Shadow Nick's banner

Shadow Nick

@doublenickk • 12,610 subscribers

Co-founder @CloseAI_hq | AI has already taken over the world | Team: @WowmaxExchange

Shorts

IT'S MONDAY MORNING. YOU'RE ASLEEP Your trading agent has already opened three positions, adjusted risk exposure twice, and closed a profitable trade. Before you reached for your phone. $100,000 simulated capital. 72 hours of full autonomy. $6,000 prize pool. Zero coding required > no-code agent builder, if you can describe how you think about markets, Bloome builds the agent > four specialized agents running simultaneously: research, technical analysis, risk management, execution > scoring rewards discipline, a 7% return with clean risk management beats a 14% return with chaos > 1,000 invite slots, competition activates at 50 participants, the field is still small right now > first place: $3,000 · second: $2,000 · third: $1,000 · payouts go out June 12 this isn't a trading bot competition it's a test of whether you can think systematically about markets and encode that thinking into an autonomous system the old model: sit at a screen, make emotional decisions, compete against algorithms that never sleep the new model: build the algorithm → let it run → go to sleep

IT'S MONDAY MORNING. YOU'RE ASLEEP Your trading agent has already opened three positions, adjusted risk exposure twice, and closed a profitable trade. Before you reached for your phone. $100,000 simulated capital. 72 hours of full autonomy. $6,000 prize pool. Zero coding required > no-code agent builder, if you can describe how you think about markets, Bloome builds the agent > four specialized agents running simultaneously: research, technical analysis, risk management, execution > scoring rewards discipline, a 7% return with clean risk management beats a 14% return with chaos > 1,000 invite slots, competition activates at 50 participants, the field is still small right now > first place: $3,000 · second: $2,000 · third: $1,000 · payouts go out June 12 this isn't a trading bot competition it's a test of whether you can think systematically about markets and encode that thinking into an autonomous system the old model: sit at a screen, make emotional decisions, compete against algorithms that never sleep the new model: build the algorithm → let it run → go to sleep

29,119 次观看

Videos

Anya Rossi

sweetdream.ai

SweetDream.ai•Sponsored•Livecam

Watch Anya Live

Anya is streaming live right now! Join her private show and enjoy exclusive content.

Exclusive private shows

1.2k viewers online

Private Show

Join now for exclusive access

Free preview available • Premium content

Fable 5 and Karpathy's knowledge base trick are basically a cheat code. Someone just dropped a full walkthrough on building the most powerful second brain ever Andrej Karpathy shared a simple idea: use an LLM to build personal knowledge bases. Index your sources, let the model organize them, and use Obsidian as the front end. Someone just built the full thing with Claude Code and Fable 5, and walked through every step You drop your sources into a folder (YouTube transcripts, PDFs, articles, meeting notes) and Claude Code reads them, splits them into linked wiki pages, and builds a living second brain that connects everything. It grows on its own as you add more. Where Fable 5 pulls ahead: it found a connection buried across two sources you'd miss reading them separately. And asked to turn the messy web of links into something a beginner could understand, it produced clean, simple HTML in one shot. The same task took a full day on Opus 4.8 and came out worse. The best part: it's all just markdown files with routing. So it's not locked to Claude Code. Plug it into Codex or any agent you want. Give your AI a real knowledge base, and it stops guessing and starts knowing. Bookmark this.

Fable 5 and Karpathy's knowledge base trick are basically a cheat code. Someone just dropped a full walkthrough on building the most powerful second brain ever Andrej Karpathy shared a simple idea: use an LLM to build personal knowledge bases. Index your sources, let the model organize them, and use Obsidian as the front end. Someone just built the full thing with Claude Code and Fable 5, and walked through every step You drop your sources into a folder (YouTube transcripts, PDFs, articles, meeting notes) and Claude Code reads them, splits them into linked wiki pages, and builds a living second brain that connects everything. It grows on its own as you add more. Where Fable 5 pulls ahead: it found a connection buried across two sources you'd miss reading them separately. And asked to turn the messy web of links into something a beginner could understand, it produced clean, simple HTML in one shot. The same task took a full day on Opus 4.8 and came out worse. The best part: it's all just markdown files with routing. So it's not locked to Claude Code. Plug it into Codex or any agent you want. Give your AI a real knowledge base, and it stops guessing and starts knowing. Bookmark this.

45,330 次观看 • 2 天前

EVERYONE BUYING A $4,200 MAC STUDIO FOR LOCAL AI MISSED THAT TESLA V100s FROM DGX SERVERS ARE DUMPED ON EBAY FOR $250, AND ONE JUST RAN GPT-OSS 20B AT HOME a Tesla V100 SXM2 16GB shipped inside nvidia DGX-1 nodes at $10,000 per card in 2017, eight per chassis. those same cards now retire from cloud datacenters as H100s land, dumped on ebay at $200 to $300. drop a $50 SXM2 to PCIe adapter into a Z8 G4, slot the card with thermal pad, total bill $330. GPT-OSS 20B runs at 87°C and 180W the article calls the $700 used RTX 3090 the best memory per dollar. this V100 hack does the same job for one third the price with HBM2. the catch: HP Z620 fails on AVX2, install CUDA 11 not 12, flip above 4G decoding in BIOS the V100 pulls 250W and the blower screams. the mac mini from the article pulls 30W and runs silent. $300 versus $4,200 buys a lot of electricity and earplugs over four years

EVERYONE BUYING A $4,200 MAC STUDIO FOR LOCAL AI MISSED THAT TESLA V100s FROM DGX SERVERS ARE DUMPED ON EBAY FOR $250, AND ONE JUST RAN GPT-OSS 20B AT HOME a Tesla V100 SXM2 16GB shipped inside nvidia DGX-1 nodes at $10,000 per card in 2017, eight per chassis. those same cards now retire from cloud datacenters as H100s land, dumped on ebay at $200 to $300. drop a $50 SXM2 to PCIe adapter into a Z8 G4, slot the card with thermal pad, total bill $330. GPT-OSS 20B runs at 87°C and 180W the article calls the $700 used RTX 3090 the best memory per dollar. this V100 hack does the same job for one third the price with HBM2. the catch: HP Z620 fails on AVX2, install CUDA 11 not 12, flip above 4G decoding in BIOS the V100 pulls 250W and the blower screams. the mac mini from the article pulls 30W and runs silent. $300 versus $4,200 buys a lot of electricity and earplugs over four years

100,935 次观看 • 8 天前

Anthropic shipped 125 settings for Claude The official docs cover 40 One developer found the other 85 and his API bill dropped from $340 to $87 - not by using a cheaper model - not by writing shorter prompts just by moving one line in a config file to the right place > memory scoped per project → past clients never bleed into new work > Extended Thinking on Light by default → 18–25% fewer Opus tokens in week one > cache_control moved to the right line → the fix that turned a $340 bill into $87 > plugins and MCP servers toggled off when idle → saved 25–40K tokens per session > per-project model override → Haiku for docs, Sonnet for infra, Opus only where it matters most Claude users are running a $100/month tool at 30% of its actual capability

Anthropic shipped 125 settings for Claude The official docs cover 40 One developer found the other 85 and his API bill dropped from $340 to $87 - not by using a cheaper model - not by writing shorter prompts just by moving one line in a config file to the right place > memory scoped per project → past clients never bleed into new work > Extended Thinking on Light by default → 18–25% fewer Opus tokens in week one > cache_control moved to the right line → the fix that turned a $340 bill into $87 > plugins and MCP servers toggled off when idle → saved 25–40K tokens per session > per-project model override → Haiku for docs, Sonnet for infra, Opus only where it matters most Claude users are running a $100/month tool at 30% of its actual capability

379,495 次观看 • 1 个月前

EVERYONE IS COPYING AI PROMPTS, BUT ALMOST NOBODY IS COPYING THE SYSTEM BEHIND THEM That is exactly why a small number of creators are generating millions of views while everyone else keeps wondering why the same prompts never work twice. 27 videos → 175,000 subscribers → Millions of views per upload ust a system and the patience to set it up once. The channel is about backyard bunker timelapses. Which sounds absurdly niche. And that's exactly why it works. It's the one content format where: the viewer literally cannot stop watching because they need to see it finished > ChatGPT generates the full construction blueprint, every phase, every prompt, in perfect sequence > Google Whisk creates the opening frame in 9:16 before a single video is generated > Grok animates each phase from the last frame of the previous clip, seamless continuity > the frame extractor is the secret, last frame of clip 1 becomes first frame of clip 2, every time > CapCut stitches it all together, and the raw construction sounds stay in because they're what hooks people

EVERYONE IS COPYING AI PROMPTS, BUT ALMOST NOBODY IS COPYING THE SYSTEM BEHIND THEM That is exactly why a small number of creators are generating millions of views while everyone else keeps wondering why the same prompts never work twice. 27 videos → 175,000 subscribers → Millions of views per upload ust a system and the patience to set it up once. The channel is about backyard bunker timelapses. Which sounds absurdly niche. And that's exactly why it works. It's the one content format where: the viewer literally cannot stop watching because they need to see it finished > ChatGPT generates the full construction blueprint, every phase, every prompt, in perfect sequence > Google Whisk creates the opening frame in 9:16 before a single video is generated > Grok animates each phase from the last frame of the previous clip, seamless continuity > the frame extractor is the secret, last frame of clip 1 becomes first frame of clip 2, every time > CapCut stitches it all together, and the raw construction sounds stay in because they're what hooks people

35,097 次观看 • 23 天前

Stanford just proved Claude agrees with you 49% more than a human would The fix is the LLM Council from Andrei Karpathy. Five different advisers debate your decision inside one Claude chat: > contrarian (looks only for what will fail > first-principles thinker > expansionist (finds the upside) > outsider (knows nothing about your industry) > executor (Monday-morning next step) a chairman reads it all and gives you the final call.

Stanford just proved Claude agrees with you 49% more than a human would The fix is the LLM Council from Andrei Karpathy. Five different advisers debate your decision inside one Claude chat: > contrarian (looks only for what will fail > first-principles thinker > expansionist (finds the upside) > outsider (knows nothing about your industry) > executor (Monday-morning next step) a chairman reads it all and gives you the final call.

54,664 次观看 • 1 个月前

IN JUST 1 MONTH, HE EARNED $44,000 THANKS TO APPS IN THE APP STORE This guy has been taught his whole life that to create your own app, you need a team of 10 people, a degree in software development, start-up capital, etc. But it's good that he didn't listen to anyone and started studying the world of AI and Cladu Code. > he created the app in 2 days > later released it in the app store > he made his first sales > his app started gaining momentum > and within a month, he made his first money online

IN JUST 1 MONTH, HE EARNED $44,000 THANKS TO APPS IN THE APP STORE This guy has been taught his whole life that to create your own app, you need a team of 10 people, a degree in software development, start-up capital, etc. But it's good that he didn't listen to anyone and started studying the world of AI and Cladu Code. > he created the app in 2 days > later released it in the app store > he made his first sales > his app started gaining momentum > and within a month, he made his first money online

33,629 次观看 • 1 个月前

> 20 free daily tokens covers a full working session on GPT 5.5 or GLM > Opus 4.7 handles 2-3 serious architecture tasks per day at zero cost > one GitHub account can link to multiple Tembo accounts, the math on that is obvious > 5 minutes to sign up. 10 minutes to your first merged PR > no clarifying questions, prompts have to be precise, the agent just executes > the $100/month tools and the $0 tool are now producing the same output on most tasks and most developers haven't noticed yet this is not a discount → this is the same models → the same → capability → the same output → for nothing!

> 20 free daily tokens covers a full working session on GPT 5.5 or GLM > Opus 4.7 handles 2-3 serious architecture tasks per day at zero cost > one GitHub account can link to multiple Tembo accounts, the math on that is obvious > 5 minutes to sign up. 10 minutes to your first merged PR > no clarifying questions, prompts have to be precise, the agent just executes > the $100/month tools and the $0 tool are now producing the same output on most tasks and most developers haven't noticed yet this is not a discount → this is the same models → the same → capability → the same output → for nothing!

26,539 次观看 • 1 个月前

AN AI CONSULTING AGENCY REVEALED HOW THEY ACQUIRE CLIENTS And the process is much simpler than most people think. They start by choosing one niche they understand deeply, such as law firms, roofers, pest control companies, or construction businesses. Then they create a highly specific offer with a clear outcome and minimal risk for the client. The next step is where AI changes everything. AI generates ad creatives, marketing assets, and lead generation campaigns that run across Facebook, Instagram, and TikTok. Once leads start coming in, automated workflows help qualify, organize, and manage the entire process.

AN AI CONSULTING AGENCY REVEALED HOW THEY ACQUIRE CLIENTS And the process is much simpler than most people think. They start by choosing one niche they understand deeply, such as law firms, roofers, pest control companies, or construction businesses. Then they create a highly specific offer with a clear outcome and minimal risk for the client. The next step is where AI changes everything. AI generates ad creatives, marketing assets, and lead generation campaigns that run across Facebook, Instagram, and TikTok. Once leads start coming in, automated workflows help qualify, organize, and manage the entire process.

17,718 次观看 • 29 天前

MY YOUNGER BROTHER GOT 45M+ VIEWS ON X THANKS TO THIS My younger brother is 17 years old and was looking for a suitable platform to fulfill his potential. I sent him my article and recommended X platform, as it offers limitless opportunities. Moreover, it has one of the best monetization options and some of the best algorithms. What he did next to achieve 45M+ views in a month: > downloaded X and registered > studied my article > chose a content vertical > published content wisely every day > enabled monetization within a month and received his first payout of $12,000

MY YOUNGER BROTHER GOT 45M+ VIEWS ON X THANKS TO THIS My younger brother is 17 years old and was looking for a suitable platform to fulfill his potential. I sent him my article and recommended X platform, as it offers limitless opportunities. Moreover, it has one of the best monetization options and some of the best algorithms. What he did next to achieve 45M+ views in a month: > downloaded X and registered > studied my article > chose a content vertical > published content wisely every day > enabled monetization within a month and received his first payout of $12,000

17,501 次观看 • 1 个月前

9 out of 10 multi-agent projects never leave demo mode Not because the model is bad. Because the structure is missing. Most people who try to build [ a team of AI agents ] end up with one agent talking to itself in five tabs. The agents don't share context → Don't divide work → Don't know what the others are doing. > stage 1: if your agent doesn't have a real loop, observe, act, iterate, you have a long prompt, not an agent > stage 2: subagents need isolated context, the orchestrator never reads their raw transcript, only the summary > stage 3: the orchestrator plans and delegates, the moment it executes, it drowns in details that belong inside subagents > stage 4: without a shared task list it's not a team, it's five agents duplicating each other's work in parallel > stage 5: a permissions file is what lets you sleep, the model cannot bypass it because the rule lives outside the model a team of AI agents is not more model, it is more structure the most ignored stage in every demo that died: - durability... when a 50-step task crashes at step 47 and starts from zero, that's not a model failure. that's a missing write-to-disk call

9 out of 10 multi-agent projects never leave demo mode Not because the model is bad. Because the structure is missing. Most people who try to build [ a team of AI agents ] end up with one agent talking to itself in five tabs. The agents don't share context → Don't divide work → Don't know what the others are doing. > stage 1: if your agent doesn't have a real loop, observe, act, iterate, you have a long prompt, not an agent > stage 2: subagents need isolated context, the orchestrator never reads their raw transcript, only the summary > stage 3: the orchestrator plans and delegates, the moment it executes, it drowns in details that belong inside subagents > stage 4: without a shared task list it's not a team, it's five agents duplicating each other's work in parallel > stage 5: a permissions file is what lets you sleep, the model cannot bypass it because the rule lives outside the model a team of AI agents is not more model, it is more structure the most ignored stage in every demo that died: - durability... when a 50-step task crashes at step 47 and starts from zero, that's not a model failure. that's a missing write-to-disk call

14,501 次观看 • 1 个月前

没有更多内容可加载