Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

I generated a full earnings teardown with Perplexity Computer from a single prompt. Prompt: Break down Nvidia’s latest earnings. Put actuals next to consensus (revenue, EPS). Highlight segment performance and margin moves. Summarize the headline takeaways, what management emphasized, AI/data center demand signals, key risks, and the outlook. Close...

AmControo's profile picture

FATHELA ESQ

54,823 subscribers

71,444 görüntüleme • 3 ay önce •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

I asked Perplexity Computer one question: “If Nvidia’s AI data center revenue doubles again, map exactly where every incremental dollar flows across the semiconductor supply chain with a chart” It generated this full supply chain chart and video in minutes. It shows exactly who benefits - memory, foundry, packaging, and more. This level of research used to take hours. Now it takes minutes.
0:55

I asked Perplexity Computer one question: “If Nvidia’s AI data center revenue doubles again, map exactly where every incremental dollar flows across the semiconductor supply chain with a chart” It generated this full supply chain chart and video in minutes. It shows exactly who benefits - memory, foundry, packaging, and more. This level of research used to take hours. Now it takes minutes.

Venu

101,207 görüntüleme • 5 ay önce

THIS TOP-TRADER’S 3 CLAUDE PROMPTS TURN ANY STOCK INTO A PROFITABLE INVESTMENT IN 5 MINUTES. Here is how you can become profitable and analyze any stocks in 5 minutes using Claude. This is the exact 3-prompt framework I use to break down stocks fast: >Why is the stock moving? Claude explains the investment thesis, key catalysts, risks, and what Wall Street is saying. >Is the business healthy - and is the stock cheap? Claude checks fundamentals, valuation, and compares it against 5 competitors. >What happens next? Claude builds bull, base, and bear case scenarios - including potential price targets and when to exit. I use this to build my own investment theses before going deeper. Want the full Claude prompt pack? Comment “PROMPT” and I’ll DM it to you. Follow for more AI investing hacks.
0:53

THIS TOP-TRADER’S 3 CLAUDE PROMPTS TURN ANY STOCK INTO A PROFITABLE INVESTMENT IN 5 MINUTES. Here is how you can become profitable and analyze any stocks in 5 minutes using Claude. This is the exact 3-prompt framework I use to break down stocks fast: >Why is the stock moving? Claude explains the investment thesis, key catalysts, risks, and what Wall Street is saying. >Is the business healthy - and is the stock cheap? Claude checks fundamentals, valuation, and compares it against 5 competitors. >What happens next? Claude builds bull, base, and bear case scenarios - including potential price targets and when to exit. I use this to build my own investment theses before going deeper. Want the full Claude prompt pack? Comment “PROMPT” and I’ll DM it to you. Follow for more AI investing hacks.

kiosa

19,659 görüntüleme • 2 ay önce

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

32,132 görüntüleme • 3 ay önce

🚨JPMORGAN’S STEVE TUSA JUST DROPPED HIS 2026 OUTLOOK, IT’S BULLISH FOR DATA CENTERS🔥 Steve Tusa from JPMorgan has released his 2026 market predictions, with data centers sitting at the center of his outlook. Within the industrials space, he describes data centers as the primary driver, arguing that much of the group’s performance ultimately ties back to the AI and data center buildout. While he acknowledges some recent concern around the sustainability and length of the cycle, his on-the-ground read differs from the narrative that has taken hold in parts of the market. Demand tied to data centers has continued to accelerate through recent months, and he is clear that being materially underexposed to AI data centers is a mistake. In his view, pullbacks should be approached as opportunities rather than warnings. He directly addresses the overbuild debate, which remains a key source of skepticism. According to Tusa, there is no pause in real-world data center construction activity. Order activity has improved in recent weeks and is running stronger than it was around the end of the third quarter. Feedback from hyperscalers suggests supply is still struggling to catch up with demand, reinforcing his belief that the industry remains early in a multi-year buildout rather than late in the cycle. His comment about not seeing any “dark GPUs” sitting idle captures how tight the market still is. From a portfolio perspective, Tusa continues to favor staying with the AI data center buildout trade into 2026. Several data center-exposed industrial names have pulled back, but he views those moves as valuation resets driven by sentiment rather than a deterioration in underlying demand. That reset has created a more attractive entry point than what investors were facing just a few months ago. His preferred setup is a barbell approach. On one side are growth-oriented names with direct exposure to AI infrastructure demand. On the other are idiosyncratic margin expansion stories with some data center leverage, such as Johnson Controls, where he sees earnings growing in the mid-teens to around twenty percent over the next few years at reasonable valuations. Beyond that, he also points to select industrial names with cheaper economic leverage, but the primary focus remains on data center-driven growth and margin expansion. The broader takeaway is that despite skepticism and overbuild chatter, real-world demand, orders, and construction tied to data centers continue to strengthen. From JPMorgan’s perspective, this cycle still has meaningful runway left and is unlikely to be nearing its end anytime soon. $NBIS $IREN $NVDA $ORCL $AMD $GOOGL
5:29

🚨JPMORGAN’S STEVE TUSA JUST DROPPED HIS 2026 OUTLOOK, IT’S BULLISH FOR DATA CENTERS🔥 Steve Tusa from JPMorgan has released his 2026 market predictions, with data centers sitting at the center of his outlook. Within the industrials space, he describes data centers as the primary driver, arguing that much of the group’s performance ultimately ties back to the AI and data center buildout. While he acknowledges some recent concern around the sustainability and length of the cycle, his on-the-ground read differs from the narrative that has taken hold in parts of the market. Demand tied to data centers has continued to accelerate through recent months, and he is clear that being materially underexposed to AI data centers is a mistake. In his view, pullbacks should be approached as opportunities rather than warnings. He directly addresses the overbuild debate, which remains a key source of skepticism. According to Tusa, there is no pause in real-world data center construction activity. Order activity has improved in recent weeks and is running stronger than it was around the end of the third quarter. Feedback from hyperscalers suggests supply is still struggling to catch up with demand, reinforcing his belief that the industry remains early in a multi-year buildout rather than late in the cycle. His comment about not seeing any “dark GPUs” sitting idle captures how tight the market still is. From a portfolio perspective, Tusa continues to favor staying with the AI data center buildout trade into 2026. Several data center-exposed industrial names have pulled back, but he views those moves as valuation resets driven by sentiment rather than a deterioration in underlying demand. That reset has created a more attractive entry point than what investors were facing just a few months ago. His preferred setup is a barbell approach. On one side are growth-oriented names with direct exposure to AI infrastructure demand. On the other are idiosyncratic margin expansion stories with some data center leverage, such as Johnson Controls, where he sees earnings growing in the mid-teens to around twenty percent over the next few years at reasonable valuations. Beyond that, he also points to select industrial names with cheaper economic leverage, but the primary focus remains on data center-driven growth and margin expansion. The broader takeaway is that despite skepticism and overbuild chatter, real-world demand, orders, and construction tied to data centers continue to strengthen. From JPMorgan’s perspective, this cycle still has meaningful runway left and is unlikely to be nearing its end anytime soon. $NBIS $IREN $NVDA $ORCL $AMD $GOOGL

Jordan

56,476 görüntüleme • 7 ay önce

On the left is the top performing ad in the ad account. On the right is the viral organic post it was based on. Recreating organic content in your niche is one of the most effective ways to find winning ads. Here’s how we do it: 1. Search TikTok and Shorts for content around the problem/desired transformation (e.g. ”how to grow glutes”) 2. Save down top performing content to Foreplay 3. Take the transcription from Foreplay and input it to ChatGPT with the prompt below 4. Tweak the script and send it over to the creator Prompt (full script): "Now knowing what you know about my brand, rewrite this script for BRAND but instead, position the PRODUCT as the solution." Prompt (talking points): "Now knowing what you know about my brand, take this same structure and give me talking points to recreate it - but instead for a version where PRODUCT is positioned as the solution."
1:18

On the left is the top performing ad in the ad account. On the right is the viral organic post it was based on. Recreating organic content in your niche is one of the most effective ways to find winning ads. Here’s how we do it: 1. Search TikTok and Shorts for content around the problem/desired transformation (e.g. ”how to grow glutes”) 2. Save down top performing content to Foreplay 3. Take the transcription from Foreplay and input it to ChatGPT with the prompt below 4. Tweak the script and send it over to the creator Prompt (full script): "Now knowing what you know about my brand, rewrite this script for BRAND but instead, position the PRODUCT as the solution." Prompt (talking points): "Now knowing what you know about my brand, take this same structure and give me talking points to recreate it - but instead for a version where PRODUCT is positioned as the solution."

Alex Cooper

26,937 görüntüleme • 1 yıl önce

Running operations used to take me 10+ hours/week. Now it takes 30 minutes. Here’s what changed: → I stopped using AI as a chatbot → I started using Perplexity Computer as a system In one workflow, it: • Reads my Slack updates • Checks my calendar • Pulls data from sheets • Generates a full weekly report • Summarizes key decisions • Flags risks automatically No switching tools. No manual work. This is the shift most people are missing: AI isn’t for asking questions anymore. It’s for executing workflows. If you’re still “chatting” with AI… you’re already behind. see what you’ve been missing—start now, explore key features in minutes, and feel the difference . Try it now:
0:21

Running operations used to take me 10+ hours/week. Now it takes 30 minutes. Here’s what changed: → I stopped using AI as a chatbot → I started using Perplexity Computer as a system In one workflow, it: • Reads my Slack updates • Checks my calendar • Pulls data from sheets • Generates a full weekly report • Summarizes key decisions • Flags risks automatically No switching tools. No manual work. This is the shift most people are missing: AI isn’t for asking questions anymore. It’s for executing workflows. If you’re still “chatting” with AI… you’re already behind. see what you’ve been missing—start now, explore key features in minutes, and feel the difference . Try it now:

Aryan Rakib

39,084 görüntüleme • 3 ay önce

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 earnings report in the transcripts of the S&P 500 companies every quarter. Note common themes that executives are talking about. Keywords and trends that could help me potentially make money and identify larger trends. As a momentum trader. S&P 500 Earnings Intelligence Dashboard is live and fully updated with 484 company transcripts covering the latest earnings season. What's inside: 5 KPIs at a glance — total companies, themes tracked, momentum signals, average sentiment, and sector coverage Theme frequency chart : aggregated by GICS sector, so you can see which sectors are driving each narrative (AI CapEx, margin expansion, regulatory risk, etc.) Sector sentiment ranked as horizontal bars — Utilities leading at 0.79, Consumer Staples trailing at 0.66 12 momentum signals — 8 bullish, 3 caution, 1 energy transition — with the tickers behind each signal Searchable executive quotes with sector filters and pagination across all 484 companies Full sector breakdown showing every company's sentiment, themes, and key quotes Recurring refresh: A quarterly refresh is scheduled for May 15, Aug 15, Nov 15, and Feb 15 at 9am EST (cron a07f9c7c). Each run will pull fresh transcripts for all S&P 500 constituents, reprocess through NLP, and redeploy the dashboard automatically. Jeff Grimes kwak jiwon Aravind Srinivas Computer IS INSANE. Can't wait to see what else I can build for myself.
1:50

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 earnings report in the transcripts of the S&P 500 companies every quarter. Note common themes that executives are talking about. Keywords and trends that could help me potentially make money and identify larger trends. As a momentum trader. S&P 500 Earnings Intelligence Dashboard is live and fully updated with 484 company transcripts covering the latest earnings season. What's inside: 5 KPIs at a glance — total companies, themes tracked, momentum signals, average sentiment, and sector coverage Theme frequency chart : aggregated by GICS sector, so you can see which sectors are driving each narrative (AI CapEx, margin expansion, regulatory risk, etc.) Sector sentiment ranked as horizontal bars — Utilities leading at 0.79, Consumer Staples trailing at 0.66 12 momentum signals — 8 bullish, 3 caution, 1 energy transition — with the tickers behind each signal Searchable executive quotes with sector filters and pagination across all 484 companies Full sector breakdown showing every company's sentiment, themes, and key quotes Recurring refresh: A quarterly refresh is scheduled for May 15, Aug 15, Nov 15, and Feb 15 at 9am EST (cron a07f9c7c). Each run will pull fresh transcripts for all S&P 500 constituents, reprocess through NLP, and redeploy the dashboard automatically. Jeff Grimes kwak jiwon Aravind Srinivas Computer IS INSANE. Can't wait to see what else I can build for myself.

Ted Zhang

253,871 görüntüleme • 5 ay önce

Micron is going to $4,000 and here is why (Save this). For 25 years, DRAM prices did one thing, they went down. Memory makers overbuilt, supply overwhelmed demand, buyers had all the negotiating leverage and that commodity trap crushed memory stocks every single cycle. What you are watching right now is a complete structural break from that 25 year trend. DRAM contract prices are up 700% year over year and the reason is AI and it is not going away. HBM3 was 12 layers, HBM4 in production and shipping now to Nvidia's latest GPUs is 16 layers. Each generation consumes significantly more wafer to produce than the last, meaning supply structurally tightens as the technology advances. Memory was 8% of hyperscaler capex in 2023 but is 35% in 2026 and is projected to hit 48% in 2027. Nearly half of everything Microsoft, Amazon, Google, and Meta spend on infrastructure will go to memory by next year. Going from the GB300 to the Vera Rubin 200 generation, GPU cost went up 57% while memory cost went up 435%. There are three companies on earth that can make DRAM at scale, Samsung, SK Hynix, and Micron. Both Samsung and SK Hynix are converting capacity to HBM which means conventional DRAM supply tightens further for everything else, and Micron captures pricing on both sides. Micron guided to $33.5 billion for Q3 and they reported $41.46 billion, a $7.96 billion beat, the largest earnings beat in the company's history. Gross margins came in at 85% above the 81% they guided. For Q4, they are now guiding to $50 billion in revenue with ~86% gross margins and $31 EPS. At $112 EPS in FY2027, the pre-earnings consensus and a 35x multiple, that is a $3,920 stock but with Q4 guiding to $31 EPS alone in a single quarter, FY2027 estimates will be revised meaningfully higher. Deutsche Bank says the supply-demand gap worsens through all of 2027 and into 2028. The market still thinks this is a cyclical bounce but this is far from it. This is the first chapters of a multi year repricing of the most critical component in the AI economy and Micron is at the center of it. Follow me Melvin for more AI, semis, and the next big market themes.
4:08

Micron is going to $4,000 and here is why (Save this). For 25 years, DRAM prices did one thing, they went down. Memory makers overbuilt, supply overwhelmed demand, buyers had all the negotiating leverage and that commodity trap crushed memory stocks every single cycle. What you are watching right now is a complete structural break from that 25 year trend. DRAM contract prices are up 700% year over year and the reason is AI and it is not going away. HBM3 was 12 layers, HBM4 in production and shipping now to Nvidia's latest GPUs is 16 layers. Each generation consumes significantly more wafer to produce than the last, meaning supply structurally tightens as the technology advances. Memory was 8% of hyperscaler capex in 2023 but is 35% in 2026 and is projected to hit 48% in 2027. Nearly half of everything Microsoft, Amazon, Google, and Meta spend on infrastructure will go to memory by next year. Going from the GB300 to the Vera Rubin 200 generation, GPU cost went up 57% while memory cost went up 435%. There are three companies on earth that can make DRAM at scale, Samsung, SK Hynix, and Micron. Both Samsung and SK Hynix are converting capacity to HBM which means conventional DRAM supply tightens further for everything else, and Micron captures pricing on both sides. Micron guided to $33.5 billion for Q3 and they reported $41.46 billion, a $7.96 billion beat, the largest earnings beat in the company's history. Gross margins came in at 85% above the 81% they guided. For Q4, they are now guiding to $50 billion in revenue with ~86% gross margins and $31 EPS. At $112 EPS in FY2027, the pre-earnings consensus and a 35x multiple, that is a $3,920 stock but with Q4 guiding to $31 EPS alone in a single quarter, FY2027 estimates will be revised meaningfully higher. Deutsche Bank says the supply-demand gap worsens through all of 2027 and into 2028. The market still thinks this is a cyclical bounce but this is far from it. This is the first chapters of a multi year repricing of the most critical component in the AI economy and Micron is at the center of it. Follow me Melvin for more AI, semis, and the next big market themes.

Melvin

93,627 görüntüleme • 1 ay önce

🚨 2026 DUMP: COLLAPSE JUST STARTED What I warned you about is here. → Silver dumped 12.61% → Gold dumped 4.71% → Stock market bleeding daily → Bitcoin down 50% from ATH Same pattern as 10 and 20 years ago. → 2008: correlations went to one, "safe" and "risk" fell together, nowhere to hide → 2020: every screen turned red in a week, until the Fed flooded the system with money → Now: the same setup is repeating, quietly, across borders You don't hold "stocks," "crypto," and "gold." You hold one trade under different names. One push and the whole thing moves. Under the hood the pressure is already showing: → Bond yields are flashing stress → Liquidity is tightening → Fed is cornered: ease and inflate the bubble, or tighten and break the market Both paths lead to the same point. Something breaks. A crash never arrives with one scary headline. It arrives when correlation goes to one. When the market stops being a market. That started this week. Most will call it "a normal correction" right up to the end. Reminder: I called BTC at $16K and the top at $126K. When I exit, you'll see it here first. Turn notifications on.
0:27

🚨 2026 DUMP: COLLAPSE JUST STARTED What I warned you about is here. → Silver dumped 12.61% → Gold dumped 4.71% → Stock market bleeding daily → Bitcoin down 50% from ATH Same pattern as 10 and 20 years ago. → 2008: correlations went to one, "safe" and "risk" fell together, nowhere to hide → 2020: every screen turned red in a week, until the Fed flooded the system with money → Now: the same setup is repeating, quietly, across borders You don't hold "stocks," "crypto," and "gold." You hold one trade under different names. One push and the whole thing moves. Under the hood the pressure is already showing: → Bond yields are flashing stress → Liquidity is tightening → Fed is cornered: ease and inflate the bubble, or tighten and break the market Both paths lead to the same point. Something breaks. A crash never arrives with one scary headline. It arrives when correlation goes to one. When the market stops being a market. That started this week. Most will call it "a normal correction" right up to the end. Reminder: I called BTC at $16K and the top at $126K. When I exit, you'll see it here first. Turn notifications on.

winkle.

78,636 görüntüleme • 1 ay önce

I built a fully functional app in minutes — without writing a single line of code. With Replit, I just described what I wanted in plain English, and the app came to life almost instantly. My AI tool now takes care of: ✅ Data handling ✅ AI-powered logic ✅ Clean, usable UI Start building here: And it’s not limited to content tools. With a single prompt, you can spin up things like a unit converter with inputs, selectors, instant results, copy actions, and history — fully working in minutes. Why I’m a fan of Replit: 🚀 Build by describing, then iterate fast. 🚀 300+ AI models in one place. 🚀 Build, collaborate, and ship from one platform. 🚀 Integrates with Drive, Dropbox, Notion, Slack 🚀 Works seamlessly on desktop and mobile No setup. No code. Just ideas → real apps.
0:50

I built a fully functional app in minutes — without writing a single line of code. With Replit, I just described what I wanted in plain English, and the app came to life almost instantly. My AI tool now takes care of: ✅ Data handling ✅ AI-powered logic ✅ Clean, usable UI Start building here: And it’s not limited to content tools. With a single prompt, you can spin up things like a unit converter with inputs, selectors, instant results, copy actions, and history — fully working in minutes. Why I’m a fan of Replit: 🚀 Build by describing, then iterate fast. 🚀 300+ AI models in one place. 🚀 Build, collaborate, and ship from one platform. 🚀 Integrates with Drive, Dropbox, Notion, Slack 🚀 Works seamlessly on desktop and mobile No setup. No code. Just ideas → real apps.

Ajay Sharma

62,646 görüntüleme • 7 ay önce

Everyone wants agent swarms. Very few people are talking seriously enough about the context layer that makes swarms useful. Even with one agent, context is fragile. Too little context and the agent guesses. Too much context and it wastes tokens, loses focus, or reasons over irrelevant noise. The sweet spot is precise context: the right knowledge, in the right structure, at the right moment. With many agents, that challenge explodes. Each agent produces decisions, assumptions, findings, summaries, risks, and partial conclusions. Unless that knowledge becomes shared, structured, and reusable, every new agent is forced to rediscover what another agent already learned. That is not a swarm. That is a crowd. Shared context graphs are what turn agent activity into agent collaboration, and OriginTrail DKG V10 brings them to life. Was just playing with some final polishing for the V10 release, and it is really powerful to see shared context graphs where multiple agents contribute knowledge into the same connected memory, with attribution visible directly in the graph ui. That matters for three reasons. First, agents can access and build on one shared memory instead of staying trapped in isolated sessions. Second, the graph structure helps them retrieve the exact context they need, instead of stuffing everything into a prompt and hoping the model sorts it out. Third, verifiability of provenance. You can see which agent contributed each piece of knowledge, trace the source, and decide what to trust. Tokenmaxxing starts with fewer tokens, but the deeper story is coordination - agents stop reloading the world and start building on shared, verifiable context. That is the foundation for serious multi-agent work across software engineering, research, finance, operations, project management, and far beyond. The future is not more agents, it is agents working from shared, verifiable context. But the more the merrier, of course.
0:22

Everyone wants agent swarms. Very few people are talking seriously enough about the context layer that makes swarms useful. Even with one agent, context is fragile. Too little context and the agent guesses. Too much context and it wastes tokens, loses focus, or reasons over irrelevant noise. The sweet spot is precise context: the right knowledge, in the right structure, at the right moment. With many agents, that challenge explodes. Each agent produces decisions, assumptions, findings, summaries, risks, and partial conclusions. Unless that knowledge becomes shared, structured, and reusable, every new agent is forced to rediscover what another agent already learned. That is not a swarm. That is a crowd. Shared context graphs are what turn agent activity into agent collaboration, and OriginTrail DKG V10 brings them to life. Was just playing with some final polishing for the V10 release, and it is really powerful to see shared context graphs where multiple agents contribute knowledge into the same connected memory, with attribution visible directly in the graph ui. That matters for three reasons. First, agents can access and build on one shared memory instead of staying trapped in isolated sessions. Second, the graph structure helps them retrieve the exact context they need, instead of stuffing everything into a prompt and hoping the model sorts it out. Third, verifiability of provenance. You can see which agent contributed each piece of knowledge, trace the source, and decide what to trust. Tokenmaxxing starts with fewer tokens, but the deeper story is coordination - agents stop reloading the world and start building on shared, verifiable context. That is the foundation for serious multi-agent work across software engineering, research, finance, operations, project management, and far beyond. The future is not more agents, it is agents working from shared, verifiable context. But the more the merrier, of course.

Jurij Skornik

11,070 görüntüleme • 2 ay önce

AI is fueling a generational bull market and it only makes the case for bitcoin stronger. I sat down with Anthony Pompliano 🌪 to discuss the current macro set up, inflation risks, why scarcity assets will win the AI boom, and why the "bubble" crowd is so wrong right now. This conversation is packed with unique insights that will surprise you. TIMESTAMPS: 0:00 - Affordability decides midterms 3:00 - Iran and inflation 4:33 - Short conflict vs. structural inflation 7:08 - $BTC as the "certainty" asset 9:31 - AI demand wall 11:13 - Scarcity in an AI world 13:36 - Pomp vs. AI bears 17:01 - Doomer predictions 18:46 - Micron $MU and market froth
20:57

AI is fueling a generational bull market and it only makes the case for bitcoin stronger. I sat down with Anthony Pompliano 🌪 to discuss the current macro set up, inflation risks, why scarcity assets will win the AI boom, and why the "bubble" crowd is so wrong right now. This conversation is packed with unique insights that will surprise you. TIMESTAMPS: 0:00 - Affordability decides midterms 3:00 - Iran and inflation 4:33 - Short conflict vs. structural inflation 7:08 - $BTC as the "certainty" asset 9:31 - AI demand wall 11:13 - Scarcity in an AI world 13:36 - Pomp vs. AI bears 17:01 - Doomer predictions 18:46 - Micron $MU and market froth

Phil Rosen

17,122 görüntüleme • 2 ay önce

Hermes + Claude + Higgsfield MCP + ViralBuilder = 💰💰💰 Four tools. One prompt chain. Hook to finished video in 10 minutes. I built a Claude skill that writes shot-by-shot Higgsfield prompts from a single creative brief. ViralBuilder tells you what's winning. The skill turns it into a production-ready prompt. Higgsfield renders it. No creative director. No guessing. No separate tools. Here is the setup: Higgsfield MCP → Open Claude Code → Settings → Connectors → Enter: → Connect your account Hermes → The agent layer running underneath Claude Code → It holds your skills, crons, memory, and routing rules → When you prompt Claude, Hermes feeds it the context it needs ViralBuilder (like Gethookd) → The winning ecom video database → Scrapes top performing ecom videos across platforms → Claude reads the data and extracts what styles, hooks, and formats are actually scaling The skill: video-prompt-builder → Installed inside Claude via Hermes → Takes a creative brief and outputs a full shot-by-shot prompt → Covers camera work, effects, transitions, pacing, and energy arc → Every output is structured for Higgsfield to render without ambiguity No switching apps. No export steps. Everything runs from one place. ▸ FIND WINNING CREATIVE ANGLES ViralBuilder tells you what the market already validated. Claude reads it and extracts the pattern. Prompts to run: "Search ViralBuilder for the top performing ecom videos in [niche] over the last 21 days. Extract the 3 dominant hook styles and rank by view velocity." "Pull the winning video formats in [niche] from ViralBuilder. Which opening 3 seconds appears most across videos spending over $10k?" "Find what video style is scaling right now in [niche] for the US market. UGC, talking head, or product demo. Filter for videos with over 1M views." "Pull the last 30 days of viral ecom hooks in [niche] from ViralBuilder. Cluster by emotional trigger. Which cluster has the most longevity?" You are not guessing at angles. You are reading what the market already spent money validating. ▸ BUILD THE PROMPT WITH THE SKILL This is where the video-prompt-builder skill takes over. You give Claude the winning angle. The skill outputs a complete shot-by-shot prompt with effects, transitions, pacing, and energy arc ready to fire into Higgsfield. Prompts to run: "Use the video-prompt-builder skill. Brief: 15-second UGC ad for [product] in [niche]. Hook style: [style from ViralBuilder]. Tone: direct to camera, US English. Output the full shot-by-shot effects timeline, effects inventory, density map, and energy arc." "Use the video-prompt-builder skill. The dominant hook in [niche] this week is [hook]. Build a 10-second product video prompt that opens with a speed ramp into a close-up product reveal. Include a signature visual effect and a low-density CTA landing." "Use the video-prompt-builder skill. Brief: replicate the pacing and energy of a [style description] video for [product]. Target duration: 20 seconds. Output all four sections. Then generate the video with Higgsfield using the shot-by-shot prompt." The skill outputs four sections every time: → Shot-by-shot effects timeline with camera, movement, and transitions per shot → Master effects inventory showing every technique used and where → Effects density map showing high, medium, and low intensity across the timeline → Energy arc describing how the video opens, builds, and lands That output goes directly into Higgsfield. No rewriting. No translating. ▸ GENERATE THE CREATIVE Claude writes the brief via the skill. Higgsfield MCP builds the video. Both happen in the same session. Prompts to run: "Use the video-prompt-builder skill to write a 15-second UGC prompt for [product]. Hook in the first 3 seconds, speed ramp into product reveal, slow-motion CTA landing. Then generate with Higgsfield in 9:16 format." "Build 3 prompt variations on this winning angle: [angle]. Each variation opens with a different effect — speed ramp, digital zoom, whip pan. Use the video-prompt-builder skill for each. Then generate all three with Higgsfield." "Use the video-prompt-builder skill. Brief: problem-solution ad for [product], 20 seconds, US market. Problem shot at high density, product reveal at medium, result and CTA at low. Generate with Higgsfield in 9:16." No separate tool. No file transfer. The video comes back in the same thread. ▸ CHAIN THE WHOLE STACK One prompt. All four tools firing together. "You are my ad creative director. Hermes has loaded my brand context. Pull the top performing video style in [niche] from ViralBuilder this week. Use the video-prompt-builder skill to write a full shot-by-shot prompt for [product] that replicates that style — 20 seconds, 9:16, US market, hook in the first 3 seconds. Output the effects timeline, inventory, density map, and energy arc. Then generate the video with Higgsfield." That single prompt replaces a half-day of production. The math before this stack: Brief: 30 minutes Script: 1 hour Creative production: 2 to 3 hours Agency or freelancer cost: $500 to $2,000 per creative With this stack: Hook to finished creative: 10 minutes Cost per creative: tool subscription, a fraction of agency rate 5 product tests in the time it used to take to brief one Bad product tests are where US ad budget disappears. $600 to $1,500 per failed test, before you even know if the angle works. This stack shows you what the market already validated before you spend a dollar on production. Hermes = your context layer. Brand, goals, past performance. Claude is always informed. ViralBuilder = your winning video database. See exactly what styles, hooks, and formats are scaling before you produce anything. video-prompt-builder skill = the translation layer. Turns a creative brief into a structured, production-ready Higgsfield prompt every time. Claude = the brain. Reads the market, writes the brief, chains the tools. Higgsfield MCP = the output. Video generated directly from the prompt. No export step. Four tools. One session. 10 minutes. Comment + RT "STACK" and I'll DM you the full workflow + the video-prompt-builder skill file.
0:26

Hermes + Claude + Higgsfield MCP + ViralBuilder = 💰💰💰 Four tools. One prompt chain. Hook to finished video in 10 minutes. I built a Claude skill that writes shot-by-shot Higgsfield prompts from a single creative brief. ViralBuilder tells you what's winning. The skill turns it into a production-ready prompt. Higgsfield renders it. No creative director. No guessing. No separate tools. Here is the setup: Higgsfield MCP → Open Claude Code → Settings → Connectors → Enter: → Connect your account Hermes → The agent layer running underneath Claude Code → It holds your skills, crons, memory, and routing rules → When you prompt Claude, Hermes feeds it the context it needs ViralBuilder (like Gethookd) → The winning ecom video database → Scrapes top performing ecom videos across platforms → Claude reads the data and extracts what styles, hooks, and formats are actually scaling The skill: video-prompt-builder → Installed inside Claude via Hermes → Takes a creative brief and outputs a full shot-by-shot prompt → Covers camera work, effects, transitions, pacing, and energy arc → Every output is structured for Higgsfield to render without ambiguity No switching apps. No export steps. Everything runs from one place. ▸ FIND WINNING CREATIVE ANGLES ViralBuilder tells you what the market already validated. Claude reads it and extracts the pattern. Prompts to run: "Search ViralBuilder for the top performing ecom videos in [niche] over the last 21 days. Extract the 3 dominant hook styles and rank by view velocity." "Pull the winning video formats in [niche] from ViralBuilder. Which opening 3 seconds appears most across videos spending over $10k?" "Find what video style is scaling right now in [niche] for the US market. UGC, talking head, or product demo. Filter for videos with over 1M views." "Pull the last 30 days of viral ecom hooks in [niche] from ViralBuilder. Cluster by emotional trigger. Which cluster has the most longevity?" You are not guessing at angles. You are reading what the market already spent money validating. ▸ BUILD THE PROMPT WITH THE SKILL This is where the video-prompt-builder skill takes over. You give Claude the winning angle. The skill outputs a complete shot-by-shot prompt with effects, transitions, pacing, and energy arc ready to fire into Higgsfield. Prompts to run: "Use the video-prompt-builder skill. Brief: 15-second UGC ad for [product] in [niche]. Hook style: [style from ViralBuilder]. Tone: direct to camera, US English. Output the full shot-by-shot effects timeline, effects inventory, density map, and energy arc." "Use the video-prompt-builder skill. The dominant hook in [niche] this week is [hook]. Build a 10-second product video prompt that opens with a speed ramp into a close-up product reveal. Include a signature visual effect and a low-density CTA landing." "Use the video-prompt-builder skill. Brief: replicate the pacing and energy of a [style description] video for [product]. Target duration: 20 seconds. Output all four sections. Then generate the video with Higgsfield using the shot-by-shot prompt." The skill outputs four sections every time: → Shot-by-shot effects timeline with camera, movement, and transitions per shot → Master effects inventory showing every technique used and where → Effects density map showing high, medium, and low intensity across the timeline → Energy arc describing how the video opens, builds, and lands That output goes directly into Higgsfield. No rewriting. No translating. ▸ GENERATE THE CREATIVE Claude writes the brief via the skill. Higgsfield MCP builds the video. Both happen in the same session. Prompts to run: "Use the video-prompt-builder skill to write a 15-second UGC prompt for [product]. Hook in the first 3 seconds, speed ramp into product reveal, slow-motion CTA landing. Then generate with Higgsfield in 9:16 format." "Build 3 prompt variations on this winning angle: [angle]. Each variation opens with a different effect — speed ramp, digital zoom, whip pan. Use the video-prompt-builder skill for each. Then generate all three with Higgsfield." "Use the video-prompt-builder skill. Brief: problem-solution ad for [product], 20 seconds, US market. Problem shot at high density, product reveal at medium, result and CTA at low. Generate with Higgsfield in 9:16." No separate tool. No file transfer. The video comes back in the same thread. ▸ CHAIN THE WHOLE STACK One prompt. All four tools firing together. "You are my ad creative director. Hermes has loaded my brand context. Pull the top performing video style in [niche] from ViralBuilder this week. Use the video-prompt-builder skill to write a full shot-by-shot prompt for [product] that replicates that style — 20 seconds, 9:16, US market, hook in the first 3 seconds. Output the effects timeline, inventory, density map, and energy arc. Then generate the video with Higgsfield." That single prompt replaces a half-day of production. The math before this stack: Brief: 30 minutes Script: 1 hour Creative production: 2 to 3 hours Agency or freelancer cost: $500 to $2,000 per creative With this stack: Hook to finished creative: 10 minutes Cost per creative: tool subscription, a fraction of agency rate 5 product tests in the time it used to take to brief one Bad product tests are where US ad budget disappears. $600 to $1,500 per failed test, before you even know if the angle works. This stack shows you what the market already validated before you spend a dollar on production. Hermes = your context layer. Brand, goals, past performance. Claude is always informed. ViralBuilder = your winning video database. See exactly what styles, hooks, and formats are scaling before you produce anything. video-prompt-builder skill = the translation layer. Turns a creative brief into a structured, production-ready Higgsfield prompt every time. Claude = the brain. Reads the market, writes the brief, chains the tools. Higgsfield MCP = the output. Video generated directly from the prompt. No export step. Four tools. One session. 10 minutes. Comment + RT "STACK" and I'll DM you the full workflow + the video-prompt-builder skill file.

Kid Pak

57,457 görüntüleme • 3 ay önce

If you remember one thing from me right now, let it be this: Short tech, long energy. Back in May, while the crowd was hyping up SpaceX, I wrote the bear case and said to short it. This week it fell below its IPO price, down about a third from its peak, and the buyers are now underwater. Tech is priced for a fantasy, and while the prices have finally started to come down, the positioning hasn't, which means almost everyone is still long and wrong. Energy, meanwhile, is setting up for a run that most people are ignoring. I lay out the full case in this update, and I also tell you about the 15 investors joining me on July 22 to name names and hand you their single best ideas. I genuinely believe these 9 minutes are the most important I recorded this year.
9:28

If you remember one thing from me right now, let it be this: Short tech, long energy. Back in May, while the crowd was hyping up SpaceX, I wrote the bear case and said to short it. This week it fell below its IPO price, down about a third from its peak, and the buyers are now underwater. Tech is priced for a fantasy, and while the prices have finally started to come down, the positioning hasn't, which means almost everyone is still long and wrong. Energy, meanwhile, is setting up for a run that most people are ignoring. I lay out the full case in this update, and I also tell you about the 15 investors joining me on July 22 to name names and hand you their single best ideas. I genuinely believe these 9 minutes are the most important I recorded this year.

George Noble

120,084 görüntüleme • 18 gün önce

ELON MUSK JUST EXPLAINED WHY HE IGNORES QUARTERLY EARNINGS, AND IT LINES UP WITH TOM LEE MORE THAN IT LOOKS He manages SpaceX on a 5-to-10-year horizon, the Mars spending was disclosed in the S1, and short-term earnings pressure mostly comes from managers whose own pay depends on quick results. Tom Lee's market thesis runs on earnings too, just measured in years, not quarters. He argues profits rising faster than prices is why the S&P is cheaper now than in January, with AI margin expansion still ahead. One ignores the quarter, the other tracks the multi-year trend. Both are pointing in the same direction: the long arc is what counts. I wonder if Tom Lee Thomas (Tom) Lee (not drummer) FundstratDirect.com sees Musk's approach as the same long-term lens he applies to the market.
1:30

ELON MUSK JUST EXPLAINED WHY HE IGNORES QUARTERLY EARNINGS, AND IT LINES UP WITH TOM LEE MORE THAN IT LOOKS He manages SpaceX on a 5-to-10-year horizon, the Mars spending was disclosed in the S1, and short-term earnings pressure mostly comes from managers whose own pay depends on quick results. Tom Lee's market thesis runs on earnings too, just measured in years, not quarters. He argues profits rising faster than prices is why the S&P is cheaper now than in January, with AI margin expansion still ahead. One ignores the quarter, the other tracks the multi-year trend. Both are pointing in the same direction: the long arc is what counts. I wonder if Tom Lee Thomas (Tom) Lee (not drummer) FundstratDirect.com sees Musk's approach as the same long-term lens he applies to the market.

Tom Lee Tracker (Not actually Tom)

109,304 görüntüleme • 5 gün önce

THIS GUY BUILT HIS ENTIRE COMMAND CENTER INSIDE OBSIDIAN USING A SINGLE CLAUDE INSTANCE AND NOW HE NEVER LEAVES IT He calls it handro operator Here’s what’s actually running inside: > Live Claude usage tracking (tokens, models and real-time costs) > A ClickUp task queue with Claude generated action suggestions that can be executed immediately > Full calendar sync > A custom intelligence feed for signals and news (AI video, Reddit, frontier research, searchable by keywords and time) > An Intelligence tab with Gmail highlights, Slack activity and Fireflies meeting transcripts > The ability to reply to emails and Slack messages directly from Obsidian without ever leaving the vault He built the whole thing in a single day: Mood board → defined the specs → dropped everything into Claude with one prompt → got a complete dashboard UI kit → fed it back into Claude → Claude mapped and connected everything automatically The article below goes deeper into how to reduce token usage when combining Claude with Obsidian Save both the post and the article - you might end up combining the ideas into a single product later
1:15

THIS GUY BUILT HIS ENTIRE COMMAND CENTER INSIDE OBSIDIAN USING A SINGLE CLAUDE INSTANCE AND NOW HE NEVER LEAVES IT He calls it handro operator Here’s what’s actually running inside: > Live Claude usage tracking (tokens, models and real-time costs) > A ClickUp task queue with Claude generated action suggestions that can be executed immediately > Full calendar sync > A custom intelligence feed for signals and news (AI video, Reddit, frontier research, searchable by keywords and time) > An Intelligence tab with Gmail highlights, Slack activity and Fireflies meeting transcripts > The ability to reply to emails and Slack messages directly from Obsidian without ever leaving the vault He built the whole thing in a single day: Mood board → defined the specs → dropped everything into Claude with one prompt → got a complete dashboard UI kit → fed it back into Claude → Claude mapped and connected everything automatically The article below goes deeper into how to reduce token usage when combining Claude with Obsidian Save both the post and the article - you might end up combining the ideas into a single product later

Bonsai 🌳

21,343 görüntüleme • 2 ay önce

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

1,814,717 görüntüleme • 6 ay önce

Billions of $$ raised to generate images, and none of them let you actually edit what you get. You type a prompt, get something close, try to fix one thing, and the whole image regenerates. Now 50% of what was working is gone. So you prompt again. And again. Stuck in prompt doom loops, burning tokens every single time. The output is always a flat PNG, limiting what you can do with it. Lica World actually reads your image and breaks it into structured, editable layers. You go in, change what you need to change, and everything else stays exactly where it was. Route each layer to the right model or a capable human. You don't need to regenerate from scratch or pay the token tax to fix a font color. Enterprises publishing creatives across site, social, and email are already using Lica to own their model and own their output. We're grateful to be supported by Accel, Amjad Masad, Srinivas Narayanan, , Village Global, and Michele Catasta to build the editing layer that AI image gen has been missing. Want early access? Check the next thread below.
1:41

Billions of $$ raised to generate images, and none of them let you actually edit what you get. You type a prompt, get something close, try to fix one thing, and the whole image regenerates. Now 50% of what was working is gone. So you prompt again. And again. Stuck in prompt doom loops, burning tokens every single time. The output is always a flat PNG, limiting what you can do with it. Lica World actually reads your image and breaks it into structured, editable layers. You go in, change what you need to change, and everything else stays exactly where it was. Route each layer to the right model or a capable human. You don't need to regenerate from scratch or pay the token tax to fix a font color. Enterprises publishing creatives across site, social, and email are already using Lica to own their model and own their output. We're grateful to be supported by Accel, Amjad Masad, Srinivas Narayanan, , Village Global, and Michele Catasta to build the editing layer that AI image gen has been missing. Want early access? Check the next thread below.

Priyaa

1,441,592 görüntüleme • 4 ay önce

Everyone is asking the same question right now: What happens next for $MSTR and $STRC? 🤔 We sat down with K A L E O to debate it in depth, laying out the bull case for Strategy and digital credit while hearing the bear case directly. This is an opportunity to understand both sides of the story, assess the risks, and decide for yourself what may come next. 👇 ⏱️ Timestamps: 00:00 Introduction 04:22 K A L E O’s market outlook 07:10 The bear case for $MSTR and $STRC 11:54 The bull case: refinancing, liquidity & capital access 19:42 When does Strategy’s capital structure become a concern? 24:22 Credit risk, duration & preferred equity 36:28 Has Strategy shifted the goalposts? 43:45 What should Strategy do differently? 45:52 Why $MSTR needs leverage 50:46 Has the market rejected preferred-based leverage? 55:08 How Apyx handles $STRC discount risk 01:06:08 Is apxUSD really a stablecoin? 01:11:18 Redemptions, weekend liquidity & market structure 01:19:59 Market pressure, sentiment & potential short attacks 01:22:56 Closing bull case for Strategy 01:25:18 Closing thoughts from K A L E O
1:28:10

Everyone is asking the same question right now: What happens next for $MSTR and $STRC? 🤔 We sat down with K A L E O to debate it in depth, laying out the bull case for Strategy and digital credit while hearing the bear case directly. This is an opportunity to understand both sides of the story, assess the risks, and decide for yourself what may come next. 👇 ⏱️ Timestamps: 00:00 Introduction 04:22 K A L E O’s market outlook 07:10 The bear case for $MSTR and $STRC 11:54 The bull case: refinancing, liquidity & capital access 19:42 When does Strategy’s capital structure become a concern? 24:22 Credit risk, duration & preferred equity 36:28 Has Strategy shifted the goalposts? 43:45 What should Strategy do differently? 45:52 Why $MSTR needs leverage 50:46 Has the market rejected preferred-based leverage? 55:08 How Apyx handles $STRC discount risk 01:06:08 Is apxUSD really a stablecoin? 01:11:18 Redemptions, weekend liquidity & market structure 01:19:59 Market pressure, sentiment & potential short attacks 01:22:56 Closing bull case for Strategy 01:25:18 Closing thoughts from K A L E O

Apyx

27,673 görüntüleme • 1 ay önce

i just figured out the best way to use Seedance 2.5 latest model from ByteDance lets you generate up to 30 second continuous videos and accepts up to 50 reference assets (images, videos and audio) all in one generation most people overcomplicate it, the real trick is in the details my prompt structure looks like this: [1] global scene + visual style [2] character descriptions [3] timestamped storyboard (0-5s, 5-10s, 10-15s...) [4] camera movement [5] negative prompts [6] ending constraints for example, instead of saying: "girl doing her skincare routine with x product" you tell it exactly what happens every few seconds, where the camera moves, how the emotion changes, what should never appear i put together the exact framework i use and leaking it all to you right now here's what you're getting: > the prompt formula for 30-second videos > how to Use Seedance 2.5 at a fraction of the cost > the best way to use reference images/videos > transitions, camera movements and negative prompts RT + reply "SEEDANCE" and i'll send it over (must follow so i can dm)
0:30

i just figured out the best way to use Seedance 2.5 latest model from ByteDance lets you generate up to 30 second continuous videos and accepts up to 50 reference assets (images, videos and audio) all in one generation most people overcomplicate it, the real trick is in the details my prompt structure looks like this: [1] global scene + visual style [2] character descriptions [3] timestamped storyboard (0-5s, 5-10s, 10-15s...) [4] camera movement [5] negative prompts [6] ending constraints for example, instead of saying: "girl doing her skincare routine with x product" you tell it exactly what happens every few seconds, where the camera moves, how the emotion changes, what should never appear i put together the exact framework i use and leaking it all to you right now here's what you're getting: > the prompt formula for 30-second videos > how to Use Seedance 2.5 at a fraction of the cost > the best way to use reference images/videos > transitions, camera movements and negative prompts RT + reply "SEEDANCE" and i'll send it over (must follow so i can dm)

MAX

70,221 görüntüleme • 2 gün önce