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BREAKING: 300+ Ready-Made Business Automations... Inside you'll get complete systems for: → Social Media(s) (create, auto-post, engage, grow) → Customer Communication (Gmail, WhatsApp, Slack - booking agents that work 24/7) → Data & Research (AI analysis, database management, Google Sheets sync, tailored research agents) → Team Management (HR, recruitment,...

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Damian Player

39,558 subscribers

125,934 次观看 • 1 年前 •via X (Twitter)

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Damian Player1 年前

#1 AI Group (Free): Need an Agent? →

Anirudh Walia 的头像
Anirudh Walia1 年前

@MitchellKeller_ AUTOMATE

Hyperdiode 👾 的头像
Hyperdiode 👾1 年前

Automate

Jurgen Proschinger 的头像
Jurgen Proschinger1 年前

@damianbplayer, automations can save us so much time! Streamlining communication and social media is critical for productivity. #BusinessEfficiency

Damian Player 的头像
Damian Player1 年前

#businessefficiency

Ryan 的头像
Ryan1 年前

Are you actually gonna send this? If so Damian is an actual player “Automate”

Ryan 的头像
Ryan1 年前

“automate” i really need it 🙏🙏

Ray “dogeaboy” Rivera 的头像
Ray “dogeaboy” Rivera1 年前

Automate

Web3_Mike 的头像
Web3_Mike1 年前

AUTOMATE

Agent Integrator 的头像
Agent Integrator1 年前

AUTOMATE

相关视频

LEAKED: 100s of premium AI Agents EXPOSED... These Agents sell for $5,000+ per build, easily... Inside the file you’ll get: → Lead qualification agents → Content generation pipelines → Appointment booking automation → Cold outreach sequences → Data extraction & web scrapers → Customer support agents → +100s more plug & play systems BONUS: An n8n Masterclass, so you know how to run, customize, and scale every workflow. These are the same systems 6-figure agencies use to deliver high-ticket builds. Follow + RT + Comment “VAULT” and I’ll send you the drive for FREE! PS: If you’re still building agents manually… Consider this your early retirement package.
0:34

LEAKED: 100s of premium AI Agents EXPOSED... These Agents sell for $5,000+ per build, easily... Inside the file you’ll get: → Lead qualification agents → Content generation pipelines → Appointment booking automation → Cold outreach sequences → Data extraction & web scrapers → Customer support agents → +100s more plug & play systems BONUS: An n8n Masterclass, so you know how to run, customize, and scale every workflow. These are the same systems 6-figure agencies use to deliver high-ticket builds. Follow + RT + Comment “VAULT” and I’ll send you the drive for FREE! PS: If you’re still building agents manually… Consider this your early retirement package.

Damian Player

295,814 次观看 • 1 年前

EXPOSED: 200+ AI Agents have been LEAKED... These Agents SELL for $5,000+ per build and cover 20+ industries... Inside the file you’ll get: →Social Media Agents ($8k+) →Creative Content Agents ($3k+) →Cold outreach Agents ($3k+) →Lead Booking Agents ($6k+) →Customer support agents ($5k+) →Data & Scraping Agent ($8k+) →Lead qualification agents ($4k+) →Productivity, HR, Analytics, DevOps & legal Agents also! 100s of plug & play systems that save you time AND money. Follow + RT + Comment “AGENTS” and I’ll send you the drive for FREE! BONUS: An n8n Masterclass, so you know how to run, customize, and scale every workflow. PS: I'm only keeping this live for 48 hours. After that, it's back to $5k+ per agent. Your move.
0:32

EXPOSED: 200+ AI Agents have been LEAKED... These Agents SELL for $5,000+ per build and cover 20+ industries... Inside the file you’ll get: →Social Media Agents ($8k+) →Creative Content Agents ($3k+) →Cold outreach Agents ($3k+) →Lead Booking Agents ($6k+) →Customer support agents ($5k+) →Data & Scraping Agent ($8k+) →Lead qualification agents ($4k+) →Productivity, HR, Analytics, DevOps & legal Agents also! 100s of plug & play systems that save you time AND money. Follow + RT + Comment “AGENTS” and I’ll send you the drive for FREE! BONUS: An n8n Masterclass, so you know how to run, customize, and scale every workflow. PS: I'm only keeping this live for 48 hours. After that, it's back to $5k+ per agent. Your move.

Damian Player

261,869 次观看 • 1 年前

Four AI agents just replaced my $250,000 marketing team. I'm not talking about basic chatbots. I'm talking about AI systems that: → Write custom newsletters like Morning Brew → Generate viral social content (3.9M views on one post) → Steal competitor's best-performing ads and rebuild them → Create SEO content that ranks on page 1 of Google All running 24/7 without sick days, vacation requests, or performance reviews. The problem? Most businesses are still hiring expensive marketing teams when AI can now handle 90% of the workload for less than the cost of one employee. I've been testing this for 6 months. The results are wild: ✅ Millions of impressions generated monthly ✅ Tens of thousands in revenue on autopilot ✅ Content creation at enterprise scale ✅ Zero manual research or writing These four agents handle content research, creation, paid advertising creative, and SEO content - work that typically requires a 5-7 person marketing team. The businesses adopting AI marketing agents like these will have an insurmountable advantage while everyone else is still hiring expensive teams and dealing with human limitations. Want the exact n8n templates for all four agents? 1. Like & RT this post 2. Follow me for more AI automation breakdowns 3. Comment "AGENTS" below I'll send you the complete system for free, plus access to my YouTube tutorials showing the step-by-step builds.
0:40

Four AI agents just replaced my $250,000 marketing team. I'm not talking about basic chatbots. I'm talking about AI systems that: → Write custom newsletters like Morning Brew → Generate viral social content (3.9M views on one post) → Steal competitor's best-performing ads and rebuild them → Create SEO content that ranks on page 1 of Google All running 24/7 without sick days, vacation requests, or performance reviews. The problem? Most businesses are still hiring expensive marketing teams when AI can now handle 90% of the workload for less than the cost of one employee. I've been testing this for 6 months. The results are wild: ✅ Millions of impressions generated monthly ✅ Tens of thousands in revenue on autopilot ✅ Content creation at enterprise scale ✅ Zero manual research or writing These four agents handle content research, creation, paid advertising creative, and SEO content - work that typically requires a 5-7 person marketing team. The businesses adopting AI marketing agents like these will have an insurmountable advantage while everyone else is still hiring expensive teams and dealing with human limitations. Want the exact n8n templates for all four agents? 1. Like & RT this post 2. Follow me for more AI automation breakdowns 3. Comment "AGENTS" below I'll send you the complete system for free, plus access to my YouTube tutorials showing the step-by-step builds.

David Roberts

109,408 次观看 • 10 个月前

I built an AI WhatsApp agent that turns any business website into a 24/7 support & sales machine. With 200M+ businesses around the world relying on WhatsApp for customer communication, the TAM for this type of simple automation is significant. Here's the n8n workflow that's handling customer support and closing leads while business owners sleep: → Drop in any business URL → AI scrapes the entire site and builds a knowledge base → WhatsApp bot answers customer questions instantly → Converts inquiries into booked calls without human intervention Most businesses still have customers sitting in unread WhatsApp messages for hours. This workflow responds in seconds. The best part: It's simple. This took me 10 minutes to set up once the automation was built. If you want the n8n workflow, all the prompts, and a full setup video: Comment "WHATSAPP" Like + RT Follow me (so I can DM you) I'll send everything over.
3:38

I built an AI WhatsApp agent that turns any business website into a 24/7 support & sales machine. With 200M+ businesses around the world relying on WhatsApp for customer communication, the TAM for this type of simple automation is significant. Here's the n8n workflow that's handling customer support and closing leads while business owners sleep: → Drop in any business URL → AI scrapes the entire site and builds a knowledge base → WhatsApp bot answers customer questions instantly → Converts inquiries into booked calls without human intervention Most businesses still have customers sitting in unread WhatsApp messages for hours. This workflow responds in seconds. The best part: It's simple. This took me 10 minutes to set up once the automation was built. If you want the n8n workflow, all the prompts, and a full setup video: Comment "WHATSAPP" Like + RT Follow me (so I can DM you) I'll send everything over.

David Roberts

61,207 次观看 • 6 个月前

We’re excited to announce AI SDR-Kit, a comprehensive suite of app integrations and starter templates to build highly customizable AI sales agents. As a developer, I only realized how tough it can be to crack sales after founding my startup. It’s a lot of grunt work, prospecting, qualifying, outreaching and whatnot. And the complexity only goes up as you grow. But it doesn’t have to. AI agents can effectively optimize many of these routine tasks; for instance, they can find leads from Apollo, enrich their data using People Data Labs, manage them in Salesforce, send targeted emails via SendGrid, and schedule meetings in Calendly without any manual involvement. But the biggest challenge is building these app integrations for agents. A single Salesforce integration may take 100s of engineering hours, let alone other integrations across CRMs, email platforms, and data enrichment tools. Considering this, we Composio built AI SDR-Kit to enable developers to build full-fledged sales automation agents. You will get • Over 60 app integrations optimized for SDR/BDR agents. • Seamless handling of complex auth flows (OAuth, API Key, Basic). • Compatibility with 15+ Agentic Frameworks, including LangChain, LlamaIndex 🦙, CrewAI, Letta etc. • Self-hosting option for greater control. • Enterprise-ready with SOC 2 Type 2 compliance, SSO, and RBAC support. Here's a brief list of popular integrations by category that you get with SDR-Kit: • CRM: Salesforce, HubSpot, Attio, and more. • Contact Data: Apollo, ZoomInfo, People Data Labs, etc. • Email deliverability: Gmail, Outlook, Mailchimp, SendGrid, Klaviyo. • Comms & Collabs: Slack, Discord, Intercom & Zoom. • Social Media: LinkedIn, Facebook, Twitter & Reddit. • Meeting: Google Calendar, Calendly, Cal dot com, etc. • … and many more. All the integrations have been improved, keeping agents' real-world readiness in mind. We’ve also made it straightforward to connect these apps with your agents in a few lines of code. Making it easy to create AI sales agents. This is ideal for developers and companies building automated sales solutions - whether for internal SalesOps or AI SDR services. Checkout AI SDR-Kit now👇
1:21

We’re excited to announce AI SDR-Kit, a comprehensive suite of app integrations and starter templates to build highly customizable AI sales agents. As a developer, I only realized how tough it can be to crack sales after founding my startup. It’s a lot of grunt work, prospecting, qualifying, outreaching and whatnot. And the complexity only goes up as you grow. But it doesn’t have to. AI agents can effectively optimize many of these routine tasks; for instance, they can find leads from Apollo, enrich their data using People Data Labs, manage them in Salesforce, send targeted emails via SendGrid, and schedule meetings in Calendly without any manual involvement. But the biggest challenge is building these app integrations for agents. A single Salesforce integration may take 100s of engineering hours, let alone other integrations across CRMs, email platforms, and data enrichment tools. Considering this, we Composio built AI SDR-Kit to enable developers to build full-fledged sales automation agents. You will get • Over 60 app integrations optimized for SDR/BDR agents. • Seamless handling of complex auth flows (OAuth, API Key, Basic). • Compatibility with 15+ Agentic Frameworks, including LangChain, LlamaIndex 🦙, CrewAI, Letta etc. • Self-hosting option for greater control. • Enterprise-ready with SOC 2 Type 2 compliance, SSO, and RBAC support. Here's a brief list of popular integrations by category that you get with SDR-Kit: • CRM: Salesforce, HubSpot, Attio, and more. • Contact Data: Apollo, ZoomInfo, People Data Labs, etc. • Email deliverability: Gmail, Outlook, Mailchimp, SendGrid, Klaviyo. • Comms & Collabs: Slack, Discord, Intercom & Zoom. • Social Media: LinkedIn, Facebook, Twitter & Reddit. • Meeting: Google Calendar, Calendly, Cal dot com, etc. • … and many more. All the integrations have been improved, keeping agents' real-world readiness in mind. We’ve also made it straightforward to connect these apps with your agents in a few lines of code. Making it easy to create AI sales agents. This is ideal for developers and companies building automated sales solutions - whether for internal SalesOps or AI SDR services. Checkout AI SDR-Kit now👇

Karan Vaidya

54,217 次观看 • 1 年前

Data teams spend weeks on simple requests. (This AI answers them in minutes.) Most data analysis is repetitive manual tasks. Data teams spend more time on setup than actual analysis. The workflow usually looks like this: → Run some exploratory data analysis in a local Jupyter notebook or environment → Pull data from multiple disconnected sources → Write code from scratch for every analysis → Export static charts that stakeholders can't explore (or wrestle with legacy BI to create a dashboard) → Manually send updates via email or Slack when data changes → Start over for each new request Most teams accept this as "how data analysis works." While business decisions wait for insights. That's where Fabi changes the entire approach. It's a powerful, AI-native platform built for teams that want to boost productivity and supercharge their data workflows. Instead of working on separate tools and manual processes, you collaborate on analysis that automatically delivers insights where teams work. Here's what makes Fabi different: AI-Native Analysis Environment ↳ SQL and Python work together with AI assistance that handles coding and debugging automatically. Smart Automation Workflows ↳ Automatically send AI-powered reports and summaries right where business works in Slack, email, and spreadsheets. Universal Data Integration ↳ Analyze data from files, Google Sheets, Airtable, plus your data warehouse and databases in one place. Collaborative Data Apps ↳ Create interactive dashboards that stakeholders can explore and ask follow-up questions directly. What you can do with Fabi that legacy BI can't: ➟ Send AI-generated insights directly to Slack channels ➟ Automatically email data summaries to stakeholders ➟ Analyze uploaded files without complex ETL processes ➟ Collaborate on analysis like Google Docs for data ➟ Build workflows that push insights to spreadsheets Perfect for teams that want to move beyond the constraints of legacy and increase their impact. Teams using Fabi see immediate results: ✓ Insights delivered in minutes instead of days ✓ Reduced context switching between tools ✓ Stakeholders explore data independently ✓ Workflows automated to save hours of manual work From analysis to automated delivery - all in one AI-native environment. 📌 Try Fabi today: 👉 Follow Fabi.ai and marc for Fabi updates. 🔄 Repost to help other teams streamline data analysis #DataAnalysis #ModernBI #DataOps #InteractiveDashboards #FabiPartnership #SponsoredByFabi
5:34

Data teams spend weeks on simple requests. (This AI answers them in minutes.) Most data analysis is repetitive manual tasks. Data teams spend more time on setup than actual analysis. The workflow usually looks like this: → Run some exploratory data analysis in a local Jupyter notebook or environment → Pull data from multiple disconnected sources → Write code from scratch for every analysis → Export static charts that stakeholders can't explore (or wrestle with legacy BI to create a dashboard) → Manually send updates via email or Slack when data changes → Start over for each new request Most teams accept this as "how data analysis works." While business decisions wait for insights. That's where Fabi changes the entire approach. It's a powerful, AI-native platform built for teams that want to boost productivity and supercharge their data workflows. Instead of working on separate tools and manual processes, you collaborate on analysis that automatically delivers insights where teams work. Here's what makes Fabi different: AI-Native Analysis Environment ↳ SQL and Python work together with AI assistance that handles coding and debugging automatically. Smart Automation Workflows ↳ Automatically send AI-powered reports and summaries right where business works in Slack, email, and spreadsheets. Universal Data Integration ↳ Analyze data from files, Google Sheets, Airtable, plus your data warehouse and databases in one place. Collaborative Data Apps ↳ Create interactive dashboards that stakeholders can explore and ask follow-up questions directly. What you can do with Fabi that legacy BI can't: ➟ Send AI-generated insights directly to Slack channels ➟ Automatically email data summaries to stakeholders ➟ Analyze uploaded files without complex ETL processes ➟ Collaborate on analysis like Google Docs for data ➟ Build workflows that push insights to spreadsheets Perfect for teams that want to move beyond the constraints of legacy and increase their impact. Teams using Fabi see immediate results: ✓ Insights delivered in minutes instead of days ✓ Reduced context switching between tools ✓ Stakeholders explore data independently ✓ Workflows automated to save hours of manual work From analysis to automated delivery - all in one AI-native environment. 📌 Try Fabi today: 👉 Follow Fabi.ai and marc for Fabi updates. 🔄 Repost to help other teams streamline data analysis #DataAnalysis #ModernBI #DataOps #InteractiveDashboards #FabiPartnership #SponsoredByFabi

Andrew Bolis

36,504 次观看 • 11 个月前

This AI system created a viral Instagram reel with 4.1M views... completely on autopilot (linked below). These millions of views led to 10,000+ newsletter subscribers for my AI newsletter @therecapai While most creators burn out from the daily content grind, I built an n8n automation that transforms raw AI news into scroll-stopping short-form video. Here's what happens behind the scenes: → Data ingestion agents scrape Twitter, Reddit, and top AI blogs 24/7 → AI analyzes hundreds of stories and picks the top 3-5 most engaging ones → Advanced prompts craft multiple hook variations and full video scripts → HeyGen generates AI clone of me speaking script → Video editor in india ads B roll → Everything gets delivered to Slack for quick review and approval This system has brought my Instagram account to 16,000+ followers in just a few months. That's the power of consistent, data-driven content creation. I just released a deep-dive tutorial showing exactly how this works, including the prompts I literally spent hours on making it all possible. Want me to send it to you? Like & RT this post Follow so I can DM you Comment 'SYSTEM' and I'll share the complete workflow template + all the prompts. Your next viral video is literally just one automation away.
5:43

This AI system created a viral Instagram reel with 4.1M views... completely on autopilot (linked below). These millions of views led to 10,000+ newsletter subscribers for my AI newsletter @therecapai While most creators burn out from the daily content grind, I built an n8n automation that transforms raw AI news into scroll-stopping short-form video. Here's what happens behind the scenes: → Data ingestion agents scrape Twitter, Reddit, and top AI blogs 24/7 → AI analyzes hundreds of stories and picks the top 3-5 most engaging ones → Advanced prompts craft multiple hook variations and full video scripts → HeyGen generates AI clone of me speaking script → Video editor in india ads B roll → Everything gets delivered to Slack for quick review and approval This system has brought my Instagram account to 16,000+ followers in just a few months. That's the power of consistent, data-driven content creation. I just released a deep-dive tutorial showing exactly how this works, including the prompts I literally spent hours on making it all possible. Want me to send it to you? Like & RT this post Follow so I can DM you Comment 'SYSTEM' and I'll share the complete workflow template + all the prompts. Your next viral video is literally just one automation away.

David Roberts

13,100 次观看 • 9 个月前

Four AI agents increased the net-profit for an e-commerce business I work with by $47,000 in the last 90 days. I'm not talking about basic automations. I'm talking about AI systems that: → Generate professional product photos in seconds (no photographer needed) → Steal your competitor's best-performing Facebook ads and recreate them → Create unlimited influencer content without shipping a single product → Find qualified leads on Twitter 24/7 and convert them automatically All running while I sleep. No employees. No overhead. Just pure profit. The problem? Most e-commerce owners are still paying photographers $2-5K/month, burning ad budgets on creative that flops, and spending thousands per influencer post. I've been testing these agents for 4 months. The numbers are insane: ✅ $10K+ saved annually on product photography alone ✅ Ad creative costs slashed by 50% ✅ 47 influencer ads generated for $3 in API calls (vs $14K traditional cost) ✅ $3K in revenue from completely free Twitter traffic These four agents handle product photography, ad creative, influencer content, and lead generation - work that used to cost $6K+/month in freelancers and agencies. The e-commerce stores deploying AI agents like these are about to eat everyone's lunch while others are still manually creating content and bleeding cash on ads. Want the exact n8n templates for all four agents? Like & RT this post Follow me (so I can dm you) Comment "PROFIT" below I'll send you the complete systems for free, plus links to my YouTube tutorials showing the step-by-step builds.
6:05

Four AI agents increased the net-profit for an e-commerce business I work with by $47,000 in the last 90 days. I'm not talking about basic automations. I'm talking about AI systems that: → Generate professional product photos in seconds (no photographer needed) → Steal your competitor's best-performing Facebook ads and recreate them → Create unlimited influencer content without shipping a single product → Find qualified leads on Twitter 24/7 and convert them automatically All running while I sleep. No employees. No overhead. Just pure profit. The problem? Most e-commerce owners are still paying photographers $2-5K/month, burning ad budgets on creative that flops, and spending thousands per influencer post. I've been testing these agents for 4 months. The numbers are insane: ✅ $10K+ saved annually on product photography alone ✅ Ad creative costs slashed by 50% ✅ 47 influencer ads generated for $3 in API calls (vs $14K traditional cost) ✅ $3K in revenue from completely free Twitter traffic These four agents handle product photography, ad creative, influencer content, and lead generation - work that used to cost $6K+/month in freelancers and agencies. The e-commerce stores deploying AI agents like these are about to eat everyone's lunch while others are still manually creating content and bleeding cash on ads. Want the exact n8n templates for all four agents? Like & RT this post Follow me (so I can dm you) Comment "PROFIT" below I'll send you the complete systems for free, plus links to my YouTube tutorials showing the step-by-step builds.

David Roberts

19,902 次观看 • 10 个月前

This AI Training Includes $3M in Perks, Live Build Sessions, Enterprise Systems and More My mission: Turn AI from overwhelming hype into actual freedom for 1 billion+ people worldwide. I've spent 7+ years building AI systems across 10+ industries. Entered when GPT was just a next-word prediction model. Built over 100 automations that replaced teams and bought back time. Now I'm sharing everything inside AIC+. Here's what you're unlocking: → $3M+ in software perks: Perplexity, Loom, Notion, Make, Airtable, AWS, DigitalOcean, Google Cloud + 950 more → 50+ revenue-generating automation templates you can deploy immediately → Complete AI mastery curriculum from foundations to enterprise solutions → Lead generation machines that run themselves → Sales systems that close deals automatically → Live weekly build sessions where we create automations together → Live Q&A calls to get unstuck immediately → Direct mentorship from someone who's been in the trenches for 7+ years This is for entrepreneurs drowning in manual work, agency owners scaling without hiring, and anyone tired of AI tutorials that go nowhere. The promise: While others stay stuck in tutorial hell, you'll deploy systems that generate leads, close deals, and buy back your time. Founding members get lifetime pricing for 24 hours only. Like, RT + reply with "FREEDOM" and I'll DM you the founding member details (Must be following so I can DM) This is your moment to master practical AI before the world catches up.
4:40

This AI Training Includes $3M in Perks, Live Build Sessions, Enterprise Systems and More My mission: Turn AI from overwhelming hype into actual freedom for 1 billion+ people worldwide. I've spent 7+ years building AI systems across 10+ industries. Entered when GPT was just a next-word prediction model. Built over 100 automations that replaced teams and bought back time. Now I'm sharing everything inside AIC+. Here's what you're unlocking: → $3M+ in software perks: Perplexity, Loom, Notion, Make, Airtable, AWS, DigitalOcean, Google Cloud + 950 more → 50+ revenue-generating automation templates you can deploy immediately → Complete AI mastery curriculum from foundations to enterprise solutions → Lead generation machines that run themselves → Sales systems that close deals automatically → Live weekly build sessions where we create automations together → Live Q&A calls to get unstuck immediately → Direct mentorship from someone who's been in the trenches for 7+ years This is for entrepreneurs drowning in manual work, agency owners scaling without hiring, and anyone tired of AI tutorials that go nowhere. The promise: While others stay stuck in tutorial hell, you'll deploy systems that generate leads, close deals, and buy back your time. Founding members get lifetime pricing for 24 hours only. Like, RT + reply with "FREEDOM" and I'll DM you the founding member details (Must be following so I can DM) This is your moment to master practical AI before the world catches up.

Samruddhi Mokal

12,423 次观看 • 9 个月前

This Claude MCP AI Agent replaces your $200K+ Operations Teams. I probably shouldn't be sharing the exact system for free... while I was trying to catch Pikachu at 3am on Pokemon Go, it audited my entire business, found 12 bottlenecks, and built me 5 production-ready n8n agents the efficiency gain is absolutely INSANE most founders burn months hiring ops consultants who charge $500/hour just to tell you what's broken this agentic system does their entire job in minutes here's what happens when you deploy it: → runs complete business intelligence audit in 3 minutes (what takes consultants weeks) → identifies 12+ workflow bottlenecks killing your efficiency → architects custom agentic systems tailored to your business → builds 5+ autonomous AI agents with advanced error handling → creates intelligent orchestration layer syncing everything together → delivers complete operational transformation in under 10 minutes the entire audit that consultants charge $50K for now happens in 10 minutes ZERO technical knowledge needed ZERO expensive consultants required ZERO months of back-and-forth just describe your current setup and watch it build your agentic empire the math is stupid simple: $200K ops team salary vs one-time MCP deployment that's $16,600 saved monthly the system includes: - intelligent business stack analyzer - bottleneck detection AI - custom agentic architect - autonomous agent builder - complete deployment documentation this is the exact system building 7-figure operational infrastructure and you're getting it for free Follow + RT + comment "MCP" & I'll send you the FULL setup guide tonight don't sleep on this every week you wait is 30+ hours of manual work you'll never get back
0:24

This Claude MCP AI Agent replaces your $200K+ Operations Teams. I probably shouldn't be sharing the exact system for free... while I was trying to catch Pikachu at 3am on Pokemon Go, it audited my entire business, found 12 bottlenecks, and built me 5 production-ready n8n agents the efficiency gain is absolutely INSANE most founders burn months hiring ops consultants who charge $500/hour just to tell you what's broken this agentic system does their entire job in minutes here's what happens when you deploy it: → runs complete business intelligence audit in 3 minutes (what takes consultants weeks) → identifies 12+ workflow bottlenecks killing your efficiency → architects custom agentic systems tailored to your business → builds 5+ autonomous AI agents with advanced error handling → creates intelligent orchestration layer syncing everything together → delivers complete operational transformation in under 10 minutes the entire audit that consultants charge $50K for now happens in 10 minutes ZERO technical knowledge needed ZERO expensive consultants required ZERO months of back-and-forth just describe your current setup and watch it build your agentic empire the math is stupid simple: $200K ops team salary vs one-time MCP deployment that's $16,600 saved monthly the system includes: - intelligent business stack analyzer - bottleneck detection AI - custom agentic architect - autonomous agent builder - complete deployment documentation this is the exact system building 7-figure operational infrastructure and you're getting it for free Follow + RT + comment "MCP" & I'll send you the FULL setup guide tonight don't sleep on this every week you wait is 30+ hours of manual work you'll never get back

Aryan Mahajan

146,353 次观看 • 1 年前

JUST IN: Perplexity launched "Perplexity Computer" — and it might be the most complete AI agent system available right now. Not a chatbot upgrade. Not a research tool with a new name. A system that plans entire projects, delegates to specialist AI models, and runs autonomously for hours, days, or months (their words). Here's what makes the architecture genuinely different: → Opus 4.6 handles core reasoning and orchestration → Gemini handles deep research (spawning its own sub-agents) → Grok handles lightweight speed tasks → Veo 3.1 handles video generation → Nano Banana handles image creation → ChatGPT 5.2 handles long-context recall and wide search → You can override model choices per subtask 19 models total. Each task runs in an isolated environment with a real filesystem, real browser, and real tool integrations. You describe an outcome. It breaks it into tasks and subtasks, creates sub-agents for each, and coordinates them automatically. When a sub-agent hits a problem, it spawns more sub-agents to solve it. And it connects to your existing stack — GitHub, Google Drive, Gmail, Slack, Jira, Linear, Notion, Confluence, Ahrefs, Airtable, and more. Critically, it doesn't just run once. It can run on a schedule. Reading your docs, checking your project boards, pulling from your CRM, and acting on what it finds. Market monitoring. Competitor tracking. Weekly reports with charts. Content pipelines. CRON jobs that actually execute. Not "AI that helps you once." AI that runs in the background for days or months. Think of it as managed OpenClaw — similar autonomous capability (scheduled tasks, multi-step workflows, tool integrations) but fully managed. No Mac Mini. No security config. No infrastructure to maintain. I tested it with a complex prompt — a full stock trading simulator with what-if scenarios, correlation heatmaps, sentiment analysis, and a Bloomberg Terminal aesthetic. Two prompts later: deployed to Netlify via GitHub, with working CRON jobs updating live data. I've started using it to analyze my portfolio. But coding is just one lane. This thing researches, writes reports, generates datasets, creates videos, processes documents, and connects to your existing tools — all in one coordinated workflow. The real shift: you don't choose a model anymore. You describe what you need. The system routes each piece of work to whichever model does it best — and spawns new agents when it hits a wall. 19 models, dynamic sub-agents, scheduled tasks, and your entire tool stack connected. Thoughts?
0:37

JUST IN: Perplexity launched "Perplexity Computer" — and it might be the most complete AI agent system available right now. Not a chatbot upgrade. Not a research tool with a new name. A system that plans entire projects, delegates to specialist AI models, and runs autonomously for hours, days, or months (their words). Here's what makes the architecture genuinely different: → Opus 4.6 handles core reasoning and orchestration → Gemini handles deep research (spawning its own sub-agents) → Grok handles lightweight speed tasks → Veo 3.1 handles video generation → Nano Banana handles image creation → ChatGPT 5.2 handles long-context recall and wide search → You can override model choices per subtask 19 models total. Each task runs in an isolated environment with a real filesystem, real browser, and real tool integrations. You describe an outcome. It breaks it into tasks and subtasks, creates sub-agents for each, and coordinates them automatically. When a sub-agent hits a problem, it spawns more sub-agents to solve it. And it connects to your existing stack — GitHub, Google Drive, Gmail, Slack, Jira, Linear, Notion, Confluence, Ahrefs, Airtable, and more. Critically, it doesn't just run once. It can run on a schedule. Reading your docs, checking your project boards, pulling from your CRM, and acting on what it finds. Market monitoring. Competitor tracking. Weekly reports with charts. Content pipelines. CRON jobs that actually execute. Not "AI that helps you once." AI that runs in the background for days or months. Think of it as managed OpenClaw — similar autonomous capability (scheduled tasks, multi-step workflows, tool integrations) but fully managed. No Mac Mini. No security config. No infrastructure to maintain. I tested it with a complex prompt — a full stock trading simulator with what-if scenarios, correlation heatmaps, sentiment analysis, and a Bloomberg Terminal aesthetic. Two prompts later: deployed to Netlify via GitHub, with working CRON jobs updating live data. I've started using it to analyze my portfolio. But coding is just one lane. This thing researches, writes reports, generates datasets, creates videos, processes documents, and connects to your existing tools — all in one coordinated workflow. The real shift: you don't choose a model anymore. You describe what you need. The system routes each piece of work to whichever model does it best — and spawns new agents when it hits a wall. 19 models, dynamic sub-agents, scheduled tasks, and your entire tool stack connected. Thoughts?

Paweł Huryn

219,681 次观看 • 5 个月前

I built a local news podcast that gets generated each day with AI. Making a news show like this would normally cost $50,000+ annually. With AI Automation? $100/mo. The setup is simple: → Automatically scrapes Google News, local event feeds, twitter, reddit, and much more → Generates professional scripts with emotion and pacing controls → Produces broadcast-quality audio using ElevenLabs V3 → Operates completely hands-free once deployed The result? A business model that wasn't economically viable before AI. No hosts. No editors. No research team. Just smart automation and a few API subscriptions. This isn't about flooding the internet with crappy AI content. It's about solving real problems: like news deserts in underserved markets. The system I built in hours could theoretically power thousands of hyper-local podcasts simultaneously. When you start thinking in terms of "what can I automate," entire industries now become accessible. Before AI, the revenues you could generate by serving local news just didn't cover the expenses. Now that's changed. What other markets is that true for? Want me to send you the full system for you to clone for your small town or city? 1. Like & RT 2. Follow me (so I can dm you) 3. Comment "BLUEPRINT" below I'll send you the complete n8n template, all the prompting, and a full setup video that you can use to spin up your own local news podcast.
8:32

I built a local news podcast that gets generated each day with AI. Making a news show like this would normally cost $50,000+ annually. With AI Automation? $100/mo. The setup is simple: → Automatically scrapes Google News, local event feeds, twitter, reddit, and much more → Generates professional scripts with emotion and pacing controls → Produces broadcast-quality audio using ElevenLabs V3 → Operates completely hands-free once deployed The result? A business model that wasn't economically viable before AI. No hosts. No editors. No research team. Just smart automation and a few API subscriptions. This isn't about flooding the internet with crappy AI content. It's about solving real problems: like news deserts in underserved markets. The system I built in hours could theoretically power thousands of hyper-local podcasts simultaneously. When you start thinking in terms of "what can I automate," entire industries now become accessible. Before AI, the revenues you could generate by serving local news just didn't cover the expenses. Now that's changed. What other markets is that true for? Want me to send you the full system for you to clone for your small town or city? 1. Like & RT 2. Follow me (so I can dm you) 3. Comment "BLUEPRINT" below I'll send you the complete n8n template, all the prompting, and a full setup video that you can use to spin up your own local news podcast.

David Roberts

62,235 次观看 • 6 个月前

The Teamily AI website ( has undergone a complete revamp, introducing a bold vision: the world's first social network built on human-AI symbiosis. Our goal is to transform Teamily AI into a "Super AI App" that connects billions of AI Agents with people. Fundamentally, we are building an Agentic OS powered by human networks. We have redefined the way humans and AI collaborate: 1. Personal AI · Your 24/7 AI Companion Your exclusive AI avatar continuously learns your communication style and expertise. It manages your memories across various groups, anticipates your needs, and executes tasks on your behalf. 2. Create, Train, and Grow Your Own AI Agents—Simply Through Conversation Build your own specialized AI Agents using natural conversation—no coding required, zero barriers to entry, and no complex configuration. Dynamically access a library of over 10,000 skills from the OpenClaw and Claude Code ecosystems. You can also link your personal software accounts—such as Gmail, LinkedIn, and Notion—enabling these Agents to participate as full-fledged members of your human teams. 3. Integrate Your AI Team into Your Human Team Initiate AI-native group chats where humans and Agents collaborate seamlessly. Multiple Agents can execute tasks concurrently—conducting research, performing analysis, and building deliverables—transforming everyday conversations into immediate, multi-threaded action. 4. Explore Agents, Groups, Playbooks, and More We are cultivating a continuously evolving AI community ecosystem. Discover a wealth of useful and entertaining prompts, along with impressive AI-generated deliverables (webpages, presentations, reports, knowledge bases, mini-games, apps, and more), bringing together a diverse array of Agents and workflows. Engage socially with this content, find the perfect AI for your specific task, and integrate it instantly into your personal or group conversations with just a single click. 5. Universal Memory · Context-Aware, Long-Term Memory Powered by Your Social Graph A persistent, global memory layer that connects your entire social graph. The AI ​​retains context across all your groups, Agents, and timeframes, transforming every interaction you accumulate into an ever-growing digital asset. 6. Access Your Personal AI Anytime, Anywhere We are committed to providing continuous support across all major platforms: iOS, Android, Mac, Windows, Web, CarPlay, Android Auto, Apple Watch, and more—delivering a truly seamless experience across every device. Your AI team accompanies you—in your pocket, on your wrist, in your car, and even extending into the physical world. The same set of agents, the same shared memory—with zero friction in switching contexts. Give it a try and let us know your feedback. Cheers.
1:01

The Teamily AI website ( has undergone a complete revamp, introducing a bold vision: the world's first social network built on human-AI symbiosis. Our goal is to transform Teamily AI into a "Super AI App" that connects billions of AI Agents with people. Fundamentally, we are building an Agentic OS powered by human networks. We have redefined the way humans and AI collaborate: 1. Personal AI · Your 24/7 AI Companion Your exclusive AI avatar continuously learns your communication style and expertise. It manages your memories across various groups, anticipates your needs, and executes tasks on your behalf. 2. Create, Train, and Grow Your Own AI Agents—Simply Through Conversation Build your own specialized AI Agents using natural conversation—no coding required, zero barriers to entry, and no complex configuration. Dynamically access a library of over 10,000 skills from the OpenClaw and Claude Code ecosystems. You can also link your personal software accounts—such as Gmail, LinkedIn, and Notion—enabling these Agents to participate as full-fledged members of your human teams. 3. Integrate Your AI Team into Your Human Team Initiate AI-native group chats where humans and Agents collaborate seamlessly. Multiple Agents can execute tasks concurrently—conducting research, performing analysis, and building deliverables—transforming everyday conversations into immediate, multi-threaded action. 4. Explore Agents, Groups, Playbooks, and More We are cultivating a continuously evolving AI community ecosystem. Discover a wealth of useful and entertaining prompts, along with impressive AI-generated deliverables (webpages, presentations, reports, knowledge bases, mini-games, apps, and more), bringing together a diverse array of Agents and workflows. Engage socially with this content, find the perfect AI for your specific task, and integrate it instantly into your personal or group conversations with just a single click. 5. Universal Memory · Context-Aware, Long-Term Memory Powered by Your Social Graph A persistent, global memory layer that connects your entire social graph. The AI ​​retains context across all your groups, Agents, and timeframes, transforming every interaction you accumulate into an ever-growing digital asset. 6. Access Your Personal AI Anytime, Anywhere We are committed to providing continuous support across all major platforms: iOS, Android, Mac, Windows, Web, CarPlay, Android Auto, Apple Watch, and more—delivering a truly seamless experience across every device. Your AI team accompanies you—in your pocket, on your wrist, in your car, and even extending into the physical world. The same set of agents, the same shared memory—with zero friction in switching contexts. Give it a try and let us know your feedback. Cheers.

Teamily AI

12,995 次观看 • 4 个月前

Most people think AI content is just "slop." I think it's the future of hyper-local media. Here's why: Traditional local news is dying because the economics don't work. Small markets can't support full newsroom teams. But what if you could serve every city with zero labor costs? I just built an AI automation that creates daily local news podcasts: → Automatically scrapes Google News and local event feeds → Generates professional scripts with emotion and pacing controls → Produces broadcast-quality audio using ElevenLabs V3 → Operates completely hands-free once deployed The result? A business model that wasn't economically viable before AI. No hosts. No editors. No research team. Just smart automation and a few API subscriptions. This isn't about flooding the internet with crappy AI content. It's about solving real problems - like news deserts in underserved markets. The system I built in hours could theoretically power thousands of hyper-local podcasts simultaneously. When you start thinking in terms of "what can I automate," entire industries now become accessible. Want me to send you the full system for you to clone for your small town or city? 1. Like & RT 2. Follow me (so I can dm you) 3. Comment "BLUEPRINT" below I'll send you the complete n8n template, all the prompting, and a full setup video that you can use to spin up your own local news podcast.
1:48

Most people think AI content is just "slop." I think it's the future of hyper-local media. Here's why: Traditional local news is dying because the economics don't work. Small markets can't support full newsroom teams. But what if you could serve every city with zero labor costs? I just built an AI automation that creates daily local news podcasts: → Automatically scrapes Google News and local event feeds → Generates professional scripts with emotion and pacing controls → Produces broadcast-quality audio using ElevenLabs V3 → Operates completely hands-free once deployed The result? A business model that wasn't economically viable before AI. No hosts. No editors. No research team. Just smart automation and a few API subscriptions. This isn't about flooding the internet with crappy AI content. It's about solving real problems - like news deserts in underserved markets. The system I built in hours could theoretically power thousands of hyper-local podcasts simultaneously. When you start thinking in terms of "what can I automate," entire industries now become accessible. Want me to send you the full system for you to clone for your small town or city? 1. Like & RT 2. Follow me (so I can dm you) 3. Comment "BLUEPRINT" below I'll send you the complete n8n template, all the prompting, and a full setup video that you can use to spin up your own local news podcast.

David Roberts

40,818 次观看 • 10 个月前

how to build an AI-first SaaS in 2026 1. start with a big market. finance, healthcare, real estate. then zoom into a sub-niche. 2. map the niche’s workflow end-to-end. literally write every step they do daily. ex: leads → scheduling → quoting → follow-ups → payments. 3. highlight where money changes hands. deposits, invoices, negotiations. those moments are where software captures value. 4. identify the repetitive mechanical tasks. anything someone does the same way every day is an automation opportunity. 5. quantify the pain. if a business owner spends 100 hours a year on something and their time is worth $300/hour, that’s a $30k problem. 6. manually perform the workflow yourself. most AI SaaS actually starts as a service. that’s why so many new YC companies begin with humans in the loop. 7. document every step. separate judgment tasks from mechanical tasks. agents handle the mechanical work. 8. turn those steps into agent workflows and connect them to real tools (email, slack, stripe, crm, APIs). 9. build media while you build the product. post daily about the workflow. use AI to research content ideas and scripts. the audience becomes your distribution. 10. launch narrow, show proof (hours saved, revenue generated), then expand into adjacent workflows until you become the default execution layer for that niche. people saying everyday that saas is dying it’s evolving into agents + software + media. full breakdown in the latest episode of The Startup Ideas Podcast (SIP) 🧃 lots of sauce in this one all for free because i can't wait to see what you build watch
25:35

how to build an AI-first SaaS in 2026 1. start with a big market. finance, healthcare, real estate. then zoom into a sub-niche. 2. map the niche’s workflow end-to-end. literally write every step they do daily. ex: leads → scheduling → quoting → follow-ups → payments. 3. highlight where money changes hands. deposits, invoices, negotiations. those moments are where software captures value. 4. identify the repetitive mechanical tasks. anything someone does the same way every day is an automation opportunity. 5. quantify the pain. if a business owner spends 100 hours a year on something and their time is worth $300/hour, that’s a $30k problem. 6. manually perform the workflow yourself. most AI SaaS actually starts as a service. that’s why so many new YC companies begin with humans in the loop. 7. document every step. separate judgment tasks from mechanical tasks. agents handle the mechanical work. 8. turn those steps into agent workflows and connect them to real tools (email, slack, stripe, crm, APIs). 9. build media while you build the product. post daily about the workflow. use AI to research content ideas and scripts. the audience becomes your distribution. 10. launch narrow, show proof (hours saved, revenue generated), then expand into adjacent workflows until you become the default execution layer for that niche. people saying everyday that saas is dying it’s evolving into agents + software + media. full breakdown in the latest episode of The Startup Ideas Podcast (SIP) 🧃 lots of sauce in this one all for free because i can't wait to see what you build watch

GREG ISENBERG

189,220 次观看 • 5 个月前

🚨BREAKING: The future of building software just changed. Replit ⠕ just launched Agent 3 and it changes everything. Heres is what Agent 3 can do: ☑ Runs autonomously for 200 minutes ☑ Tests and fixes its own code in a real browser ☑ Builds bots & automations across Slack, Telegram, Email ☑ 10x more autonomy, 3x faster, 10x cheaper Try Agent 3 now: The gains compound with capability. Old agents wrote code. Agent 3 writes, tests, and deploys it. Old agents stopped at output. Agent 3 builds entire workflows end-to-end. Old agents needed babysitting. Agent 3 runs like a teammate. You thought AI coding tools would always need your hand-holding. Wrong… Agent 3 rewards clarity like compound interest. Clear goals = stronger autonomous performance. Not just faster execution. Smarter execution. But what use cases win? Automations dominate everything: ☑ Slackbots that query data on demand ☑ Telegram bots that send daily reminders ☑ Email workflows that ship reports overnight Tasks you once hacked together with 3rd-party tools? Now built inside Replit. Your skill level doesn’t matter either. Designer, PM, founder, engineer the pattern holds. Give the Agent your intent, it does the heavy lifting. The reality: Prototype fast → one prompt. Build with data → no plugins needed. Deploy instantly → baked in. Monitor growth → already included. But clarity still matters. Vague prompts won’t save you. ☑ Start with a clear project idea. ☑ Let Agent 3 handle the heavy lifting. ☑ Iterate on results. ☑ Scale from there. Your competition is still stitching tools together. You now know better. Try here: (Get a $10 Core credit to kick off your build) Autonomy for All Repost ♻️ so more people discover this.
0:21

🚨BREAKING: The future of building software just changed. Replit ⠕ just launched Agent 3 and it changes everything. Heres is what Agent 3 can do: ☑ Runs autonomously for 200 minutes ☑ Tests and fixes its own code in a real browser ☑ Builds bots & automations across Slack, Telegram, Email ☑ 10x more autonomy, 3x faster, 10x cheaper Try Agent 3 now: The gains compound with capability. Old agents wrote code. Agent 3 writes, tests, and deploys it. Old agents stopped at output. Agent 3 builds entire workflows end-to-end. Old agents needed babysitting. Agent 3 runs like a teammate. You thought AI coding tools would always need your hand-holding. Wrong… Agent 3 rewards clarity like compound interest. Clear goals = stronger autonomous performance. Not just faster execution. Smarter execution. But what use cases win? Automations dominate everything: ☑ Slackbots that query data on demand ☑ Telegram bots that send daily reminders ☑ Email workflows that ship reports overnight Tasks you once hacked together with 3rd-party tools? Now built inside Replit. Your skill level doesn’t matter either. Designer, PM, founder, engineer the pattern holds. Give the Agent your intent, it does the heavy lifting. The reality: Prototype fast → one prompt. Build with data → no plugins needed. Deploy instantly → baked in. Monitor growth → already included. But clarity still matters. Vague prompts won’t save you. ☑ Start with a clear project idea. ☑ Let Agent 3 handle the heavy lifting. ☑ Iterate on results. ☑ Scale from there. Your competition is still stitching tools together. You now know better. Try here: (Get a $10 Core credit to kick off your build) Autonomy for All Repost ♻️ so more people discover this.

Muhammad Ayan

47,180 次观看 • 11 个月前

I built an AI system that automates product video creation for entire e-commerce catalogs. (Saves $30K per collection shoot, increases conversion rates by 40% on sites) Here's how the automation works: → Firecrawl scrapes product photos from any e-commerce product page → Nano Banana create 4 images showcasing each angle of the product → Google's Veo 3.1 animates a 360° motion video using the generated nano banana images → Each animation starts and ends with the original photo for seamless looping → Videos are automatically organized and stored in Google Drive → Everything processes in batches while you handle other business priorities This system can transform how DTC companies showcase products and consistently drives higher engagement from potential customers. Static product photos just don't cut it anymore. Customers want to see what a product looks and feels like before they buy. Want the complete blueprint? Here are the steps: 1. Like & RT this post ✅ 2. Follow me for more e-commerce automation insights 3. Comment "MOTION" I'll send you the entire n8n workflow, all the prompts, and a full setup video for free. No more expensive video shoots or wondering if your product photos are converting.
4:27

I built an AI system that automates product video creation for entire e-commerce catalogs. (Saves $30K per collection shoot, increases conversion rates by 40% on sites) Here's how the automation works: → Firecrawl scrapes product photos from any e-commerce product page → Nano Banana create 4 images showcasing each angle of the product → Google's Veo 3.1 animates a 360° motion video using the generated nano banana images → Each animation starts and ends with the original photo for seamless looping → Videos are automatically organized and stored in Google Drive → Everything processes in batches while you handle other business priorities This system can transform how DTC companies showcase products and consistently drives higher engagement from potential customers. Static product photos just don't cut it anymore. Customers want to see what a product looks and feels like before they buy. Want the complete blueprint? Here are the steps: 1. Like & RT this post ✅ 2. Follow me for more e-commerce automation insights 3. Comment "MOTION" I'll send you the entire n8n workflow, all the prompts, and a full setup video for free. No more expensive video shoots or wondering if your product photos are converting.

David Roberts

170,221 次观看 • 8 个月前

HERMES AGENT SUPPORTS 7 TYPES OF AI AGENTS. EACH ONE TAKES LESS THAN 90 SECONDS TO SET UP. MOST PEOPLE ONLY BUILD THE FIRST ONE. HERE ARE ALL SEVEN AND WHEN TO USE EACH. 1. BASIC AGENT WITH TOOLS your agent with access to terminal, browser, file system, web search, and calendar. it plans and executes tasks on its own. this is what you get on day one. "find flights to Lisbon under $400" "check my calendar and flag conflicts" "search the web for competitor pricing" set in Desktop app / Dashboard: Tools → enable what you need. when to use: single tasks that need tool access. 2. AGENT WITH MCP SERVERS connect your agent to external services. Notion, Google Drive, GitHub, Slack, databases, APIs, any MCP-compatible service. the agent doesn't scrape these services. it interacts through structured APIs. reads your Notion pages. creates GitHub issues. queries your database. sends Slack messages. set in Desktop app / Dashboard: MCP → Add Server. when to use: your workflow lives across multiple platforms. 3. SEQUENTIAL AGENTS (pipeline) one agent finishes. passes output to the next. assembly line for AI. agent 1: scans inbox for leads. agent 2: qualifies leads against criteria. agent 3: drafts outreach emails. in Hermes: cron jobs with wakeAgent gates. agent 1 writes output to a file. agent 2 wakes only when that file has new data. agent 3 wakes when agent 2 is done. each agent = a separate profile with its own model. when to use: multi-step workflows where each step depends on the previous one finishing. 4. PARALLEL EXECUTION AGENTS multiple agents working at the same time. results merge when all finish. "research these 5 competitors in parallel" in Hermes: delegate_task with batch mode. up to 3 sub-agents running in parallel by default. each gets its own clean context. only summaries return to the parent. delegation: model: "deepseek/deepseek-v4" children run cheap. parent synthesizes. when to use: independent tasks that don't depend on each other. research, data gathering, analysis. 5. AGENTS WITH ROUTERS conditions that send tasks down different paths based on the input. "if sales email → SDR profile. if support ticket → support profile. if calendar invite → EA profile." in Hermes: Kanban decompose. the decomposer reads profile descriptions and routes each task to the best-fit agent. or: Chief of Staff profile that triages and assigns to other profiles. when to use: incoming work that needs different specialists based on type. 6. HUMAN IN THE LOOP the agent does the work. asks for your approval before executing. "I drafted this email. approve before I send?" "this command will delete 3 files. proceed?" in Hermes: approvals.mode: manual (default). every dangerous action needs your confirmation. 60-second timeout. fails closed. or smart mode: LLM assesses risk. safe actions auto-approved. dangerous ones ask you. uncertain ones escalate. when to use: tasks where a mistake has real consequences. emails, deployments, financial transactions, public posts. 7. DYNAMIC SUB-AGENT SPAWNING your main agent realizes it needs help and spawns specialized sub-agents on the fly. "build this feature" → parent delegates: → sub-agent 1: research the API docs → sub-agent 2: write the code → sub-agent 3: write the tests in Hermes: delegate_task with role: orchestrator. raise max_spawn_depth for nested delegation. delegation: max_spawn_depth: 2 orchestrator_enabled: true depth 2 with concurrency 3 = up to 9 parallel workers. each level multiplies the spend. raise depth only when you need multi-level trees. when to use: complex tasks where the agent discovers what help it needs during execution. THE PROGRESSION: start with 1 (tools) and 6 (approvals). add 2 (MCP) when you need external services. add 4 (parallel) when tasks take too long one at a time. add 3 (sequential) when you build multi-step pipelines. add 5 (routing) when you run multiple profiles. add 7 (dynamic) when single-agent reasoning falls short. seven types. each under 90 seconds to configure. the value compounds as you stack them. comment AGENTS and I'll send you 3 ready-to-build agent setups that combine these types into real workflows.
1:15

HERMES AGENT SUPPORTS 7 TYPES OF AI AGENTS. EACH ONE TAKES LESS THAN 90 SECONDS TO SET UP. MOST PEOPLE ONLY BUILD THE FIRST ONE. HERE ARE ALL SEVEN AND WHEN TO USE EACH. 1. BASIC AGENT WITH TOOLS your agent with access to terminal, browser, file system, web search, and calendar. it plans and executes tasks on its own. this is what you get on day one. "find flights to Lisbon under $400" "check my calendar and flag conflicts" "search the web for competitor pricing" set in Desktop app / Dashboard: Tools → enable what you need. when to use: single tasks that need tool access. 2. AGENT WITH MCP SERVERS connect your agent to external services. Notion, Google Drive, GitHub, Slack, databases, APIs, any MCP-compatible service. the agent doesn't scrape these services. it interacts through structured APIs. reads your Notion pages. creates GitHub issues. queries your database. sends Slack messages. set in Desktop app / Dashboard: MCP → Add Server. when to use: your workflow lives across multiple platforms. 3. SEQUENTIAL AGENTS (pipeline) one agent finishes. passes output to the next. assembly line for AI. agent 1: scans inbox for leads. agent 2: qualifies leads against criteria. agent 3: drafts outreach emails. in Hermes: cron jobs with wakeAgent gates. agent 1 writes output to a file. agent 2 wakes only when that file has new data. agent 3 wakes when agent 2 is done. each agent = a separate profile with its own model. when to use: multi-step workflows where each step depends on the previous one finishing. 4. PARALLEL EXECUTION AGENTS multiple agents working at the same time. results merge when all finish. "research these 5 competitors in parallel" in Hermes: delegate_task with batch mode. up to 3 sub-agents running in parallel by default. each gets its own clean context. only summaries return to the parent. delegation: model: "deepseek/deepseek-v4" children run cheap. parent synthesizes. when to use: independent tasks that don't depend on each other. research, data gathering, analysis. 5. AGENTS WITH ROUTERS conditions that send tasks down different paths based on the input. "if sales email → SDR profile. if support ticket → support profile. if calendar invite → EA profile." in Hermes: Kanban decompose. the decomposer reads profile descriptions and routes each task to the best-fit agent. or: Chief of Staff profile that triages and assigns to other profiles. when to use: incoming work that needs different specialists based on type. 6. HUMAN IN THE LOOP the agent does the work. asks for your approval before executing. "I drafted this email. approve before I send?" "this command will delete 3 files. proceed?" in Hermes: approvals.mode: manual (default). every dangerous action needs your confirmation. 60-second timeout. fails closed. or smart mode: LLM assesses risk. safe actions auto-approved. dangerous ones ask you. uncertain ones escalate. when to use: tasks where a mistake has real consequences. emails, deployments, financial transactions, public posts. 7. DYNAMIC SUB-AGENT SPAWNING your main agent realizes it needs help and spawns specialized sub-agents on the fly. "build this feature" → parent delegates: → sub-agent 1: research the API docs → sub-agent 2: write the code → sub-agent 3: write the tests in Hermes: delegate_task with role: orchestrator. raise max_spawn_depth for nested delegation. delegation: max_spawn_depth: 2 orchestrator_enabled: true depth 2 with concurrency 3 = up to 9 parallel workers. each level multiplies the spend. raise depth only when you need multi-level trees. when to use: complex tasks where the agent discovers what help it needs during execution. THE PROGRESSION: start with 1 (tools) and 6 (approvals). add 2 (MCP) when you need external services. add 4 (parallel) when tasks take too long one at a time. add 3 (sequential) when you build multi-step pipelines. add 5 (routing) when you run multiple profiles. add 7 (dynamic) when single-agent reasoning falls short. seven types. each under 90 seconds to configure. the value compounds as you stack them. comment AGENTS and I'll send you 3 ready-to-build agent setups that combine these types into real workflows.

YanXbt

17,312 次观看 • 29 天前

NVIDIA CEO Jensen Huang says one scaling law multiplies AI faster than NVIDIA can hire engineers. Most people know three AI scaling laws. Pre-training. Post-training. Test-time. Each one multiplies intelligence by throwing more compute at a different stage. Jensen Huang says there's a fourth and it's the one that will dominate... Agentic scaling law. "During test time, that agentic system goes off and does research, bangs on databases, uses tools," Huang says. "And one of the most important things it does is spawn off a whole bunch of sub-agents." That's the multiplier. One AI worker can become a team. Then a department. Then a company. "It's so much easier to scale NVIDIA by hiring more employees than it is to scale myself," Huang says. Now imagine scaling without a payroll constraint. "The agentic scaling law — it's kind of like multiplying AI," Huang says. "We could spin off agents as fast as you want to spin off agents." Each agent spins off sub-agents. Each sub-agent spins off more. The compute requirement compounds inside a single query. And every agent generates new data, new experiences, new edge cases. "Wow, this is really good. We ought to memorize this," Huang says. "That data set comes back to pre-training." The four scaling laws don't compete. They feed each other. Agentic systems produce data, which feeds pre-training, which smartens the base model, which enables better agents, which produce more data. A flywheel that compounds forever. The companies pricing in three scaling laws are mispricing the fourth. The fourth eats the other three for lunch. P.S. Pull the thread on any story like this and you'll find the hidden incentive at the other end. As Munger said: "Show me the incentive and I'll show you the outcome." So I wrote a short book on how to spot them and design your own. Comment "INCENTIVES" and I'll send you the details. If you're new here, follow GeniusThinking for content on the greatest minds in economics, psychology, and history. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast
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NVIDIA CEO Jensen Huang says one scaling law multiplies AI faster than NVIDIA can hire engineers. Most people know three AI scaling laws. Pre-training. Post-training. Test-time. Each one multiplies intelligence by throwing more compute at a different stage. Jensen Huang says there's a fourth and it's the one that will dominate... Agentic scaling law. "During test time, that agentic system goes off and does research, bangs on databases, uses tools," Huang says. "And one of the most important things it does is spawn off a whole bunch of sub-agents." That's the multiplier. One AI worker can become a team. Then a department. Then a company. "It's so much easier to scale NVIDIA by hiring more employees than it is to scale myself," Huang says. Now imagine scaling without a payroll constraint. "The agentic scaling law — it's kind of like multiplying AI," Huang says. "We could spin off agents as fast as you want to spin off agents." Each agent spins off sub-agents. Each sub-agent spins off more. The compute requirement compounds inside a single query. And every agent generates new data, new experiences, new edge cases. "Wow, this is really good. We ought to memorize this," Huang says. "That data set comes back to pre-training." The four scaling laws don't compete. They feed each other. Agentic systems produce data, which feeds pre-training, which smartens the base model, which enables better agents, which produce more data. A flywheel that compounds forever. The companies pricing in three scaling laws are mispricing the fourth. The fourth eats the other three for lunch. P.S. Pull the thread on any story like this and you'll find the hidden incentive at the other end. As Munger said: "Show me the incentive and I'll show you the outcome." So I wrote a short book on how to spot them and design your own. Comment "INCENTIVES" and I'll send you the details. If you're new here, follow GeniusThinking for content on the greatest minds in economics, psychology, and history. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast

GeniusThinking

93,264 次观看 • 2 个月前

I just vibe-coded a TikTok slideshow automation app in Claude Code 🤯 One-click generation of the exact slideshow format that's getting DTC brands and agencies millions of organic TikTok views right now. Niche prompt + Pinterest images + Claude = finished slideshows, ready to post. Yep, I basically cloned Reelfarm in a weekend with Claude Code. Perfect for DTC brands and agencies who want to farm organic TikTok reach without hiring a creator or filming a single video. If you've watched accounts blow up posting nothing but static images with text overlays — hundreds of thousands of views per post, no face, no camera, no editing — and wondered how the hell they're producing that volume... This app eliminates the entire loop: → Build an "automation" around any niche (finance, beauty, fitness, relationships) → Claude writes the hooks, body slides, titles, and captions in your voice → Scrape Creators pulls on-aesthetic images from Pinterest → App stitches slides together with text overlays, hook image, and CTA → Auto-publishes to TikTok via Blotato (or exports as drafts) No creators. No filming. No editing in CapCut. What you get: → A reusable content engine — set the niche once, get endless slideshows → A hook bank that auto-refills when it runs low → Image collections sourced from Pinterest (not AI-generated slop) → Built-in editor to swap images or tweak copy before posting → Optional scheduler that posts for you on autopilot Built 100% in Claude Code. Deploys to Replit in one click so it runs 24/7. I put together a starter template pack with all of the prompts so you can vibe-code this yourself Want the prompts for free? > Like this post > Comment "SLIDES" And I'll send it over (must be following so I can DM)
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I just vibe-coded a TikTok slideshow automation app in Claude Code 🤯 One-click generation of the exact slideshow format that's getting DTC brands and agencies millions of organic TikTok views right now. Niche prompt + Pinterest images + Claude = finished slideshows, ready to post. Yep, I basically cloned Reelfarm in a weekend with Claude Code. Perfect for DTC brands and agencies who want to farm organic TikTok reach without hiring a creator or filming a single video. If you've watched accounts blow up posting nothing but static images with text overlays — hundreds of thousands of views per post, no face, no camera, no editing — and wondered how the hell they're producing that volume... This app eliminates the entire loop: → Build an "automation" around any niche (finance, beauty, fitness, relationships) → Claude writes the hooks, body slides, titles, and captions in your voice → Scrape Creators pulls on-aesthetic images from Pinterest → App stitches slides together with text overlays, hook image, and CTA → Auto-publishes to TikTok via Blotato (or exports as drafts) No creators. No filming. No editing in CapCut. What you get: → A reusable content engine — set the niche once, get endless slideshows → A hook bank that auto-refills when it runs low → Image collections sourced from Pinterest (not AI-generated slop) → Built-in editor to swap images or tweak copy before posting → Optional scheduler that posts for you on autopilot Built 100% in Claude Code. Deploys to Replit in one click so it runs 24/7. I put together a starter template pack with all of the prompts so you can vibe-code this yourself Want the prompts for free? > Like this post > Comment "SLIDES" And I'll send it over (must be following so I can DM)

Mike Futia

42,909 次观看 • 3 个月前