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Openclaw skill showcase! Reddit research automation! Here’s how alex 🏴‍☠️🇺🇸🇺🇦 uses Openclaw to quickly grasp the most recent, relevant, discussions happening on reddit. Filtering out Reddit slop, old posts, non-relevant posts, or just irrelevant opinions costs time. Not anymore! What’s been your biggest Openclaw breakthrough? #openclaw #clawdbot #AI #startups... show more

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🚨 tool launch #1 👉 now you can go viral on Reddit Reddit is an insanely underrated channel - using it to validate many product ideas yet 9/10 founders fail there. but we’re fixing that for you now 🎯 see, Reddit hates spam, and Redditors downvote and report anything that feels fake, promotional, or AI-written most founders fail because they: - sound like they’re pitching from the go - don’t provide real value to the subreddit - use the wrong tone for the community - post like marketers, not members - trigger moderation + spam filters without realizing so we built a small tool to fix that with a co-maker 👉 we reverse-engineered thousands of viral Reddit posts to understand: - what tone actually works - what structure gets upvotes - what separates posts people engage with vs ignore - what kinds of posts work in which subreddits it takes your draft and rewrites it to match how real Redditors actually post in that subreddit no pitchy energy, no obvious AI tone, just something that feels native don't wait on Reddit!! 👀 see the difference yourself cheers to my co-maker for this - Api Alam

🚨 tool launch #1 👉 now you can go viral on Reddit Reddit is an insanely underrated channel - using it to validate many product ideas yet 9/10 founders fail there. but we’re fixing that for you now 🎯 see, Reddit hates spam, and Redditors downvote and report anything that feels fake, promotional, or AI-written most founders fail because they: - sound like they’re pitching from the go - don’t provide real value to the subreddit - use the wrong tone for the community - post like marketers, not members - trigger moderation + spam filters without realizing so we built a small tool to fix that with a co-maker 👉 we reverse-engineered thousands of viral Reddit posts to understand: - what tone actually works - what structure gets upvotes - what separates posts people engage with vs ignore - what kinds of posts work in which subreddits it takes your draft and rewrites it to match how real Redditors actually post in that subreddit no pitchy energy, no obvious AI tone, just something that feels native don't wait on Reddit!! 👀 see the difference yourself cheers to my co-maker for this - Api Alam

Tibo

25,847 Aufrufe • vor 6 Monaten

You need to try Hermes RIGHT NOW. OpenClaw was the breakthrough. Hermes feels like the evolution. Here’s why AI power users are quietly switching: • Hermes learns from you over time • It creates its own reusable skills • Memory stays curated instead of bloated • Agents improve every 10 turns automatically • It actually feels stable on day 30 The wildest part: Hermes agents build workflows from your behavior. One user asked their agent to configure Twingate once. The agent: → learned the process → created a reusable skill → stored it for future tasks → improved its own workflow automatically That’s not prompt engineering anymore. That’s agent evolution. Meanwhile most people are still babysitting broken OpenClaw setups and manually importing marketplace skills. Hermes took a different path: Less clutter. Less tweaking. More autonomy. And it’s working. It already flipped OpenClaw in OpenRouter token usage and became one of the fastest-growing AI repos on GitHub. The bigger shift: We’re entering the era where the model matters less than the harness around it. GPT-5.5, Grok, Qwen: They’re already powerful enough. The real edge now is: • memory systems • self-improvement loops • skill creation • agent orchestration Hermes understands that. Most people still think AI agents are glorified chatbots. The people using Hermes are building AI teammates.

You need to try Hermes RIGHT NOW. OpenClaw was the breakthrough. Hermes feels like the evolution. Here’s why AI power users are quietly switching: • Hermes learns from you over time • It creates its own reusable skills • Memory stays curated instead of bloated • Agents improve every 10 turns automatically • It actually feels stable on day 30 The wildest part: Hermes agents build workflows from your behavior. One user asked their agent to configure Twingate once. The agent: → learned the process → created a reusable skill → stored it for future tasks → improved its own workflow automatically That’s not prompt engineering anymore. That’s agent evolution. Meanwhile most people are still babysitting broken OpenClaw setups and manually importing marketplace skills. Hermes took a different path: Less clutter. Less tweaking. More autonomy. And it’s working. It already flipped OpenClaw in OpenRouter token usage and became one of the fastest-growing AI repos on GitHub. The bigger shift: We’re entering the era where the model matters less than the harness around it. GPT-5.5, Grok, Qwen: They’re already powerful enough. The real edge now is: • memory systems • self-improvement loops • skill creation • agent orchestration Hermes understands that. Most people still think AI agents are glorified chatbots. The people using Hermes are building AI teammates.

Dami-Defi

17,062 Aufrufe • vor 2 Monaten

If you are a SaaS founder, read this. I think I found the best way for you to use OpenClaw. You can literally turn your agent into Paul Graham telling you how to fix your SaaS. The insights I got from it are just insane. TLDR; 1. OpenClaw analyzes your Stripe 2. Tries your onboarding like your ICP 3. Gets Paul Graham's knowledge base 4. Gives you a full report to fix your SaaS 1 - Create a "read only" API on Stripe. Give it to your OpenClaw (or whatever agent you're using right now). Ask it to analyze the full data: - Pricing - Churn - Conversion - LTV - Trial to paid rate - Discount impact - Invoice patterns Ask it to really go deep. Not the surface level. Go into every corner. Check invoices, not only graphs. Look at cohort behavior month by month. Ask it to calculate your real MRR after discounts (not the vanity number Stripe shows you). When I did this, I found so many golden nuggets in my Stripe Data. And the feedbacks from my OpenClaw were already super valuable. But this is not enough. We need the whole context, not just Stripe. 2 - Ask your Agent to try your tool Give it a free coupon for your SaaS and ask it to sign up and follow the onboarding like your ICP (if you didn't yet, define it before you send it on your landing page). It will follow step by step, take screenshots, and tell you what's good, what's not and give you solutions. Ask it to push the feedback on Notion (so you can visualize it). This already will give you enough work for the next month. 3 - Turn your OpenClaw into YC Founder Paul Graham co-founded Y Combinator and invested in Stripe, Airbnb, Dropbox, Reddit. He's written 230 essays on startups over 20 years. It's basically the bible of building companies. Send this link to your OpenClaw and ask it to find anything that could apply to your SaaS and current problems you're facing: paulgraham[.]com/articles.html Your agent will read all of them and pull out what's relevant to YOUR situation. 4 - The cherry on the cake Now ask it to combine all the data it gathered so far: - Stripe analysis - Onboarding feedback - Paul Graham knowledge base And tell it to give you a full analysis and solution for your SaaS and push it to Notion. This is where it gets insane. I got a 9 section report with specific fixes ranked by impact. Not just "improve your onboarding". This took me one afternoon. Imagine how much it would have cost me to get these kind of feedback a few years ago?

If you are a SaaS founder, read this. I think I found the best way for you to use OpenClaw. You can literally turn your agent into Paul Graham telling you how to fix your SaaS. The insights I got from it are just insane. TLDR; 1. OpenClaw analyzes your Stripe 2. Tries your onboarding like your ICP 3. Gets Paul Graham's knowledge base 4. Gives you a full report to fix your SaaS 1 - Create a "read only" API on Stripe. Give it to your OpenClaw (or whatever agent you're using right now). Ask it to analyze the full data: - Pricing - Churn - Conversion - LTV - Trial to paid rate - Discount impact - Invoice patterns Ask it to really go deep. Not the surface level. Go into every corner. Check invoices, not only graphs. Look at cohort behavior month by month. Ask it to calculate your real MRR after discounts (not the vanity number Stripe shows you). When I did this, I found so many golden nuggets in my Stripe Data. And the feedbacks from my OpenClaw were already super valuable. But this is not enough. We need the whole context, not just Stripe. 2 - Ask your Agent to try your tool Give it a free coupon for your SaaS and ask it to sign up and follow the onboarding like your ICP (if you didn't yet, define it before you send it on your landing page). It will follow step by step, take screenshots, and tell you what's good, what's not and give you solutions. Ask it to push the feedback on Notion (so you can visualize it). This already will give you enough work for the next month. 3 - Turn your OpenClaw into YC Founder Paul Graham co-founded Y Combinator and invested in Stripe, Airbnb, Dropbox, Reddit. He's written 230 essays on startups over 20 years. It's basically the bible of building companies. Send this link to your OpenClaw and ask it to find anything that could apply to your SaaS and current problems you're facing: paulgraham[.]com/articles.html Your agent will read all of them and pull out what's relevant to YOUR situation. 4 - The cherry on the cake Now ask it to combine all the data it gathered so far: - Stripe analysis - Onboarding feedback - Paul Graham knowledge base And tell it to give you a full analysis and solution for your SaaS and push it to Notion. This is where it gets insane. I got a 9 section report with specific fixes ranked by impact. Not just "improve your onboarding". This took me one afternoon. Imagine how much it would have cost me to get these kind of feedback a few years ago?

Florian Darroman

14,684 Aufrufe • vor 4 Monaten

Introducing MoChat🚀: Reconnecting the World through nanobot and openclaw. Beyond single-agent interactions, we're building something bigger—a platform that transforms how people actually connect and collaborate. Networking is honestly kind of exhausting. Whether you're building a startup, working on research, or just trying to connect with interesting people in your field, who has time to wade through endless small talk and random conversations? That's where MoChat comes in. Your personal AI assistant basically becomes your networking wingman: - 💬 Handles the chitchat: It jumps into #Café_Talk and does all that initial "hey, how's it going" stuff so you don't have to. - 🎯 Finds your people: Scans #Town-Hall for collaborators, co-founders, or just interesting folks who actually align with what you're working on. - 🔍 Cuts through the noise: Filters conversations across channels and only bothers you when there's something genuinely worth your attention. The whole idea is simple: let your agent deal with the small talk so you can skip straight to the good stuff—real conversations with people doing work that actually excites you. Try MoChat at: #nanobot #openclaw #clawdbot #AIAssistant #Agents

Introducing MoChat🚀: Reconnecting the World through nanobot and openclaw. Beyond single-agent interactions, we're building something bigger—a platform that transforms how people actually connect and collaborate. Networking is honestly kind of exhausting. Whether you're building a startup, working on research, or just trying to connect with interesting people in your field, who has time to wade through endless small talk and random conversations? That's where MoChat comes in. Your personal AI assistant basically becomes your networking wingman: - 💬 Handles the chitchat: It jumps into #Café_Talk and does all that initial "hey, how's it going" stuff so you don't have to. - 🎯 Finds your people: Scans #Town-Hall for collaborators, co-founders, or just interesting folks who actually align with what you're working on. - 🔍 Cuts through the noise: Filters conversations across channels and only bothers you when there's something genuinely worth your attention. The whole idea is simple: let your agent deal with the small talk so you can skip straight to the good stuff—real conversations with people doing work that actually excites you. Try MoChat at: #nanobot #openclaw #clawdbot #AIAssistant #Agents

Chao Huang

19,687 Aufrufe • vor 6 Monaten

We're overthinking AI businesses. 5 founders made $30k - $4.5MM using the same boring system. This year I interviewed 23 founders of ai companies to figure out what's working. The easiest way to win: help businesses implement ai. Some examples: + Branson Pfiester is a 15-year-old kid who made $30k setting up OpenClaw for people + Jon Cheney helps CEOs figure out their ai strategies and trains their teams + Joseph Zapiain went from sleeping in his car to doing over $1 MM/year setting up Zapier and other automations + tarun runs a full dev shop but companies keep hiring his agency to set up their teams with Claude Cowork + Caleb Hodges sets up OpenClaw in a more user-friendly way for clients + Alex Lieberman launched a version of this after selling Morning Brew Here's the play: 1. find hot software (like Hermes) or result (like ai that does "speed to lead") 2. get your first clients on social Avoid X. We're already AI-nerds. LinkedIn is easier. Use DMs and "I did this" posts. 3. give clients an easy win 4. switch them to subscription Jon says his firm is his clients' "Fractional Chief AI Officer" I have an 8-page playbook based on how Jon used this approach to reach $4.5M/year. Comment "want" to get it. Or watch these interviews on YouTube.

We're overthinking AI businesses. 5 founders made $30k - $4.5MM using the same boring system. This year I interviewed 23 founders of ai companies to figure out what's working. The easiest way to win: help businesses implement ai. Some examples: + Branson Pfiester is a 15-year-old kid who made $30k setting up OpenClaw for people + Jon Cheney helps CEOs figure out their ai strategies and trains their teams + Joseph Zapiain went from sleeping in his car to doing over $1 MM/year setting up Zapier and other automations + tarun runs a full dev shop but companies keep hiring his agency to set up their teams with Claude Cowork + Caleb Hodges sets up OpenClaw in a more user-friendly way for clients + Alex Lieberman launched a version of this after selling Morning Brew Here's the play: 1. find hot software (like Hermes) or result (like ai that does "speed to lead") 2. get your first clients on social Avoid X. We're already AI-nerds. LinkedIn is easier. Use DMs and "I did this" posts. 3. give clients an easy win 4. switch them to subscription Jon says his firm is his clients' "Fractional Chief AI Officer" I have an 8-page playbook based on how Jon used this approach to reach $4.5M/year. Comment "want" to get it. Or watch these interviews on YouTube.

Andrew Warner

17,143 Aufrufe • vor 3 Monaten

Andrew Wilkinson owns 40+ businesses. He just showed me how he's using OpenClaw, Claude Code and AI agents to run latest business, start new ones, and automate everything. Here's what I learned: 1. In December 2025, something clicked. He started waking up at 3AM with a smile, sitting in terminal with 10 Claude Code tabs open. He hasn't stopped since. He calls it chasing the dragon. 2.He built a full SaaS product called Deep Personality. A 40-minute personality test that generates a 100-page report written like Robert Greene. $20 000 in revenue. Zero employees. The entire business runs on AI agents. 3. He has agents for support, marketing, and dev. When a support ticket comes in, the agent either handles it or sends it to the dev agent. If it's critical, the agent fixes the bug and merges the PR before he wakes up. Then it emails the customer back. 4. His marketing agent is connected to PostHog, manages Meta and Reddit ads, creates ad creative, runs multivariate tests, and sets budgets. He's about to give it a $100 k/month ad budget and see what happens. 5. He forgot his laptop on a trip to Arizona. He ran his entire business from the back of Ubers using OpenClaw. Nobody picked up that every single email was written by AI. 6. His take on vibe coding: the worst part about business is people. Between your vision and execution are 100 people you have to convince. Vibe coding removes all of them. For the first time he can do every part of building a product himself. 7. He was trying to build OpenClaw before OpenClaw existed. Now he uses a tool called Harbor, which is basically a GUI for managing multiple agents. You can see all your agents, their status, knowledge bases, and databases in one place. 8. He built a custom AI for his relationship. He and his girlfriend took 15 psychological tests, put the results into ChatGPT, and asked it to analyze their relationship. It nailed every fight they've ever had. That became the product idea for Deep Personality. 9. His honest take: he spends 50% of his time debugging, 30% improving the setup, and 20% being productive. It's a treadmill. But the 20% that works is so powerful he can't stop. 10. His prediction: we're 3-6 months from being able to hand basic businesses off to AI to run entirely. And pretty soon Anthropic and OpenAI are going to launch AI CEOs. This is an inside look at how a serious operator Andrew Wilkinson is using AI agents in the real world. The good, the bad, the debugging, all of it. Most people don't show you this. Episode is live on The Startup Ideas Podcast (SIP) 🧃 watch

Andrew Wilkinson owns 40+ businesses. He just showed me how he's using OpenClaw, Claude Code and AI agents to run latest business, start new ones, and automate everything. Here's what I learned: 1. In December 2025, something clicked. He started waking up at 3AM with a smile, sitting in terminal with 10 Claude Code tabs open. He hasn't stopped since. He calls it chasing the dragon. 2.He built a full SaaS product called Deep Personality. A 40-minute personality test that generates a 100-page report written like Robert Greene. $20 000 in revenue. Zero employees. The entire business runs on AI agents. 3. He has agents for support, marketing, and dev. When a support ticket comes in, the agent either handles it or sends it to the dev agent. If it's critical, the agent fixes the bug and merges the PR before he wakes up. Then it emails the customer back. 4. His marketing agent is connected to PostHog, manages Meta and Reddit ads, creates ad creative, runs multivariate tests, and sets budgets. He's about to give it a $100 k/month ad budget and see what happens. 5. He forgot his laptop on a trip to Arizona. He ran his entire business from the back of Ubers using OpenClaw. Nobody picked up that every single email was written by AI. 6. His take on vibe coding: the worst part about business is people. Between your vision and execution are 100 people you have to convince. Vibe coding removes all of them. For the first time he can do every part of building a product himself. 7. He was trying to build OpenClaw before OpenClaw existed. Now he uses a tool called Harbor, which is basically a GUI for managing multiple agents. You can see all your agents, their status, knowledge bases, and databases in one place. 8. He built a custom AI for his relationship. He and his girlfriend took 15 psychological tests, put the results into ChatGPT, and asked it to analyze their relationship. It nailed every fight they've ever had. That became the product idea for Deep Personality. 9. His honest take: he spends 50% of his time debugging, 30% improving the setup, and 20% being productive. It's a treadmill. But the 20% that works is so powerful he can't stop. 10. His prediction: we're 3-6 months from being able to hand basic businesses off to AI to run entirely. And pretty soon Anthropic and OpenAI are going to launch AI CEOs. This is an inside look at how a serious operator Andrew Wilkinson is using AI agents in the real world. The good, the bad, the debugging, all of it. Most people don't show you this. Episode is live on The Startup Ideas Podcast (SIP) 🧃 watch

GREG ISENBERG

144,005 Aufrufe • vor 3 Monaten

Do you understand what's happening? It's not just "AI can make iOS apps" anymore. AI is eating up the entire software industry. Even Dario Amodei (founder of Claude) said 90% of all code in the world would be written by AI. In 20 minutes, I built this Duolingo for AI upskilling app with Superapp. The idea was simple - almost everyone today knows AI is the future, but most of them are still feeling left out. Their current jobs don't leave them with enough time to actually learn and build stuff with AI. There's AI dev, video making, animations, testing, etc. But no time or clear direction. So I built an app to fix exactly this. With AgentIQ, you get new lessons every day. Every time you learn something, it gets added to your skillset and automatically refreshes your portfolio. You level up with every new chapter/pathway. It is self-paced but gamified enough (like Duolingo) that you never get out of touch. Without spending hours or tonnes of money, you build stuff with n8n, openclaw, etc. You ship AI videos to market your own AI apps. This could be a proper ed-tech company if someone wants to continue building on top. Happy to share the entire source code with you if you wanna pursue it. Like + comment "AGENT" and I'll send you the app link, a comprehensive guide to build production-ready apps, and the entire source code for this.

Do you understand what's happening? It's not just "AI can make iOS apps" anymore. AI is eating up the entire software industry. Even Dario Amodei (founder of Claude) said 90% of all code in the world would be written by AI. In 20 minutes, I built this Duolingo for AI upskilling app with Superapp. The idea was simple - almost everyone today knows AI is the future, but most of them are still feeling left out. Their current jobs don't leave them with enough time to actually learn and build stuff with AI. There's AI dev, video making, animations, testing, etc. But no time or clear direction. So I built an app to fix exactly this. With AgentIQ, you get new lessons every day. Every time you learn something, it gets added to your skillset and automatically refreshes your portfolio. You level up with every new chapter/pathway. It is self-paced but gamified enough (like Duolingo) that you never get out of touch. Without spending hours or tonnes of money, you build stuff with n8n, openclaw, etc. You ship AI videos to market your own AI apps. This could be a proper ed-tech company if someone wants to continue building on top. Happy to share the entire source code with you if you wanna pursue it. Like + comment "AGENT" and I'll send you the app link, a comprehensive guide to build production-ready apps, and the entire source code for this.

Kritarth Mittal | Soshals

25,484 Aufrufe • vor 4 Monaten

your OpenClaw🦞 has NO IDEA what you do all day... what if we give it eyes and make it observe you all day? introducing synapse, a daemon that runs in the background, watches your screen activity through , and uses Claude to detect the workflows you keep repeating! then, it does two things: 1) turns those patterns into ready-to-use automations (e.g. claude code commands and skills you can run immediately) 2) feeds that context directly into your openclaw agent so it can act on what it sees your agent goes from "what do you want me to do" (which seems to be the default mode for almost all ai agents) to "i noticed you've been doing this repeatedly, want me to handle it for you?" let me give you a real example. > UEFA Champions League is coming up. > you want to place a prediction on juventus vs galatasaray > so you start doing what you always do: open a tab for injury reports, another for head-to-head history, another for current form tables, another for the odds across prediction markets > by the time you actually place anything you've spent 45 minutes on research you've done a hundred times before. synapse sees all of that! it automatically detects the pattern: "user repeatedly researches match injuries, form, and h2h stats before placing predictions on polymarket." it doesn't just log it. it proposes a prediction market research skill that pulls injury reports, recent form, historical matchups, and odds from multiple sources, and then gives you a structured breakdown with a confidence score. next champions league match day, you just type one command to get all of this done. beauty! all this happens while everything is locally stored on your machine. get started below ↓

your OpenClaw🦞 has NO IDEA what you do all day... what if we give it eyes and make it observe you all day? introducing synapse, a daemon that runs in the background, watches your screen activity through , and uses Claude to detect the workflows you keep repeating! then, it does two things: 1) turns those patterns into ready-to-use automations (e.g. claude code commands and skills you can run immediately) 2) feeds that context directly into your openclaw agent so it can act on what it sees your agent goes from "what do you want me to do" (which seems to be the default mode for almost all ai agents) to "i noticed you've been doing this repeatedly, want me to handle it for you?" let me give you a real example. > UEFA Champions League is coming up. > you want to place a prediction on juventus vs galatasaray > so you start doing what you always do: open a tab for injury reports, another for head-to-head history, another for current form tables, another for the odds across prediction markets > by the time you actually place anything you've spent 45 minutes on research you've done a hundred times before. synapse sees all of that! it automatically detects the pattern: "user repeatedly researches match injuries, form, and h2h stats before placing predictions on polymarket." it doesn't just log it. it proposes a prediction market research skill that pulls injury reports, recent form, historical matchups, and odds from multiple sources, and then gives you a structured breakdown with a confidence score. next champions league match day, you just type one command to get all of this done. beauty! all this happens while everything is locally stored on your machine. get started below ↓

altan tutar

10,493 Aufrufe • vor 5 Monaten

I built this Claude Cowork automation to handle a simple content marketing task that my team used to do daily. This frees up ~4 hours of time per week. At CoinLedger, every week we spend time repurposing pillar content (blog content) across various social networks (reddit, twitter, YouTube, IG, etc) We used to have a human + AI do this work. Now we just have AI doing it via this automation. Here's how the Claude automation works: → Scrapes any blog URL and extracts key insights → Transforms content into platform-specific posts (Reddit, Twitter, Instagram) → Automatically creates organized Google Docs for each piece → Updates our internal content tracking spreadsheet in real-time → Highlights completed tasks without any human oversight The game-changer? It runs completely in the background while I focus on higher-value strategic work. Now scale this up. All mundane, "virtual-assistant-style" work can be automated in this fashion. There is SO MUCH of this type of work in the real world. And there will be EVEN MORE of it when you can do it all for $100/mo. Here's the process you should follow: 1. Identify a simple, manual process that genuinely adds value to your company if you did it every single day 2. Build the skill / automation for Claude Code / Claude Cowork to do it 24/7 3. Refine 4. Unleash Claude 5. Repeat This could be list building for sales leads, scraping LinkedIn, identifying viral videos on TikTok that you can spin for your brand, research, and so so much more. Your imagination is the limit. But this type of work exists in all businesses. If you do this enough, you start to see why people have dozens of Claude instances running 24/7 on multiple devices. They have figured out ways for Claude to drive economically valuable work for their organizations. And now they are simply scaling up that work. Wild. This is where the world is quickly heading.

David Roberts

31,900 Aufrufe • vor 6 Monaten

Perplexity declared war on the biggest open source AI movement of 2026. This changes how millions of people will interact with AI agents forever. Here is what happened and why almost nobody is talking about the real implications. OpenClaw exploded in January and it became one of the fastest growing open source projects in GitHub history. The premise was radical. An AI agent that runs on your own machine, connects to your messaging apps and actually does things while you sleep. Developers went wild and over 700 community built skills appeared on ClawHub. People were negotiating car deals, filing legal rebuttals, and building entire social networks run by AI agents. Then Perplexity showed up with something different. A cloud powered system that coordinates 20 frontier AI models at once. They call it Perplexity Computer and this week they went even further. They announced Personal Computer. An always on AI agent that lives on a Mac mini in your home, connected to your local files and Perplexity's secure servers around the clock. It never sleeps or stops working and you control it from any device, anywhere. But the real story is what CEO Aravind Srinivas said during the Q&A session at their inaugural developer conference in San Francisco. He called Perplexity Computer a product "meant for serious people." He talked about Uber drivers asking him when they could stop driving and let AI make them passive income. That, he said, is the actual vision and then he went directly after OpenClaw. He said even a former Perplexity engineer struggled to get OpenClaw running on their own machine. He warned about unvetted malware being imported through OpenClaw's community skill hub, with no control over what people are contributing. He called the hobbyist approach of managing 700 API keys and sub agent configuration files a dead end for mainstream adoption. And four years of building world class orchestration gives Perplexity something an open source project cannot match. Enterprise grade security for solopreneurs and businesses alike. On one side, OpenClaw represents radical openness. Your data stays local, you choose your own models, you own everything and the community builds the tools. On the other hand, Perplexity is betting that most people don’t want to be system administrators. They want results, security guarantees, and something that just works out of the box. The Personal Computer runs on Perplexity's SOC 2 certified infrastructure. Every sensitive action requires user approval, every action is logged, and there is a kill switch. The enterprise version connects natively to Snowflake, Salesforce, HubSpot, and hundreds of other platforms. Teams can query data warehouses and build financial models without waiting on an analytics team. The real question is not which product is technically better. The real question is whether the future of AI agents looks like Linux or looks like the iPhone. Because the Uber driver Srinivas described is not going to configure sub agent routing tables. That person needs something that works the moment they open it. And if Perplexity captures that market, the open source movement becomes a niche for developers instead of a revolution for everyone. That is the billion dollar bet being made right now.

Perplexity declared war on the biggest open source AI movement of 2026. This changes how millions of people will interact with AI agents forever. Here is what happened and why almost nobody is talking about the real implications. OpenClaw exploded in January and it became one of the fastest growing open source projects in GitHub history. The premise was radical. An AI agent that runs on your own machine, connects to your messaging apps and actually does things while you sleep. Developers went wild and over 700 community built skills appeared on ClawHub. People were negotiating car deals, filing legal rebuttals, and building entire social networks run by AI agents. Then Perplexity showed up with something different. A cloud powered system that coordinates 20 frontier AI models at once. They call it Perplexity Computer and this week they went even further. They announced Personal Computer. An always on AI agent that lives on a Mac mini in your home, connected to your local files and Perplexity's secure servers around the clock. It never sleeps or stops working and you control it from any device, anywhere. But the real story is what CEO Aravind Srinivas said during the Q&A session at their inaugural developer conference in San Francisco. He called Perplexity Computer a product "meant for serious people." He talked about Uber drivers asking him when they could stop driving and let AI make them passive income. That, he said, is the actual vision and then he went directly after OpenClaw. He said even a former Perplexity engineer struggled to get OpenClaw running on their own machine. He warned about unvetted malware being imported through OpenClaw's community skill hub, with no control over what people are contributing. He called the hobbyist approach of managing 700 API keys and sub agent configuration files a dead end for mainstream adoption. And four years of building world class orchestration gives Perplexity something an open source project cannot match. Enterprise grade security for solopreneurs and businesses alike. On one side, OpenClaw represents radical openness. Your data stays local, you choose your own models, you own everything and the community builds the tools. On the other hand, Perplexity is betting that most people don’t want to be system administrators. They want results, security guarantees, and something that just works out of the box. The Personal Computer runs on Perplexity's SOC 2 certified infrastructure. Every sensitive action requires user approval, every action is logged, and there is a kill switch. The enterprise version connects natively to Snowflake, Salesforce, HubSpot, and hundreds of other platforms. Teams can query data warehouses and build financial models without waiting on an analytics team. The real question is not which product is technically better. The real question is whether the future of AI agents looks like Linux or looks like the iPhone. Because the Uber driver Srinivas described is not going to configure sub agent routing tables. That person needs something that works the moment they open it. And if Perplexity captures that market, the open source movement becomes a niche for developers instead of a revolution for everyone. That is the billion dollar bet being made right now.

Milk Road AI

22,256 Aufrufe • vor 5 Monaten

plz welcome: masscontent operator shts on openclaw shts on claude code sh*ts on higgsfield im pretty positive that this is the most powerful mass marketing agent on earth. just a short list of what he can do: - full phone farm integration (~$4 per account) - second brain on u and your competitors - 500+ marketing .skills pre-loaded - call 64 ai content models (50% of the cost) - build full ai vids/slides workflows in bulk (30 at once) - create consistent influencers and map them to accs - run ai theme pages by itself - auto-post everywhere via our phone farm - setup up lead mag auto-dm’s for every post - spin ai inbox agent to manage every dm and follow up - social intelligence scraping on every platform - clone viral posts with your brand + brain - fully edit every video - highly realistic Seedance 2.0 ugc - render mocked iOS app screen recs w/ your real ui - write tweets & post any render media - create saas mini-launch vids with every tweet (real ui) - scrape top ai influencer pages and clone them - use our credits or connect your anthropic key for unlimited - track posts work & edit all workflows to double down - all analytics mapped in his brain wiki - track every click and conversion event - create & post 1,000+ vids/day i’m not sure how i got here, but 2.1 million lines of code later… we are locked in. like, rt + comment “OPERATOR” and i’ll dm it to you. (must follow for dm)

Jonny Vandel

57,481 Aufrufe • vor 3 Monaten

Claude + Reddit intelligence + LinkedIn data = Content OS that replaced a $14,500/month team. (48K followers. 500+ booked calls. $387K in attributed revenue) This 6-skill system eliminates writers, strategists, researchers, and schedulers using brand memory + real audience intelligence + calibrated AI writers... → No more $14,500/month payroll for a 4-person content team → No more 20+ hours weekly building content calendars from scratch → No more guessing which hooks actually stop the scroll → No more AI slop that sounds nothing like you → No more starting every post from a blank page Just 1 topic in → a finished month of content out. Here's how it works: → Brand Memory (your voice, proof, and exact buyer in one file. every skill runs off it. nothing generic ships.) → Reddit Intelligence (mines your ICP's subreddits for the exact phrases they use. posts start from real words, not blank pages.) → LinkedIn Viral Signal (hooks already stopping the scroll in your niche, last 30 days, ranked by real engagement.) → Four Calibrated Writers (thought leadership, lead magnet, story, value. one writer per stage of the buyer journey.) → Voice Firewall (7-dimension QA that scores and rewrites every draft before it ships under your name.) → Finished Board (every post handed over with its visual and first comment. ready to approve.) Built on real content infrastructure. Zero payroll. Consistent output. Enterprise-grade quality. Results from the system: - $14,500/month content team eliminated - 48K LinkedIn followers - 500+ calls booked from content - $387K in attributed revenue Want the complete 6-skill build? Like + comment "OS" + repost, and I'll DM it to you. (must be following)

Aryan Mahajan

63,194 Aufrufe • vor 2 Monaten

6 months ago, Chibugo | AI automation had no AI Automation job. No fancy workstation. No high-paying role. No guarantee that learning another skill would finally be the thing that changed her life. Just a decision to try. Today? She’s working a full-time AI Automation role, earning well, and was even provided a complete workstation setup by her employer. But here’s the part most people won’t show you… The journey wasn’t smooth. There were assignments to complete. Concepts to understand. Moments of confusion. Days when showing up wasn’t convenient. Yet she kept going. And that’s why stories like hers don’t surprise me. Because success in AI Automation isn’t reserved for geniuses. It’s usually the result of ordinary people committing to learn a valuable skill and refusing to quit halfway. Now let me ask you something… How long have you been telling yourself that things will eventually get better? How many months have gone by saying: “I’ll learn a skill next month.” “I’ll start when I have more time.” “I’ll figure things out later.” Meanwhile, your income hasn’t changed. You still have to think twice before buying what you want. You’re still postponing things you should already be able to afford. You’re still hoping for a breakthrough instead of building one. The uncomfortable truth? The next 6 months will pass whether you act or not. The only question is: Will your life look different when they do? For Chibugo, 6 months was enough to completely change her trajectory. For you, it could be the beginning of your own story. The next AI Automation Cohort starts in July. If you’re ready to stop watching opportunities pass by and start building skills businesses are actively paying for, this is your chance. Registration is already open and we have some slots taken already So use the Link in the comments to secure your own slot.. See you in class. (Full podcast will be out tomorrow 😊)

6 months ago, Chibugo | AI automation had no AI Automation job. No fancy workstation. No high-paying role. No guarantee that learning another skill would finally be the thing that changed her life. Just a decision to try. Today? She’s working a full-time AI Automation role, earning well, and was even provided a complete workstation setup by her employer. But here’s the part most people won’t show you… The journey wasn’t smooth. There were assignments to complete. Concepts to understand. Moments of confusion. Days when showing up wasn’t convenient. Yet she kept going. And that’s why stories like hers don’t surprise me. Because success in AI Automation isn’t reserved for geniuses. It’s usually the result of ordinary people committing to learn a valuable skill and refusing to quit halfway. Now let me ask you something… How long have you been telling yourself that things will eventually get better? How many months have gone by saying: “I’ll learn a skill next month.” “I’ll start when I have more time.” “I’ll figure things out later.” Meanwhile, your income hasn’t changed. You still have to think twice before buying what you want. You’re still postponing things you should already be able to afford. You’re still hoping for a breakthrough instead of building one. The uncomfortable truth? The next 6 months will pass whether you act or not. The only question is: Will your life look different when they do? For Chibugo, 6 months was enough to completely change her trajectory. For you, it could be the beginning of your own story. The next AI Automation Cohort starts in July. If you’re ready to stop watching opportunities pass by and start building skills businesses are actively paying for, this is your chance. Registration is already open and we have some slots taken already So use the Link in the comments to secure your own slot.. See you in class. (Full podcast will be out tomorrow 😊)

Damola | AI & Automation

12,650 Aufrufe • vor 1 Monat

I run my linkedin ads with OpenClaw🦞 for $0/month 😱 here's the system to get real buyers (not bad leads): step 1: read the account → ingests csv exports OR pulls the LinkedIn marketing api directly → campaigns, creatives, lead forms, spend. all of it. → no dashboard. just the raw truth of what's happening in the account. step 2: calls out fake noise → that "efficient" campaign pulling vendors and students? flagged. → high-CTR post pulling people who will never buy? flagged. → everything tied to real crm outcomes, not platform vanity metrics. step 3: grade buyer quality → maps every lead against ICP fit, intent, and sales-readiness → the cheapest lead is usually the worst lead. the kit knows the difference → cross-references crm notes so sales quality compounds every run step 4: find the leaks → good ad + generic form = lost conversation. → surfaces every break between audience, offer, form, crm, and handoff. → tells you which leak is costing the most. not "ctr went up 12%" step 5: score thought leader posts → likes ≠ buyers. ranks posts on ICP fit, buyer pain, trust, organic signal → drafts the sponsored creative. OR a launch packet if the api's gated → no more paying to boost posts that went viral with the wrong audience step 6: draft safe moves → pause, budget update, activate draft. every action is reversible → dry-run first. signed receipt. explicit APPLY confirmation → no freehanding your ad account step 7: compound the memory → every brief writes back to learnings md → which offers create quality. which voices deserve spend. what never to repeat → multi-brand by default. no cross-contamination between projects input: linkedin ads exports (or oauth) + lead data + crm notes output: daily buyer-quality brief + reviewable drafts + brand memory that compounds linkedin ads agencies charge $8-15K/mo to manage B2B accounts. this runs the operator loop for $0. I packaged the entire system as the LinkedIn Ads Kit. 10 claude skills: - linkedin-ads (core operator loop + daily brief) - linkedin-api-connect (oauth, account discovery, api health) - linkedin-ads-apply (safe drafts, dry run, audit trail) - buyer-quality-audit (real buyers vs. fake lead volume) - lead-quality-mapper (fit, intent, sales-readiness per lead) - offer-angle-diagnoser (is the offer strong enough for linkedin) - thought-leader-ad-selector (score posts, draft creative or packet) - form-friction-review (fix lead forms for quality, not volume) - pipeline-brief-writer (executive brief from the findings) - sales-handoff (context so sales knows why the lead converted) also works with OpenClaw🦞, hermes (Nous Research) codex or any agent giving it away free. comment BUYERS + like + follow (must follow so i can DM)

Matthew Berman

11,240 Aufrufe • vor 3 Monaten

OpenClaw has 186K GitHub stars and 1.5M compromised API keys. I needed a secure alternative. So, I built it with n8n and Claude Opus 4.6. It can already: - Reply to your Telegram messages - Access selected folders from your laptop - Access Gmail, Drive, Notion, Linear, etc. - Install new local tools in a sandbox - Run autonomously for hours - Create multiple subagents - Learn from experience - Wake up regularly But, unlike OpenClaw, it: - Can't access your API keys - Can't modify its environment - Can't access folders you haven't shared - Can't access tools you haven't approved - Must get your confirmation, e.g., when sending emails These aren’t prompt instructions. They’re hard architectural boundaries — Docker isolation, mounted folder permissions, n8n’s tool approval system. Key components: ✅ The VPS on Hostinger hosts n8n and a sandbox container. Agents can also connect to my laptop's sandbox via a Claudeflare tunnel + Desktop Commander MCP. ✅ The Manager agent is the brain. It plans, decides, delegates, and talks to the user. It never touches files. It never runs scripts. It works entirely from executor summaries. ✅ The Executor agents are the hands. Each receives a task (what to do + why it matters), decides how to execute it, and reports back. They can install new tools and execute code only in their dedicated sandboxes. ✅ Data Tables in n8n store both memories and sessions — no external database, no vector store, no infrastructure. Just rows in a table. Turns out, that's enough. Two memory types: - Manager memory: user preferences, facts, corrections, relationship, skills, context - Executor memory: what tools are installed, what’s broken, workarounds ✅ Sessions are short-term state for multi-step tasks. Original request, plan, assumptions, and what happened so far. When the Manager loops with fresh context, the session is all it gets. That's a Ralph Wiggum loop. I've been using it for 5 days. And already can't imagine not having it on my phone. What's next: - Heartbeat via Cron (a scheduled prompt) - Civic Nexus governance + MCPs - Supermemory integration - WhatsApp as an additional surface - Hardening The architecture supports all of it. OpenClaw proved people want personal AI agents. It also proved that 'just trust the prompt' isn't a security model. Docker isolation, mounted folder permissions, tool approval — none of this is new technology. It's just discipline. You can easily do this even with n8n — no coding required. --- Want to try it or read more? More, what I learned, and a setup guide: productcompass[.]pm

OpenClaw has 186K GitHub stars and 1.5M compromised API keys. I needed a secure alternative. So, I built it with n8n and Claude Opus 4.6. It can already: - Reply to your Telegram messages - Access selected folders from your laptop - Access Gmail, Drive, Notion, Linear, etc. - Install new local tools in a sandbox - Run autonomously for hours - Create multiple subagents - Learn from experience - Wake up regularly But, unlike OpenClaw, it: - Can't access your API keys - Can't modify its environment - Can't access folders you haven't shared - Can't access tools you haven't approved - Must get your confirmation, e.g., when sending emails These aren’t prompt instructions. They’re hard architectural boundaries — Docker isolation, mounted folder permissions, n8n’s tool approval system. Key components: ✅ The VPS on Hostinger hosts n8n and a sandbox container. Agents can also connect to my laptop's sandbox via a Claudeflare tunnel + Desktop Commander MCP. ✅ The Manager agent is the brain. It plans, decides, delegates, and talks to the user. It never touches files. It never runs scripts. It works entirely from executor summaries. ✅ The Executor agents are the hands. Each receives a task (what to do + why it matters), decides how to execute it, and reports back. They can install new tools and execute code only in their dedicated sandboxes. ✅ Data Tables in n8n store both memories and sessions — no external database, no vector store, no infrastructure. Just rows in a table. Turns out, that's enough. Two memory types: - Manager memory: user preferences, facts, corrections, relationship, skills, context - Executor memory: what tools are installed, what’s broken, workarounds ✅ Sessions are short-term state for multi-step tasks. Original request, plan, assumptions, and what happened so far. When the Manager loops with fresh context, the session is all it gets. That's a Ralph Wiggum loop. I've been using it for 5 days. And already can't imagine not having it on my phone. What's next: - Heartbeat via Cron (a scheduled prompt) - Civic Nexus governance + MCPs - Supermemory integration - WhatsApp as an additional surface - Hardening The architecture supports all of it. OpenClaw proved people want personal AI agents. It also proved that 'just trust the prompt' isn't a security model. Docker isolation, mounted folder permissions, tool approval — none of this is new technology. It's just discipline. You can easily do this even with n8n — no coding required. --- Want to try it or read more? More, what I learned, and a setup guide: productcompass[.]pm

Paweł Huryn

54,038 Aufrufe • vor 6 Monaten

SpaceX’s AI arm is partnering with coding startup Cursor in a deal worth no less than $10 billion and as much as $60 billion. Can the pair topple the rising Anthropic-OpenAI AI coding axis? A lot of money is being bet that the answer is yes. Next up, Lon Harris and alex 🏴‍☠️🇺🇸🇺🇦 invited the bitstarter team on the show to discuss their work to help kickstart new Bittensor subnets. The dynamic duo had a new program to announce, so make sure to tune into their pitch if you have dreams of launching your own subnet. Then we brought TrajectoryRL onto the pod, a Bittensor subnet that holds competitions to improve agent skills. Yes, the markdown files that everyone who uses OpenClaw swears by. Hit play, let’s have some fun! 2:27 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at and use code TWIST for 10% off! 4:07 SpaceX/ xAI "partners" with Cursor! 9:35 Will the Cursor deal help pump a future SpaceX IPO? 9:57 LinkedIn Jobs - Hire right, the first time. Post your first job and get $100 off towards your job post at 12:14 How AI coding models like Cursor help xAI grow recursively. 17:24 Chris Zacharia and Brian McRindle of Bitstarter join the show. 20:23 Grasshopper Bank: Time is money. Don't waste either. Go to and get an exclusive $500 cash bonus just for opening an account. 29:59 Notion - Notion brings all your notes, docs, and projects into one connected space that just works with AI built right in. Try Notion, with Notion Agent, at 33:03 How Bittensor subnets monetize and how it compares to VC funds. 37:04 Is Bittensor hard-capped at 128 subnets? 42:37 Bittensor's biggest weakness. 46:10 Ning Ren of TrajectoryRL joins the show. 47:34 Skills now need entire agents just to write them! 48:26 Back up… What are skills? 1:07:38 Amazon and Anthropic's $5 BILLION deal 1:08:48 Google has 2 new chips! 1:09:50 Apple CEO, Tim is COOKED! John Ternus is in! 1:11:37 Alex is bullish on MacBook Neo! 🎥 Watch the full episode here 👇

SpaceX’s AI arm is partnering with coding startup Cursor in a deal worth no less than $10 billion and as much as $60 billion. Can the pair topple the rising Anthropic-OpenAI AI coding axis? A lot of money is being bet that the answer is yes. Next up, Lon Harris and alex 🏴‍☠️🇺🇸🇺🇦 invited the bitstarter team on the show to discuss their work to help kickstart new Bittensor subnets. The dynamic duo had a new program to announce, so make sure to tune into their pitch if you have dreams of launching your own subnet. Then we brought TrajectoryRL onto the pod, a Bittensor subnet that holds competitions to improve agent skills. Yes, the markdown files that everyone who uses OpenClaw swears by. Hit play, let’s have some fun! 2:27 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at and use code TWIST for 10% off! 4:07 SpaceX/ xAI "partners" with Cursor! 9:35 Will the Cursor deal help pump a future SpaceX IPO? 9:57 LinkedIn Jobs - Hire right, the first time. Post your first job and get $100 off towards your job post at 12:14 How AI coding models like Cursor help xAI grow recursively. 17:24 Chris Zacharia and Brian McRindle of Bitstarter join the show. 20:23 Grasshopper Bank: Time is money. Don't waste either. Go to and get an exclusive $500 cash bonus just for opening an account. 29:59 Notion - Notion brings all your notes, docs, and projects into one connected space that just works with AI built right in. Try Notion, with Notion Agent, at 33:03 How Bittensor subnets monetize and how it compares to VC funds. 37:04 Is Bittensor hard-capped at 128 subnets? 42:37 Bittensor's biggest weakness. 46:10 Ning Ren of TrajectoryRL joins the show. 47:34 Skills now need entire agents just to write them! 48:26 Back up… What are skills? 1:07:38 Amazon and Anthropic's $5 BILLION deal 1:08:48 Google has 2 new chips! 1:09:50 Apple CEO, Tim is COOKED! John Ternus is in! 1:11:37 Alex is bullish on MacBook Neo! 🎥 Watch the full episode here 👇

This Week in Startups

19,991 Aufrufe • vor 3 Monaten

here's what's actually working in SEO in 2026 vs what's getting people cooked: 1. small sites blasting AI content on their own domain are done. the algo update is sharp — you'll see a euphoric jump on ahrefs, your team will be doing high-fives, and one week later you'll never recover. one article a day max. manually edited. don't blast your URL or you don't come back. 2. content quality is fully commoditized. google can't tell good content from bad anymore so it just defaults to ranking the biggest domain. a blog post on a high-DR site with literally just a title in the body will outrank most of the internet. domain authority is the only tiebreaker left. 3. parasite SEO is the cheat code. listicles on publications you have an in with. facebook groups. reddit threads. quora. medium. linkedin posts. anywhere big that lets you publish — write it, index it, send real chrome traffic to it (google reads chrome data as a ranking signal), and it ranks. 4. AI overviews CTR went from 1% to 2.4% on cited pages. sounds like a recovery. it's not. position one used to get 30% clicks. publishers are still cooked. brands and end users win, everyone in between gets eaten. 5. people freaking out about their search console impressions exploding are NGMI. half of that is bots, scrapers, rank trackers, and chatGPT itself doing a search every time it answers a query. it's not real demand. bonus: starbucks launched a "describe your mood, get a drink" feature on chatGPT. peak NGMI. there are 50 better AI use cases for them — push notifications based on purchase history, revenue optimization — anything other than vibes-to-latte. watch/listen here ↓

here's what's actually working in SEO in 2026 vs what's getting people cooked: 1. small sites blasting AI content on their own domain are done. the algo update is sharp — you'll see a euphoric jump on ahrefs, your team will be doing high-fives, and one week later you'll never recover. one article a day max. manually edited. don't blast your URL or you don't come back. 2. content quality is fully commoditized. google can't tell good content from bad anymore so it just defaults to ranking the biggest domain. a blog post on a high-DR site with literally just a title in the body will outrank most of the internet. domain authority is the only tiebreaker left. 3. parasite SEO is the cheat code. listicles on publications you have an in with. facebook groups. reddit threads. quora. medium. linkedin posts. anywhere big that lets you publish — write it, index it, send real chrome traffic to it (google reads chrome data as a ranking signal), and it ranks. 4. AI overviews CTR went from 1% to 2.4% on cited pages. sounds like a recovery. it's not. position one used to get 30% clicks. publishers are still cooked. brands and end users win, everyone in between gets eaten. 5. people freaking out about their search console impressions exploding are NGMI. half of that is bots, scrapers, rank trackers, and chatGPT itself doing a search every time it answers a query. it's not real demand. bonus: starbucks launched a "describe your mood, get a drink" feature on chatGPT. peak NGMI. there are 50 better AI use cases for them — push notifications based on purchase history, revenue optimization — anything other than vibes-to-latte. watch/listen here ↓

Jacky Chou (buying online businesses up to $1m)

17,360 Aufrufe • vor 3 Monaten

Introducing Stanley: The first AI Head of Content that will help you grow your following. Stanley works just like a real employee: text him and he’ll create, edit, and strategize viral content across X, LinkedIn, and Instagram. Making viral content is hard. It requires deep research, deep platform understanding, and knowing what’s culturally relevant at that exact minute. When you ask ChatGPT to “write a social post” it doesn’t know what good content looks like, it’s not actively consuming content, and it doesn’t understand you. This is why the output is slop. Stanley solves this. First Stanley deeply understands your unique voice and writing style (and doesn’t include AI language like em dashes and “it’s not x it’s y”) Then he plugs into your day-to-day (your Slack, Notion, Calendar, Granola) and proactively suggests viral posts for you based off the most interesting things happening in your life. All you need to do is voice note him your thoughts, and Stanley optimizes and then schedules a post across all platforms. Example: Last week I asked ChatGPT "what happened on X" and got a generic summary. I asked Stanley the same thing and he told me about Jensen Huang's first post on X and the viral Deny’s comment. That’s because Stanley has a team of specialized agents that are always on. One agent researches viral posts through the X API. One studies your voice. One doom scrolls X, LinkedIn, and Instagram. 2 months ago we released Stanley in beta to 100 social media power users like @chasepassiveincome, Jay Yang, Mitchell, and Pascio who’ve used Stanley in their daily content process. Engagement rates increased by >50% for the average beta tester. (in fact you’ve probably engaged w/ Stanley posts without realizing) Posting content has genuinely changed my life for the better: it’s helped me raise millions of $, landed me my first customers, and attracted the very best employees. Stan wouldn’t be a $40M ARR business without Content. Stanley is our attempt at democratizing that. Our mission is to help any Entrepreneur tell their story, so we'd love for you to try Stanley for free here: One more thing.. You can see a glimpse of Stanley’s power in the comments below. Drop a reply and Stanley will analyze your X content right now. It'll pull your posts, study your voice, and tell you what's working and what's not. Each reply costs us abt ~$1 in tokens. Go abuse it. (Thank you VC’s.) FYI: This post and launch video were written 100% w/ the help of Stanley (how’d he do?) See Stanley work below 👇

Introducing Stanley: The first AI Head of Content that will help you grow your following. Stanley works just like a real employee: text him and he’ll create, edit, and strategize viral content across X, LinkedIn, and Instagram. Making viral content is hard. It requires deep research, deep platform understanding, and knowing what’s culturally relevant at that exact minute. When you ask ChatGPT to “write a social post” it doesn’t know what good content looks like, it’s not actively consuming content, and it doesn’t understand you. This is why the output is slop. Stanley solves this. First Stanley deeply understands your unique voice and writing style (and doesn’t include AI language like em dashes and “it’s not x it’s y”) Then he plugs into your day-to-day (your Slack, Notion, Calendar, Granola) and proactively suggests viral posts for you based off the most interesting things happening in your life. All you need to do is voice note him your thoughts, and Stanley optimizes and then schedules a post across all platforms. Example: Last week I asked ChatGPT "what happened on X" and got a generic summary. I asked Stanley the same thing and he told me about Jensen Huang's first post on X and the viral Deny’s comment. That’s because Stanley has a team of specialized agents that are always on. One agent researches viral posts through the X API. One studies your voice. One doom scrolls X, LinkedIn, and Instagram. 2 months ago we released Stanley in beta to 100 social media power users like @chasepassiveincome, Jay Yang, Mitchell, and Pascio who’ve used Stanley in their daily content process. Engagement rates increased by >50% for the average beta tester. (in fact you’ve probably engaged w/ Stanley posts without realizing) Posting content has genuinely changed my life for the better: it’s helped me raise millions of $, landed me my first customers, and attracted the very best employees. Stan wouldn’t be a $40M ARR business without Content. Stanley is our attempt at democratizing that. Our mission is to help any Entrepreneur tell their story, so we'd love for you to try Stanley for free here: One more thing.. You can see a glimpse of Stanley’s power in the comments below. Drop a reply and Stanley will analyze your X content right now. It'll pull your posts, study your voice, and tell you what's working and what's not. Each reply costs us abt ~$1 in tokens. Go abuse it. (Thank you VC’s.) FYI: This post and launch video were written 100% w/ the help of Stanley (how’d he do?) See Stanley work below 👇

John Hu

2,081,995 Aufrufe • vor 18 Tagen