basic test is that I use is this: How much Bitcoin Yield can the company generate over X period of time — you decide what that period of time is — if it traded at 1x mNAV over that entire period? If the answer is 0, then they are probably entirely dependent on raising capital via the common stock ATM which means they likely don’t deserve a premium. If the answer is >0, then they are probably innovating through the use of other instruments — like converts and preferred products — which means they likely do deserve a premium and so whatever number you come up with should be used as the base for your valuation. Now, don’t be fooled. The Bitcoin Treasury Company space is, not entirely, but to a large degree, a zero-sum game. Every Dollar raised by one Bitcoin Treasury Company is at the expense of every other Bitcoin Treasury Company. Every Bitcoin purchased by one Bitcoin Treasury Company is at the expense of every other Bitcoin Treasury Company. It’s only because we are early that everyone is incentivised to essentially hold hands and cheer each other on. However, make no mistake, everyone involved is tacitly well aware that they are all competing for the same finite amount of capital and the same fixed amount of Bitcoin. Thus, the reality is that, by definition, not every Bitcoin Treasury Company is going to succeed. So choose your horses and jockeys wisely. As a side note, with the amount of Bitcoin Treasury Companies now desperately chasing and competing for the same capital from institutions, who do you think has the leverage; the Bitcoin Treasury Companies or the institutions? I’ll let you decide. Before I close, I want to leave you guys with this. There is a small subset of people invested in Bitcoin Treasury Companies who are desperately clinging on to their bags because they believe “sentiment will return.” These people are completely missing the point. My friends, if your investing philosophy is based on sentiment, you are simply not going to last. You want to base your decisions, as far as possible, on fundamentals. As investors, you either adapt and update your mental models based on how things are and not how you want them to be — or you get left behind. With that in mind: Never get caught up in tribalism. Never get attached to your beliefs. Always think critically. Always think independently. Always seek Truth.

Chris Millas

34,483 次观看 • 9 个月前

Years in banking taught me that successful stock picking comes down to 6 specific criteria. Whether markets are rising, falling, or stagnant, these criteria consistently identify quality companies Here's what they are: Criteria #1: Gross Margin >60% Companies with 60%+ gross margins aren't getting undercut by competitors. The product is defensible and hard to replicate. Service businesses typically achieve these numbers more easily than manufacturing due to lower overhead costs. Criteria #2: Return on Invested Capital Above 10% How effectively does the company turn money into more money? I want minimum 10-12% returns. Many companies barely hit 4%—you'd earn more in a high-yield savings account. Criteria #3: Free Cash Flow >20% Think of Amazon sellers constantly reinvesting in inventory—they never touch the cash. You want businesses that actually generate free cash flow of 20% or higher. This means they won't need to borrow money or dilute shareholders. They're fundamentally stronger. Criteria #4: Interest Coverage Ratio 3x+ Can they easily pay interest on debt from profits? I want this at least 3x so that even if rates spike, the business survives. This is your big warning signal for financial risk. Criteria #5: Forget P/E Ratios P/E ratios are useless snapshots. Netflix in 2015 had a P/E of 554x—everyone said "you're an idiot." Earnings then went up 100x. What matters is whether profits grow and fundamentals stack up, not the snapshot ratio. Criteria #6: The Moat How difficult is it for competitors to replicate the business? Apple's moat isn't just the phone—it's the stores, brand ecosystem, and App Store working together. Compare that to frozen yogurt shops competing themselves into bankruptcy. Look for deep, defensible competitive advantages. The Simpler Path Too complicated? Buy quality ETFs like SPQ (S&P 500 Quality Index) or IWQ (MSCI World Quality). You'll own the top 100 companies like Microsoft, Nvidia, and Apple instead of all 500 mediocre S&P companies. Stop donating money to Wall Street. Start building wealth with quality companies and real strategy.
9:37

Years in banking taught me that successful stock picking comes down to 6 specific criteria. Whether markets are rising, falling, or stagnant, these criteria consistently identify quality companies Here's what they are: Criteria #1: Gross Margin >60% Companies with 60%+ gross margins aren't getting undercut by competitors. The product is defensible and hard to replicate. Service businesses typically achieve these numbers more easily than manufacturing due to lower overhead costs. Criteria #2: Return on Invested Capital Above 10% How effectively does the company turn money into more money? I want minimum 10-12% returns. Many companies barely hit 4%—you'd earn more in a high-yield savings account. Criteria #3: Free Cash Flow >20% Think of Amazon sellers constantly reinvesting in inventory—they never touch the cash. You want businesses that actually generate free cash flow of 20% or higher. This means they won't need to borrow money or dilute shareholders. They're fundamentally stronger. Criteria #4: Interest Coverage Ratio 3x+ Can they easily pay interest on debt from profits? I want this at least 3x so that even if rates spike, the business survives. This is your big warning signal for financial risk. Criteria #5: Forget P/E Ratios P/E ratios are useless snapshots. Netflix in 2015 had a P/E of 554x—everyone said "you're an idiot." Earnings then went up 100x. What matters is whether profits grow and fundamentals stack up, not the snapshot ratio. Criteria #6: The Moat How difficult is it for competitors to replicate the business? Apple's moat isn't just the phone—it's the stores, brand ecosystem, and App Store working together. Compare that to frozen yogurt shops competing themselves into bankruptcy. Look for deep, defensible competitive advantages. The Simpler Path Too complicated? Buy quality ETFs like SPQ (S&P 500 Quality Index) or IWQ (MSCI World Quality). You'll own the top 100 companies like Microsoft, Nvidia, and Apple instead of all 500 mediocre S&P companies. Stop donating money to Wall Street. Start building wealth with quality companies and real strategy.

Felix Prehn 🐶

40,089 次观看 • 6 个月前

GPT 5.6 Sol just saved me €650 a year and demonstrated just how good this model is as an agent in @ChatGPTapp Codex. This is not a clickbait, let me explain. In France, insurance companies tend to hide all their prices behind quote forms that take at least 5min to complete for a single configuration on a single provider's website. And that take an other 5min to understand. If you want to compare 10 companies across 5 configurations each, it takes at least 4h +. (It's such a painful process that entire businesses exist just to compare insurance offers.) Since I have two cars, it would normally take me 8h so an entire day to have a real large view of my best option. Companies know this and use the friction to maintain overpriced offers. So I asked @ChatGPTapp with GPT 5.6 Sol, using Chrome tabs, to go through all those annoying forms. I provided him all my contrats with my current insurance companies so he have context. For some insurers, you even have to speak with a representative just to get a quote (which is absurd in 2026), so it emailed the companies, exchanged the required information, and obtained the prices. It then ran a complete benchmark, read all the terms and conditions, and recommended three options from three different companies. I picked one, and it completed the subscription with my new insurance company. And that's how I ended up with better insurance coverage for less money. For 4% of my weekly quota in 20x plan. (i think it's fair) All of that happened while I was walking my dog for 50 minutes, he was working on my computer all by it's on. Yes, computer use existed before OpenAI GPT 5.6 Sol, but this is a completely different level in the way it handles these kinds of tasks. I think this story shows the new era of AI we're entering, good model is not only for one single task as coding or answering question, AI now can do things for you, like in your daily live. I love being able to hand my computer over to GPT 5.6 Sol. PS: The only annoying part was that some companies still require "Verify you're human" checks. In the age of AI agents, websites really need to be ready for robot access.
0:20

GPT 5.6 Sol just saved me €650 a year and demonstrated just how good this model is as an agent in @ChatGPTapp Codex. This is not a clickbait, let me explain. In France, insurance companies tend to hide all their prices behind quote forms that take at least 5min to complete for a single configuration on a single provider's website. And that take an other 5min to understand. If you want to compare 10 companies across 5 configurations each, it takes at least 4h +. (It's such a painful process that entire businesses exist just to compare insurance offers.) Since I have two cars, it would normally take me 8h so an entire day to have a real large view of my best option. Companies know this and use the friction to maintain overpriced offers. So I asked @ChatGPTapp with GPT 5.6 Sol, using Chrome tabs, to go through all those annoying forms. I provided him all my contrats with my current insurance companies so he have context. For some insurers, you even have to speak with a representative just to get a quote (which is absurd in 2026), so it emailed the companies, exchanged the required information, and obtained the prices. It then ran a complete benchmark, read all the terms and conditions, and recommended three options from three different companies. I picked one, and it completed the subscription with my new insurance company. And that's how I ended up with better insurance coverage for less money. For 4% of my weekly quota in 20x plan. (i think it's fair) All of that happened while I was walking my dog for 50 minutes, he was working on my computer all by it's on. Yes, computer use existed before OpenAI GPT 5.6 Sol, but this is a completely different level in the way it handles these kinds of tasks. I think this story shows the new era of AI we're entering, good model is not only for one single task as coding or answering question, AI now can do things for you, like in your daily live. I love being able to hand my computer over to GPT 5.6 Sol. PS: The only annoying part was that some companies still require "Verify you're human" checks. In the age of AI agents, websites really need to be ready for robot access.

Defend Intelligence (Anis Ayari)

78,466 次观看 • 1 个月前