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767,661 次观看 • 3 年前 •via X (Twitter)

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I couldn't believe it. One product image = a full video ad with Wizstar. No script. No shoot. No editor. Just the image, one sentence of instruction, and Wizstar did everything else. It analyzes your product automatically, builds the scene around it, and generates a complete marketing video. Character stays consistent across every shot. Product details stay accurate. Audio and video sync perfectly. It powers multi-model invocation to match any style you need, and Seedance 2.0 supports face input for consistent character generation. But wait, it gets better. You can also upload any viral video from TikTok or Amazon. Then it will recreate that EXACT winning formula for YOUR product. No more guessing what works. Zero creative trial and error. Make a video today, start seeing sales in 7 days. New users get free credits on signup. First subscription is only $19 and includes a 30-second E-commerce Agent experience. Try it here: Who's making their first ad tonight? 👇 #Wizstar #AIVideo #EcommerceMarketing

I couldn't believe it. One product image = a full video ad with Wizstar. No script. No shoot. No editor. Just the image, one sentence of instruction, and Wizstar did everything else. It analyzes your product automatically, builds the scene around it, and generates a complete marketing video. Character stays consistent across every shot. Product details stay accurate. Audio and video sync perfectly. It powers multi-model invocation to match any style you need, and Seedance 2.0 supports face input for consistent character generation. But wait, it gets better. You can also upload any viral video from TikTok or Amazon. Then it will recreate that EXACT winning formula for YOUR product. No more guessing what works. Zero creative trial and error. Make a video today, start seeing sales in 7 days. New users get free credits on signup. First subscription is only $19 and includes a 30-second E-commerce Agent experience. Try it here: Who's making their first ad tonight? 👇 #Wizstar #AIVideo #EcommerceMarketing

Pradeep Pandey

59,917 次观看 • 4 个月前

Anthropic's Claude Ai Agents Team just Educated how to build production AI agents in under 30 mins. For Free. From the engineers who built the stack. CANCEL Your Weekend Plans, and Learn to Build AI Agents Today. Bookmark it. Watch it. Build your first production agent this weekend. $5,000/month. $7,000/month. $12,000/month. People are building agents for clients and charging $$$ as Beginners. You're still stuck in the thinking about AI phase. This video fixes that tonight. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward. ↓ Ivan Nardini runs Developer Relations for AI at Google Cloud. He just gave away the entire production agent stack in 30 minutes. This is the talk that separates people deploying AI agents that actually scale from people whose agents break the moment they leave localhost. Here's everything inside. I break down a production AI video like this every week. Follow Himanshu Kumar. ↓ The 4-part agent stack that actually scales. Most devs are duct-taping frameworks together and calling it an "AI agent." Ivan lays out the real stack: Agent Development Kit (ADK): open-source, code-first framework for building, evaluating, and deploying agents. Supports Claude models through Vertex AI directly. Model Context Protocol (MCP): lets your agent talk to any tool or data source with one standard. Vertex AI Agent Engine: managed platform for deploying, monitoring, and scaling agents in production. No DevOps headaches. Agent-to-Agent Protocol: open protocol so agents built on different frameworks can actually work together. This is the stack replacing every hacky agent setup in production right now. Full MCP + Claude breakdowns drop weekly on Himanshu Kumar. ↓ Building your first real agent. Ivan builds a birthday planner agent live. LLM Agent class. Name it. Define instructions. Pick the model. He uses Claude 3.7 Sonnet. You could use Opus 4.7 for better reasoning. Full agent built in minutes. Not weeks. Watch the build once and you'll never structure an agent the wrong way again. I post agent architectures people pay $500 courses to learn. Himanshu Kumar. ↓ Multi-agent systems without the chaos. Single agents are easy. Multi-agent systems are where 99% of builders fail. Ivan extends the birthday planner by: Adding a calendar service through MCP tools Creating an orchestrator agent to route requests between agents Handling state and context across agent handoffs This is production multi-agent architecture. Clean. Scalable. Debuggable. Most tutorials hand-wave this part. This one shows you every step. Multi-agent orchestration content drops weekly on Himanshu Kumar. ↓ Deployment without the DevOps nightmare. This is where most AI projects die. You build a cool agent locally. It works. You try to deploy it. Everything breaks. Vertex AI Agent Engine fixes this: Minimal code deployment Automatic monitoring of latency, CPU, and memory Built-in observability and logging No infrastructure setup needed You provide config and requirements. The platform handles the rest. This is how agents actually get to production. Deployment guides for Claude agents post every week. Himanshu Kumar. ↓ Agent-to-Agent Protocol: the future nobody's talking about. Most people don't know this exists yet. The A2A Protocol lets agents built in different frameworks communicate seamlessly. Your Claude agent. My LangChain agent. Someone else's CrewAI agent. All talking to each other. All solving parts of the same problem. All without custom integration code. This is the infrastructure layer of the coming AI economy. Getting in early on A2A Protocol is like getting in early on HTTP in 1995. A2A deep dive coming soon. Himanshu Kumar. ↓ 30 minutes from the team shipping this in production. You'll learn more from this than from 6 months of YouTube tutorials made by people who've never deployed an agent past localhost. People who watch this understand production AI agents at the architect level. People who skip it keep hacking together frameworks that break every time an API updates. Save the video. Watch it tonight. Build a real agent this weekend. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward.

Anthropic's Claude Ai Agents Team just Educated how to build production AI agents in under 30 mins. For Free. From the engineers who built the stack. CANCEL Your Weekend Plans, and Learn to Build AI Agents Today. Bookmark it. Watch it. Build your first production agent this weekend. $5,000/month. $7,000/month. $12,000/month. People are building agents for clients and charging $$$ as Beginners. You're still stuck in the thinking about AI phase. This video fixes that tonight. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward. ↓ Ivan Nardini runs Developer Relations for AI at Google Cloud. He just gave away the entire production agent stack in 30 minutes. This is the talk that separates people deploying AI agents that actually scale from people whose agents break the moment they leave localhost. Here's everything inside. I break down a production AI video like this every week. Follow Himanshu Kumar. ↓ The 4-part agent stack that actually scales. Most devs are duct-taping frameworks together and calling it an "AI agent." Ivan lays out the real stack: Agent Development Kit (ADK): open-source, code-first framework for building, evaluating, and deploying agents. Supports Claude models through Vertex AI directly. Model Context Protocol (MCP): lets your agent talk to any tool or data source with one standard. Vertex AI Agent Engine: managed platform for deploying, monitoring, and scaling agents in production. No DevOps headaches. Agent-to-Agent Protocol: open protocol so agents built on different frameworks can actually work together. This is the stack replacing every hacky agent setup in production right now. Full MCP + Claude breakdowns drop weekly on Himanshu Kumar. ↓ Building your first real agent. Ivan builds a birthday planner agent live. LLM Agent class. Name it. Define instructions. Pick the model. He uses Claude 3.7 Sonnet. You could use Opus 4.7 for better reasoning. Full agent built in minutes. Not weeks. Watch the build once and you'll never structure an agent the wrong way again. I post agent architectures people pay $500 courses to learn. Himanshu Kumar. ↓ Multi-agent systems without the chaos. Single agents are easy. Multi-agent systems are where 99% of builders fail. Ivan extends the birthday planner by: Adding a calendar service through MCP tools Creating an orchestrator agent to route requests between agents Handling state and context across agent handoffs This is production multi-agent architecture. Clean. Scalable. Debuggable. Most tutorials hand-wave this part. This one shows you every step. Multi-agent orchestration content drops weekly on Himanshu Kumar. ↓ Deployment without the DevOps nightmare. This is where most AI projects die. You build a cool agent locally. It works. You try to deploy it. Everything breaks. Vertex AI Agent Engine fixes this: Minimal code deployment Automatic monitoring of latency, CPU, and memory Built-in observability and logging No infrastructure setup needed You provide config and requirements. The platform handles the rest. This is how agents actually get to production. Deployment guides for Claude agents post every week. Himanshu Kumar. ↓ Agent-to-Agent Protocol: the future nobody's talking about. Most people don't know this exists yet. The A2A Protocol lets agents built in different frameworks communicate seamlessly. Your Claude agent. My LangChain agent. Someone else's CrewAI agent. All talking to each other. All solving parts of the same problem. All without custom integration code. This is the infrastructure layer of the coming AI economy. Getting in early on A2A Protocol is like getting in early on HTTP in 1995. A2A deep dive coming soon. Himanshu Kumar. ↓ 30 minutes from the team shipping this in production. You'll learn more from this than from 6 months of YouTube tutorials made by people who've never deployed an agent past localhost. People who watch this understand production AI agents at the architect level. People who skip it keep hacking together frameworks that break every time an API updates. Save the video. Watch it tonight. Build a real agent this weekend. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward.

Himanshu Kumar

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Claim FREE $500 USDT with zero deposit required. This works right now and takes less than 5 minutes to claim. You only need email + phone number to sign up and claim your $500 USDT. I made the complete video guide with step-by-step process. Normally priced at $100, but it's free for 24 hours. To get it: 1. Comment "USDT" 2. Like and Retweet this post. 3. Follow me Himanshu Kumar (so I can DM you) What you will guide to Setup: ✅ Complete sign up process ✅ How to locate and claim the $500 bonus ✅ Using the bonus for futures trading ✅ Other available bonuses on Toobit ✅ How the bonus system works No deposit needed. Just sign up and start trading with free $500. Must Follow me Himanshu Kumar to get the DM. ⚠️ Disclaimer: This is not financial advice. Crypto trading is extremely risky and may result in total loss. Always do your own research.

Claim FREE $500 USDT with zero deposit required. This works right now and takes less than 5 minutes to claim. You only need email + phone number to sign up and claim your $500 USDT. I made the complete video guide with step-by-step process. Normally priced at $100, but it's free for 24 hours. To get it: 1. Comment "USDT" 2. Like and Retweet this post. 3. Follow me Himanshu Kumar (so I can DM you) What you will guide to Setup: ✅ Complete sign up process ✅ How to locate and claim the $500 bonus ✅ Using the bonus for futures trading ✅ Other available bonuses on Toobit ✅ How the bonus system works No deposit needed. Just sign up and start trading with free $500. Must Follow me Himanshu Kumar to get the DM. ⚠️ Disclaimer: This is not financial advice. Crypto trading is extremely risky and may result in total loss. Always do your own research.

Himanshu Kumar

44,956 次观看 • 6 个月前

$15k–$21k from one video in 30 days. A finance channel hit almost 1 million views on a idea that has been done a thousand times. “20 Boring Businesses That Make Money While You Sleep.” 858k views and still climbing. No face. No personal brand. Just a ranked list of boring cash-flow machines with exact startup costs and real numbers. This exact format is still printing harder than almost anything else in finance right now. I dropped the same idea into NextGen Studio and had a full animated version ready in minutes, same visual style, same retention, same money packaging. Want the exact title formulas + format structures that are currently hitting 300k–1M views in this niche? Follow & Comment “TITLES” and I’ll DM you the best formats in finance niche full list free!

Shaun Young 🃏

22,856 次观看 • 1 个月前

HERMES AGENT BECOMES 10X MORE USEFUL WHEN YOU CONFIGURE THESE 5 THINGS. EACH ONE TAKES 5 MINUTES. MOST USERS NEVER TOUCH THEM. 1. THE RIGHT MODELS one model for everything = wrong model for most things. GPT-5.6 Sol: strongest reasoning. daily driver. access through your ChatGPT subscription (Plus or higher). Max plan unlocks higher reasoning effort. Grok 4.5: live X search. fastest responses. access through your X Premium+ subscription. "find me 3 high-engagement Hermes posts from the last 5 days." Grok pulls directly from X. no scraping. real-time. Kimi K3: design powerhouse. comparable quality to Claude Fable 5 at roughly 30% of the price. takes longer to generate. the quality justifies the wait. connect via Desktop app / Dashboard: Models → add provider. GPT-5.6: ChatGPT subscription → OAuth. Grok 4.5: X subscription → OAuth. Kimi K3: OpenRouter or Nous Portal. switch between them mid-session: /model [name] 2. PARALLEL TOOL CALLS Hermes used to call tools one at a time. Gmail, then calendar, then web search. sequential. now: multiple tool calls run simultaneously. "check my emails, check my calendar, tell me the weather in Dubai, and find the latest Hermes updates." four tools at once. results merge when all finish. what used to take 3 minutes takes 30 seconds. automatic after update. no config needed. hermes update 3. FASTER AND CHEAPER WEB SEARCH two improvements. one automatic, one you configure. AUTOMATIC (update only): v0.19.0 processes web pages differently. clean content straight to the agent without redundant processing steps. 60x faster. 49x cheaper. no config needed. CONFIGURE (Firecrawl): Firecrawl is the default scraping backend. strips HTML, ads, navigation, scripts. returns only the text your agent needs. 500 free credits per month on free tier. get your key from firecrawl .dev. add to .env: FIRECRAWL_API_KEY=your_key Nous Portal subscribers: Firecrawl is included through Tool Gateway. no separate key needed. SAVE MORE (auxiliary model): web summarization defaults to your main model. route it to a cheap model: auxiliary: web_extract: model: google/gemini-3-flash-preview cheap model reads the page. premium model reasons about the content. 4. MORNING BRIEF WITH EMAIL + CALENDAR connect Gmail and Google Calendar via MCP: 1. go to mcp .zapier.com 2. add Gmail: enable read and draft only. never enable send. one automated email from the wrong context can cost a relationship. 3. add Google Calendar: read access. 4. click connect → sign in → regenerate token 5. paste the token into Hermes chat tell your agent: "create a

HERMES AGENT BECOMES 10X MORE USEFUL WHEN YOU CONFIGURE THESE 5 THINGS. EACH ONE TAKES 5 MINUTES. MOST USERS NEVER TOUCH THEM. 1. THE RIGHT MODELS one model for everything = wrong model for most things. GPT-5.6 Sol: strongest reasoning. daily driver. access through your ChatGPT subscription (Plus or higher). Max plan unlocks higher reasoning effort. Grok 4.5: live X search. fastest responses. access through your X Premium+ subscription. "find me 3 high-engagement Hermes posts from the last 5 days." Grok pulls directly from X. no scraping. real-time. Kimi K3: design powerhouse. comparable quality to Claude Fable 5 at roughly 30% of the price. takes longer to generate. the quality justifies the wait. connect via Desktop app / Dashboard: Models → add provider. GPT-5.6: ChatGPT subscription → OAuth. Grok 4.5: X subscription → OAuth. Kimi K3: OpenRouter or Nous Portal. switch between them mid-session: /model [name] 2. PARALLEL TOOL CALLS Hermes used to call tools one at a time. Gmail, then calendar, then web search. sequential. now: multiple tool calls run simultaneously. "check my emails, check my calendar, tell me the weather in Dubai, and find the latest Hermes updates." four tools at once. results merge when all finish. what used to take 3 minutes takes 30 seconds. automatic after update. no config needed. hermes update 3. FASTER AND CHEAPER WEB SEARCH two improvements. one automatic, one you configure. AUTOMATIC (update only): v0.19.0 processes web pages differently. clean content straight to the agent without redundant processing steps. 60x faster. 49x cheaper. no config needed. CONFIGURE (Firecrawl): Firecrawl is the default scraping backend. strips HTML, ads, navigation, scripts. returns only the text your agent needs. 500 free credits per month on free tier. get your key from firecrawl .dev. add to .env: FIRECRAWL_API_KEY=your_key Nous Portal subscribers: Firecrawl is included through Tool Gateway. no separate key needed. SAVE MORE (auxiliary model): web summarization defaults to your main model. route it to a cheap model: auxiliary: web_extract: model: google/gemini-3-flash-preview cheap model reads the page. premium model reasons about the content. 4. MORNING BRIEF WITH EMAIL + CALENDAR connect Gmail and Google Calendar via MCP: 1. go to mcp .zapier.com 2. add Gmail: enable read and draft only. never enable send. one automated email from the wrong context can cost a relationship. 3. add Google Calendar: read access. 4. click connect → sign in → regenerate token 5. paste the token into Hermes chat tell your agent: "create a

YanXbt

29,620 次观看 • 2 个月前

$VET, #VeFam. In this video, I demonstrate in less than 4:30 minutes how to create an AI agent on veworld(.)ai. Watch me build a Mr. Robot Monologue Writer agent. If you haven't seen Mr. Robot, I suggest you watch it! This is just early bird access. The options for tools and integrations and such are limited, but what exists is already working quite well. The process is easy peasy. The UI is simple, but effective. It asks you for... 1. Role & Purpose 2. Voice & Style 3. Behavior 4. Rules 5. Tags 6. Avatar image 7. Welcome text. 8. Test drive before publication. ... and that's about it. This free version lets you have at most 3 agents, I am told. This implies that there is also a paid version. I'm all for it, because it sounds to me like VeChain is ready to do real business! I am providing feedback to Jérôme Grillères in order to help improve VeChain's AI agent marketplace. I didn't have to set up anything. The web UI is all I needed! The agent is running on Claude Sonnet 3.7. I did not have to provide a Claude API key. We seem to be riding along on VeChain's. I hope there'll be a choice for more models, including ChatGPT, in the future. This is so user friendly, that I can easily imagine that this would take off in a big, big way. I'm definitely building on this, when it goes into production with full features. Even if my own AI agents aren't successful, then I'm sure others' will be. And that means the $VET / $VTHO / $B3TR flywheel is going to take off in a big, big way. I, for one, am here for it. (See the reply below for the listing of the AI agent I just created.)

₿lackthorne AI

16,741 次观看 • 3 个月前

This guy closes $5K/month managed agent clients and his AI agent does the fulfillment. His agent Dewey builds the client's agent, onboards it into their Slack, and handles the customer support after. Nick Vasilescu watches client problems get solved from his phone while he's on a walk. He came back on the Build With AI podcast to walk through the entire system. Here's what I learned: 1. Agents building agents is here. Dewey built a $5K/month client's agent on Orgo and onboarded it into their Slack himself. 2. The company behind Hermes is hiring forward deployed engineers for enterprise. The SMB and mid-market layer beneath is up for grabs. 3. His agent has its own email, phone, and card. Dewey signed up for Higgsfield and paid for it himself. 4. Customer support runs without him. Dewey sits in iMessage group chats with clients and fixes issues on the fly. 5. The 80/20 stack: a harness (Hermes or OpenClaw), a model, an Orgo computer, Agent Mail, Agent Phone, Obsidian, Honcho for memory, Composio, Latitude. 6. packages the agent card, email, and phone for about $20/month. 7. Templatize once, deploy forever. Save your ideal stack as an Orgo template and one-click clone it for every client. 8. Nobody pays $5K/month for an agent that doesn't make them money. Build the client an agent, then help them resell it to THEIR customers. B2B2B never churns. 9. Skills come from a context dump. The client dumps everything into Slack and Dewey turns the discovery call transcript into skills. 10. Sell to real businesses, not startups. SMBs doing $1M to $2M minimum pay more and ask fewer questions. Nick put Dewey's entire build into a simple blueprint. Anyone can set this up and be texting their agent in under 2 minutes. Grab the blueprint (free) here: His 2 key takeaways: 1. Build is commoditized. The valuable skill is asking the right questions and knowing which tool to point the agent at. 2. Speed to value wins. The same day a client wires money, ship them something. Agent live by day two. Nick is living further in the future than almost anyone I know and round two did not disappoint. Go follow Nick Vasilescu. Full video below. (Also available on the Build With AI podcast wherever you get your pods)

This guy closes $5K/month managed agent clients and his AI agent does the fulfillment. His agent Dewey builds the client's agent, onboards it into their Slack, and handles the customer support after. Nick Vasilescu watches client problems get solved from his phone while he's on a walk. He came back on the Build With AI podcast to walk through the entire system. Here's what I learned: 1. Agents building agents is here. Dewey built a $5K/month client's agent on Orgo and onboarded it into their Slack himself. 2. The company behind Hermes is hiring forward deployed engineers for enterprise. The SMB and mid-market layer beneath is up for grabs. 3. His agent has its own email, phone, and card. Dewey signed up for Higgsfield and paid for it himself. 4. Customer support runs without him. Dewey sits in iMessage group chats with clients and fixes issues on the fly. 5. The 80/20 stack: a harness (Hermes or OpenClaw), a model, an Orgo computer, Agent Mail, Agent Phone, Obsidian, Honcho for memory, Composio, Latitude. 6. packages the agent card, email, and phone for about $20/month. 7. Templatize once, deploy forever. Save your ideal stack as an Orgo template and one-click clone it for every client. 8. Nobody pays $5K/month for an agent that doesn't make them money. Build the client an agent, then help them resell it to THEIR customers. B2B2B never churns. 9. Skills come from a context dump. The client dumps everything into Slack and Dewey turns the discovery call transcript into skills. 10. Sell to real businesses, not startups. SMBs doing $1M to $2M minimum pay more and ask fewer questions. Nick put Dewey's entire build into a simple blueprint. Anyone can set this up and be texting their agent in under 2 minutes. Grab the blueprint (free) here: His 2 key takeaways: 1. Build is commoditized. The valuable skill is asking the right questions and knowing which tool to point the agent at. 2. Speed to value wins. The same day a client wires money, ship them something. Agent live by day two. Nick is living further in the future than almost anyone I know and round two did not disappoint. Go follow Nick Vasilescu. Full video below. (Also available on the Build With AI podcast wherever you get your pods)

Corey Ganim

32,144 次观看 • 2 个月前

save this post to get the most out of unlimited Seedance 2.5 for up to 33 days on Higgsfield i'm going to show you how to use loops to produce ANY video format: ads, cinema, vlogs, UGC, music videos... with one system idea > vault > agent > references > images > script > video > montage > upscaling Seedance 2.5 one-shots a full 30 second video, audio generated in the same pass, carrying up to 30 image, 10 video and 10 audio references into a single generation here's a full breakdown of the setup: > idea: steal taste from work that already worked: - frameset․app and shotdeck․com for film stills - savee․com and cosmos․so for boards - eyecannndy․com for transitions then have a vision model name the lens, light, palette and grain of your picks in one locked paragraph you paste into every prompt > vault: an obsidian folder as your reference bible, one page per asset (idea, locked style, character sheets, reference images, the exact prompts that worked) plus one index page, reviewed after every session so it never rots into dead files > agent: three commands make every model callable from Claude Code: - npm install -g @ higgsfield/cli - higgsfield auth login - npx skills add higgsfield-ai/skills and your agent now submits, polls, retries and logs every job > references: build reference images by hand first, midjourney for cinema and stylized shots, nanobanana pro or gpt images 2 for realism use one locked style across the whole project, recurring characters turned into full sheets (front, side, back, blank background), and once locked you never regenerate them, you fix the motion prompt instead > images: frames before motion, always, a frame costs seconds and a clip costs minutes, so exploration happens at the cheap layer and only winners get animated > script: every shot gets the same six details, subject, action, place, camera, style, rules, and the 30 seconds splits into four timed beats inside one prompt, 0-6 set the scene, 6-14 build it out, 14-24 the turn, 24-30 the end > video: every reference gets a job and a boundary, "Video 1 defines motion and pacing" is half the instruction, "do not use the person's identity, clothing or scene" is the half that stops one reference leaking into shots it was never meant to touch > montage: the cut is a text file, one line per clip with its duration and an audio flag, ffmpeg renders the film from it, so the whole edit reruns in seconds > upscaling: once, at the end, on the finished cut, 720p while exploring, 1080p for keepers, 4K only for the master (use Topaz) for UGC ads, the same loop with two changes render the hook clip alone first, approve the face and the voice before anything else inherits them, then anchor every later clip with the approved hook's audio so one voice carries the whole ad and the script math is fixed, about 3.5 words per second, a 30 second ad is roughly 105 words, counted before anything renders unlimited means every loop above costs nothing to run... start one tonight

save this post to get the most out of unlimited Seedance 2.5 for up to 33 days on Higgsfield i'm going to show you how to use loops to produce ANY video format: ads, cinema, vlogs, UGC, music videos... with one system idea > vault > agent > references > images > script > video > montage > upscaling Seedance 2.5 one-shots a full 30 second video, audio generated in the same pass, carrying up to 30 image, 10 video and 10 audio references into a single generation here's a full breakdown of the setup: > idea: steal taste from work that already worked: - frameset․app and shotdeck․com for film stills - savee․com and cosmos․so for boards - eyecannndy․com for transitions then have a vision model name the lens, light, palette and grain of your picks in one locked paragraph you paste into every prompt > vault: an obsidian folder as your reference bible, one page per asset (idea, locked style, character sheets, reference images, the exact prompts that worked) plus one index page, reviewed after every session so it never rots into dead files > agent: three commands make every model callable from Claude Code: - npm install -g @ higgsfield/cli - higgsfield auth login - npx skills add higgsfield-ai/skills and your agent now submits, polls, retries and logs every job > references: build reference images by hand first, midjourney for cinema and stylized shots, nanobanana pro or gpt images 2 for realism use one locked style across the whole project, recurring characters turned into full sheets (front, side, back, blank background), and once locked you never regenerate them, you fix the motion prompt instead > images: frames before motion, always, a frame costs seconds and a clip costs minutes, so exploration happens at the cheap layer and only winners get animated > script: every shot gets the same six details, subject, action, place, camera, style, rules, and the 30 seconds splits into four timed beats inside one prompt, 0-6 set the scene, 6-14 build it out, 14-24 the turn, 24-30 the end > video: every reference gets a job and a boundary, "Video 1 defines motion and pacing" is half the instruction, "do not use the person's identity, clothing or scene" is the half that stops one reference leaking into shots it was never meant to touch > montage: the cut is a text file, one line per clip with its duration and an audio flag, ffmpeg renders the film from it, so the whole edit reruns in seconds > upscaling: once, at the end, on the finished cut, 720p while exploring, 1080p for keepers, 4K only for the master (use Topaz) for UGC ads, the same loop with two changes render the hook clip alone first, approve the face and the voice before anything else inherits them, then anchor every later clip with the approved hook's audio so one voice carries the whole ad and the script math is fixed, about 3.5 words per second, a 30 second ad is roughly 105 words, counted before anything renders unlimited means every loop above costs nothing to run... start one tonight

Machina

39,183 次观看 • 1 个月前

20 GitHub repos with 2.4M+ combined stars that replace tools costing $60,000+/year 1. public-apis ⭐456k - 1,500+ free APIs across every category, weather to finance to games, all documented. 2. awesome-selfhosted ⭐312k - self-hosted replacements for Notion, Google Photos, Zapier, and dozens more paid subscriptions. 3. hermes-agent ⭐230k - self-improving personal agent with persistent memory, cron scheduling, MCP built in. Free alternative to paid always-on agent platforms. 4. n8n ⭐200k - visual automation with native AI agents. Replaces Zapier/Make entirely, self-hosted. 5. ollama ⭐178k - run Llama, Mistral, DeepSeek locally with one command. No API bill, no rate limits. 6. dify ⭐152k - visual builder for AI agents and RAG pipelines. Skip the $500/mo no-code AI builder subscription. 7. free-for-dev ⭐132k - hundreds of services with permanent free tiers. No trials, no credit card. 8. awesome-llm-apps ⭐132k - 100+ ready AI agents and RAG apps with full code. 9. awesome-mcp-servers ⭐92k - thousands of MCP servers connecting your agent to browsers, databases, anything. 10. supabase ⭐108k - Firebase alternative that's actually free to start. Auth, DB, storage in one Claude Code prompt. 11. strapi ⭐73k - open-source headless CMS, generates a full API from your content model in minutes. No Contentful bill. 12. immich ⭐110k - self-hosted photo and video backup with face recognition. Cancel the Google Photos storage plan. 13. appwrite ⭐57k - complete backend-as-a-service, self-hosted. Auth, DB, functions, storage, one prompt away from Firebase money. 14. medusa ⭐36k - full ecommerce backend, open source. Skip Shopify Plus fees entirely on your next vibe-coded store. 15. novu ⭐39k - notification infrastructure for email, SMS, push, in-app, all in one API. Replaces OneSignal's paid tiers. 16. tooljet ⭐38k - drag-and-drop internal tool builder connected to any database or API. Retool's seat pricing gone. 17. mattermost ⭐38k - self-hosted team chat built for engineering orgs. Slack without the per-seat bill. 18. outline ⭐40k - fast, clean team wiki and docs. Replaces Confluence and Notion's team plan. 19. plausible ⭐28.5k - privacy-friendly analytics, lightweight script, real dashboards. No GA360 contract needed. 20. openwork ⭐22k - open-source Claude Cowork alternative. Share skills and MCPs across Claude Code, Cursor, Codex, one setup for every agent. Save this before you pay for another tool this list already replaces for free 👇

20 GitHub repos with 2.4M+ combined stars that replace tools costing $60,000+/year 1. public-apis ⭐456k - 1,500+ free APIs across every category, weather to finance to games, all documented. 2. awesome-selfhosted ⭐312k - self-hosted replacements for Notion, Google Photos, Zapier, and dozens more paid subscriptions. 3. hermes-agent ⭐230k - self-improving personal agent with persistent memory, cron scheduling, MCP built in. Free alternative to paid always-on agent platforms. 4. n8n ⭐200k - visual automation with native AI agents. Replaces Zapier/Make entirely, self-hosted. 5. ollama ⭐178k - run Llama, Mistral, DeepSeek locally with one command. No API bill, no rate limits. 6. dify ⭐152k - visual builder for AI agents and RAG pipelines. Skip the $500/mo no-code AI builder subscription. 7. free-for-dev ⭐132k - hundreds of services with permanent free tiers. No trials, no credit card. 8. awesome-llm-apps ⭐132k - 100+ ready AI agents and RAG apps with full code. 9. awesome-mcp-servers ⭐92k - thousands of MCP servers connecting your agent to browsers, databases, anything. 10. supabase ⭐108k - Firebase alternative that's actually free to start. Auth, DB, storage in one Claude Code prompt. 11. strapi ⭐73k - open-source headless CMS, generates a full API from your content model in minutes. No Contentful bill. 12. immich ⭐110k - self-hosted photo and video backup with face recognition. Cancel the Google Photos storage plan. 13. appwrite ⭐57k - complete backend-as-a-service, self-hosted. Auth, DB, functions, storage, one prompt away from Firebase money. 14. medusa ⭐36k - full ecommerce backend, open source. Skip Shopify Plus fees entirely on your next vibe-coded store. 15. novu ⭐39k - notification infrastructure for email, SMS, push, in-app, all in one API. Replaces OneSignal's paid tiers. 16. tooljet ⭐38k - drag-and-drop internal tool builder connected to any database or API. Retool's seat pricing gone. 17. mattermost ⭐38k - self-hosted team chat built for engineering orgs. Slack without the per-seat bill. 18. outline ⭐40k - fast, clean team wiki and docs. Replaces Confluence and Notion's team plan. 19. plausible ⭐28.5k - privacy-friendly analytics, lightweight script, real dashboards. No GA360 contract needed. 20. openwork ⭐22k - open-source Claude Cowork alternative. Share skills and MCPs across Claude Code, Cursor, Codex, one setup for every agent. Save this before you pay for another tool this list already replaces for free 👇

unicode

34,424 次观看 • 1 个月前

This guy sells AI employees to small businesses. He's a non-technical designer with no audience, spends $0 on ads, has no tech background. Yet he's still done 21 agent setups in 6 months, almost all from referrals. His model: install one AI agent as a digital employee, then get paid monthly to manage it and coach the owner. Setup fee plus a per-agent monthly rate. Phil came on the Build With AI pod to walk us through the whole playbook. Here's what I learned: 1. The product is the coaching, not the agent. Owners treat AI like Google. You get paid to manage it so they never have to. 2. Raise your price every yes. $500 setups became $1,000. Now he's targeting $2,000 setups plus $1,000/month per agent. 3. Give the agent a value ledger. It logs every task and sends a weekly ROI report. One client's first week: 63 hours saved, $6,300 in value. 4. Put yourself in the group chat. Telegram group with Phil, the client, and the agent. The client learns by watching him talk to it. 5. The agents handle real multi-step work. One prompt: find the invoice email, extract the PDF into Excel, save to Dropbox, send the link. Done in 10 minutes. 6. Uptime is a selling point. The best prospects tried agents themselves and quit when they broke. Phil fixes it before the client notices. 7. Free work is the referral engine. Friends in his small Georgia town told friends in Atlanta and Dallas. Now he has clients nationwide. 8. The pitch is one text. "I'm testing a managed agent service. Want to be a guinea pig? I'll charge you less." First client: $250/month. 9. Make the agent write to Excel, not its own markdown. A shared source of truth is the difference between a demo and a system. 10. Phil builds his agents on Orgo. $29/month gets your agent a computer with pre-built templates. Phil's agent handles the Orgo admin itself. His 2 key takeaways: 1. You only need to be one step ahead. If you've built an agent for yourself, you know more than the owner who never has. Charge from day one. 2. Visible ROI is the retention strategy. A weekly "you saved $6,300" report re-sells the retainer every single week. Phil is doing this at a level most technical people are not, and we had a blast going deep on it. Go follow Phil Full video below. (Also available on the Build With AI podcast wherever you get your pods)

This guy sells AI employees to small businesses. He's a non-technical designer with no audience, spends $0 on ads, has no tech background. Yet he's still done 21 agent setups in 6 months, almost all from referrals. His model: install one AI agent as a digital employee, then get paid monthly to manage it and coach the owner. Setup fee plus a per-agent monthly rate. Phil came on the Build With AI pod to walk us through the whole playbook. Here's what I learned: 1. The product is the coaching, not the agent. Owners treat AI like Google. You get paid to manage it so they never have to. 2. Raise your price every yes. $500 setups became $1,000. Now he's targeting $2,000 setups plus $1,000/month per agent. 3. Give the agent a value ledger. It logs every task and sends a weekly ROI report. One client's first week: 63 hours saved, $6,300 in value. 4. Put yourself in the group chat. Telegram group with Phil, the client, and the agent. The client learns by watching him talk to it. 5. The agents handle real multi-step work. One prompt: find the invoice email, extract the PDF into Excel, save to Dropbox, send the link. Done in 10 minutes. 6. Uptime is a selling point. The best prospects tried agents themselves and quit when they broke. Phil fixes it before the client notices. 7. Free work is the referral engine. Friends in his small Georgia town told friends in Atlanta and Dallas. Now he has clients nationwide. 8. The pitch is one text. "I'm testing a managed agent service. Want to be a guinea pig? I'll charge you less." First client: $250/month. 9. Make the agent write to Excel, not its own markdown. A shared source of truth is the difference between a demo and a system. 10. Phil builds his agents on Orgo. $29/month gets your agent a computer with pre-built templates. Phil's agent handles the Orgo admin itself. His 2 key takeaways: 1. You only need to be one step ahead. If you've built an agent for yourself, you know more than the owner who never has. Charge from day one. 2. Visible ROI is the retention strategy. A weekly "you saved $6,300" report re-sells the retainer every single week. Phil is doing this at a level most technical people are not, and we had a blast going deep on it. Go follow Phil Full video below. (Also available on the Build With AI podcast wherever you get your pods)

Corey Ganim

225,189 次观看 • 1 个月前

Matthew Gallagher Built a $401M Company in Year One with 2 People. And the tool behind it? Claude Code. This year he's on track for $1.8B. Sam Altman predicted this. It's happening now. The problem? It costs money. API credits stack up. Monthly bills keep growing. Every prompt eats your budget. Every project drains your wallet faster. Until now. Two methods. 99% cheaper. One is completely free. Forever. $0. Not a trial. This video breaks down both step by step. ↓ Let me put this in perspective. $100-$500. That's monthly. That's what you spend. That's $6,000/year on API credits. Just to use a tool you haven't shipped anything with. The $401M guy? Spending $0. Same capability. Shipping weekly. Different cost structure. Different results. Different life. I'm about to hand you his cost structure for free. ↓ Open source vs closed source. Pay attention. Closed source: Claude. GPT-4. Pay per token. Meter always running. Open source: Qwen. Llama. Mistral. Free to download. Free to run. Free forever. No meter. No tokens. No bill. Here's what nobody tells you: 80% of coding tasks? Open source handles them. More than handles them. Writes clean code. Debugs errors. Generates boilerplate. Handles routine work perfectly. You're paying premium prices for tasks that don't need premium intelligence. That's hiring a brain surgeon to put on a bandaid. Smart play: Free models for the 80%. Paid credits for the 20%. That's what the $401M guy does. That's what this video teaches you. Follow Himanshu Kumar for more breakdowns that turn free tools into real businesses. ↓ Method 1: Ollama. Local. Free. Forever. Download it. Pull a model. Point Claude Code at it. Done. No internet needed. No API keys required. No monthly subscription. No token counting ever. No bill. Today. Tomorrow. Ever. Your data never leaves your computer. Complete privacy. Complete freedom. Claude Code thinks it's talking to the cloud. It's talking to your laptop. For $0. The video walks through every step: Every config file. Every variable. Every command. Every click. If you can follow a recipe, you can do this. People who set this up 3 months ago? Saved $300-$1,500 since then. Workflow didn't change one bit. ↓ Hardware you need: 16GB RAM: 7B models run smooth. 32GB RAM: 32B models run comfortable. 64GB + GPU: biggest models available. No GPU? Still works. Just slower. Few extra seconds. That's it. Your $1,500 laptop is sitting there running Chrome and Spotify. Put it to work saving you $200/month instead. Follow Himanshu Kumar for more breakdowns that turn free tools into real businesses. ↓ Method 2: Open Router. Free Cloud. No Hardware. Weak machine? Don't want local setup? This method is for you. Free AI models in the cloud. No download. No hardware. Configure Claude Code to route through Open Router. The config: Base URL: Open Router API. API key: free Open Router key. Default Sonnet: free. Default Opus: free. Default Haiku: free. Small fast model: free. Subagent model: free. Free. Free. Free. Free. Free across the board. Same interface. Same commands. Same workflow. Zero cost. Copy the config from the video. Paste it. Save $200/month. Starting today. Right now. ↓ When to use which: Ollama (local): Best for privacy. Best for offline work. Best for unlimited usage. Best if you have decent hardware. Open Router (cloud): Best for weak machines. Best for instant setup. Best for trying different models. Best if you don't want to manage anything. Both methods: Best for 80% of your daily work. Still use paid Claude for: Complex architecture. Multi-file refactoring. Deep reasoning tasks. The 20% that actually needs it. $20/month instead of $200/month. Same output. 90% less cost. ↓ The math that should make you angry. You (current): $200-$500/month. $2,400-$6,000/year. $7,200-$18,000 over 3 years. You (after this video): $20-$50/month. $240-$600/year. $720-$1,800 over 3 years. Savings over 3 years: $6,480-$16,200. That's a used car. That's seed money. That's 6 months of rent. All from one 25-minute video. All from 15 minutes of configuration. Highest ROI 25 minutes you'll spend this year. ↓ The limitations. I won't lie to you. Open source is not Opus. Not as smart on complex reasoning. Not as good at long-context tasks. Makes more mistakes on nuanced problems. But they are: Free. Capable. Getting better monthly. Good enough for 80% of daily work. Smart cost management isn't being cheap. It's being strategic. Expensive tool when it matters. Free tool when it doesn't. ↓ The one-person billion-dollar company is coming. $401M in year one proved it's possible. The building blocks: AI that codes: Claude Code. Way to run it free: this video. Distribution: the internet. Customers: everyone. Only missing ingredient? Someone who builds. Not reads about building. Not saves posts about building. Not bookmarks videos about building. Builds. Tools are free. Knowledge is free. Opportunity is screaming. You're still "thinking about it." ↓ Your action plan: Tonight: Watch the video. Tomorrow morning: Set up Ollama or Open Router. Tomorrow afternoon: Build something. Anything. This week: Build a second thing. Faster. This month: Charge someone for it. One video. One setup. One weekend. $0 cost. Unlimited potential. Or keep paying $200/month for something you could get free. Keep consuming instead of building. Keep planning instead of shipping. Matthew Gallagher didn't plan a $401M company. He built it. Full video attached. Every method. Every config. Every tradeoff. 25 minutes. Your move. Follow Himanshu Kumar for more breakdowns that turn free tools into real businesses.

Matthew Gallagher Built a $401M Company in Year One with 2 People. And the tool behind it? Claude Code. This year he's on track for $1.8B. Sam Altman predicted this. It's happening now. The problem? It costs money. API credits stack up. Monthly bills keep growing. Every prompt eats your budget. Every project drains your wallet faster. Until now. Two methods. 99% cheaper. One is completely free. Forever. $0. Not a trial. This video breaks down both step by step. ↓ Let me put this in perspective. $100-$500. That's monthly. That's what you spend. That's $6,000/year on API credits. Just to use a tool you haven't shipped anything with. The $401M guy? Spending $0. Same capability. Shipping weekly. Different cost structure. Different results. Different life. I'm about to hand you his cost structure for free. ↓ Open source vs closed source. Pay attention. Closed source: Claude. GPT-4. Pay per token. Meter always running. Open source: Qwen. Llama. Mistral. Free to download. Free to run. Free forever. No meter. No tokens. No bill. Here's what nobody tells you: 80% of coding tasks? Open source handles them. More than handles them. Writes clean code. Debugs errors. Generates boilerplate. Handles routine work perfectly. You're paying premium prices for tasks that don't need premium intelligence. That's hiring a brain surgeon to put on a bandaid. Smart play: Free models for the 80%. Paid credits for the 20%. That's what the $401M guy does. That's what this video teaches you. Follow Himanshu Kumar for more breakdowns that turn free tools into real businesses. ↓ Method 1: Ollama. Local. Free. Forever. Download it. Pull a model. Point Claude Code at it. Done. No internet needed. No API keys required. No monthly subscription. No token counting ever. No bill. Today. Tomorrow. Ever. Your data never leaves your computer. Complete privacy. Complete freedom. Claude Code thinks it's talking to the cloud. It's talking to your laptop. For $0. The video walks through every step: Every config file. Every variable. Every command. Every click. If you can follow a recipe, you can do this. People who set this up 3 months ago? Saved $300-$1,500 since then. Workflow didn't change one bit. ↓ Hardware you need: 16GB RAM: 7B models run smooth. 32GB RAM: 32B models run comfortable. 64GB + GPU: biggest models available. No GPU? Still works. Just slower. Few extra seconds. That's it. Your $1,500 laptop is sitting there running Chrome and Spotify. Put it to work saving you $200/month instead. Follow Himanshu Kumar for more breakdowns that turn free tools into real businesses. ↓ Method 2: Open Router. Free Cloud. No Hardware. Weak machine? Don't want local setup? This method is for you. Free AI models in the cloud. No download. No hardware. Configure Claude Code to route through Open Router. The config: Base URL: Open Router API. API key: free Open Router key. Default Sonnet: free. Default Opus: free. Default Haiku: free. Small fast model: free. Subagent model: free. Free. Free. Free. Free. Free across the board. Same interface. Same commands. Same workflow. Zero cost. Copy the config from the video. Paste it. Save $200/month. Starting today. Right now. ↓ When to use which: Ollama (local): Best for privacy. Best for offline work. Best for unlimited usage. Best if you have decent hardware. Open Router (cloud): Best for weak machines. Best for instant setup. Best for trying different models. Best if you don't want to manage anything. Both methods: Best for 80% of your daily work. Still use paid Claude for: Complex architecture. Multi-file refactoring. Deep reasoning tasks. The 20% that actually needs it. $20/month instead of $200/month. Same output. 90% less cost. ↓ The math that should make you angry. You (current): $200-$500/month. $2,400-$6,000/year. $7,200-$18,000 over 3 years. You (after this video): $20-$50/month. $240-$600/year. $720-$1,800 over 3 years. Savings over 3 years: $6,480-$16,200. That's a used car. That's seed money. That's 6 months of rent. All from one 25-minute video. All from 15 minutes of configuration. Highest ROI 25 minutes you'll spend this year. ↓ The limitations. I won't lie to you. Open source is not Opus. Not as smart on complex reasoning. Not as good at long-context tasks. Makes more mistakes on nuanced problems. But they are: Free. Capable. Getting better monthly. Good enough for 80% of daily work. Smart cost management isn't being cheap. It's being strategic. Expensive tool when it matters. Free tool when it doesn't. ↓ The one-person billion-dollar company is coming. $401M in year one proved it's possible. The building blocks: AI that codes: Claude Code. Way to run it free: this video. Distribution: the internet. Customers: everyone. Only missing ingredient? Someone who builds. Not reads about building. Not saves posts about building. Not bookmarks videos about building. Builds. Tools are free. Knowledge is free. Opportunity is screaming. You're still "thinking about it." ↓ Your action plan: Tonight: Watch the video. Tomorrow morning: Set up Ollama or Open Router. Tomorrow afternoon: Build something. Anything. This week: Build a second thing. Faster. This month: Charge someone for it. One video. One setup. One weekend. $0 cost. Unlimited potential. Or keep paying $200/month for something you could get free. Keep consuming instead of building. Keep planning instead of shipping. Matthew Gallagher didn't plan a $401M company. He built it. Full video attached. Every method. Every config. Every tradeoff. 25 minutes. Your move. Follow Himanshu Kumar for more breakdowns that turn free tools into real businesses.

Himanshu Kumar

13,677 次观看 • 5 个月前

007: First Light | 35 Minutes of Gameplay and New Details Full Video ▶️ ▪️Coming to PS5, Xbox, PC and Switch 2 on March 27, 2026 ▪️Features large Hitman style environments, hundreds of NPCs, multiple routes and infiltration options with cinematic spectacle of Uncharted ▪️High speed chases, full stealth, shootouts ▪️How you complete objectives in open situations is up to the player ▪️Bond can interact with NPCs through dialogue options ▪️Large variety of interactive tools and objects in levels to distract enemies (ex: finding a lighter and setting a wheelbarrow of hay on fire) ▪️Bond can build up "Instinct" during missions to charm or bluff his way through guards if caught or lure them ▪️Whereas Hitman was more open in what Agent 47 could do (kill anyone), Bond is more restrained and can't fire at will ▪️If the situation changes and enemies are out to kill him, a "LICENSE TO KILL" prompt flashes onscreen, indicating you are now weapons free to eliminate targets ▪️There are moments where you can don disguises that are story specific ▪️Available gadgets from Q like smoke bombs, knock-out darts, hack watch, laser traps, etc ▪️Find resources in levels to power your gadgets ▪️Melee combat is more involved than Hitman, countering, parrying, tossing enemies in a sort of mix between Mad Max and Batman Arkham #007FirstLight #PS5 #Xbox #Steam #Switch2

007: First Light | 35 Minutes of Gameplay and New Details Full Video ▶️ ▪️Coming to PS5, Xbox, PC and Switch 2 on March 27, 2026 ▪️Features large Hitman style environments, hundreds of NPCs, multiple routes and infiltration options with cinematic spectacle of Uncharted ▪️High speed chases, full stealth, shootouts ▪️How you complete objectives in open situations is up to the player ▪️Bond can interact with NPCs through dialogue options ▪️Large variety of interactive tools and objects in levels to distract enemies (ex: finding a lighter and setting a wheelbarrow of hay on fire) ▪️Bond can build up "Instinct" during missions to charm or bluff his way through guards if caught or lure them ▪️Whereas Hitman was more open in what Agent 47 could do (kill anyone), Bond is more restrained and can't fire at will ▪️If the situation changes and enemies are out to kill him, a "LICENSE TO KILL" prompt flashes onscreen, indicating you are now weapons free to eliminate targets ▪️There are moments where you can don disguises that are story specific ▪️Available gadgets from Q like smoke bombs, knock-out darts, hack watch, laser traps, etc ▪️Find resources in levels to power your gadgets ▪️Melee combat is more involved than Hitman, countering, parrying, tossing enemies in a sort of mix between Mad Max and Batman Arkham #007FirstLight #PS5 #Xbox #Steam #Switch2

Shinobi602

167,991 次观看 • 1 年前

HERMES JUST GOT A CHATGPT INTERFACE AND IT IS COMPLETELY FREE. No terminal. No command line. No technical setup that takes half a day to figure out. Here is what just became possible. You can now run Hermes, DeepSeek, Ollama, and OpenClaw from a single clean chat interface. Switch between them in one click. Upload files directly. Attach knowledge bases and notes. Preview code without touching the terminal once. Use it on mobile. Make voice and video calls. All of it. Free. Open source. The setup took one conversation with Hermes itself. Pasted the GitHub link in. Hermes installed Open Web UI in Docker on its own. Connected the API server and gateway automatically. A clean ChatGPT-level interface running entirely on local hardware was live in minutes. No subscription. No data leaving your machine. No API bill at the end of the month. The people who set this up this weekend will have a local AI stack that rivals what most companies are paying $2,000 a month for in cloud infrastructure. The people who wait will keep paying for tools that send their data somewhere they cannot see. Both tools are free. Both are open source. The only thing between you and this setup is the next 30 minutes. Follow CyrilXBT for the exact config, setup steps, and local AI workflows I use to run a full stack without spending a dollar on cloud inference.

HERMES JUST GOT A CHATGPT INTERFACE AND IT IS COMPLETELY FREE. No terminal. No command line. No technical setup that takes half a day to figure out. Here is what just became possible. You can now run Hermes, DeepSeek, Ollama, and OpenClaw from a single clean chat interface. Switch between them in one click. Upload files directly. Attach knowledge bases and notes. Preview code without touching the terminal once. Use it on mobile. Make voice and video calls. All of it. Free. Open source. The setup took one conversation with Hermes itself. Pasted the GitHub link in. Hermes installed Open Web UI in Docker on its own. Connected the API server and gateway automatically. A clean ChatGPT-level interface running entirely on local hardware was live in minutes. No subscription. No data leaving your machine. No API bill at the end of the month. The people who set this up this weekend will have a local AI stack that rivals what most companies are paying $2,000 a month for in cloud infrastructure. The people who wait will keep paying for tools that send their data somewhere they cannot see. Both tools are free. Both are open source. The only thing between you and this setup is the next 30 minutes. Follow CyrilXBT for the exact config, setup steps, and local AI workflows I use to run a full stack without spending a dollar on cloud inference.

CyrilXBT

37,120 次观看 • 5 个月前

One of my best engineers just showed me how to set up OpenClaw securely & without a Mac Mini. Here's his step-by-step: 1) Spin up a VPS on Hetzner It's a virtual server in the cloud. basically a computer you rent for $5-10/month. Pick 8GB RAM, Ubuntu, US East. Takes 2 minutes. 2) Install Tailscale This makes your server invisible to the public internet. Think of it like moving from a house on Google Maps into a gated community where only your devices can get in. Without this, bots start attacking your server within seconds of it going live. 3) Harden the server SSH keys only. Firewall. Intrusion prevention. Auto security updates. CJ actually uses AI to red team his own servers. Tells it to try and break in, then patches whatever it finds. 4) Install OpenClaw🦞 and run the onboarding. You pick your model provider, connect Telegram via BotFather, and configure hooks that give your agent long-term memory. The hooks auto-save sessions and context so the agent gets smarter over time. 5) Set up the gateway This is the piece that makes it actually powerful. It's a message bus that lets your main agent talk to sub-agents, receive messages from Telegram/Discord/Slack, and orchestrate everything. this is what keeps it running 24/7. 6) Hatch your claw and start training it Dump as much info about yourself as possible. tell it your preferences, your workflows, your tools. CJ's agent monitors his email, Slack, and manages his to-do list autonomously. Watch the video for the full break-down & follow CJ Hess for more AI engineering sauce.

One of my best engineers just showed me how to set up OpenClaw securely & without a Mac Mini. Here's his step-by-step: 1) Spin up a VPS on Hetzner It's a virtual server in the cloud. basically a computer you rent for $5-10/month. Pick 8GB RAM, Ubuntu, US East. Takes 2 minutes. 2) Install Tailscale This makes your server invisible to the public internet. Think of it like moving from a house on Google Maps into a gated community where only your devices can get in. Without this, bots start attacking your server within seconds of it going live. 3) Harden the server SSH keys only. Firewall. Intrusion prevention. Auto security updates. CJ actually uses AI to red team his own servers. Tells it to try and break in, then patches whatever it finds. 4) Install OpenClaw🦞 and run the onboarding. You pick your model provider, connect Telegram via BotFather, and configure hooks that give your agent long-term memory. The hooks auto-save sessions and context so the agent gets smarter over time. 5) Set up the gateway This is the piece that makes it actually powerful. It's a message bus that lets your main agent talk to sub-agents, receive messages from Telegram/Discord/Slack, and orchestrate everything. this is what keeps it running 24/7. 6) Hatch your claw and start training it Dump as much info about yourself as possible. tell it your preferences, your workflows, your tools. CJ's agent monitors his email, Slack, and manages his to-do list autonomously. Watch the video for the full break-down & follow CJ Hess for more AI engineering sauce.

Alex Lieberman

65,211 次观看 • 7 个月前

I cut Fable 5 token usage 2.5x with just one change! - Before: 5.5 M tokens · 7 errors · $8.94 - After: 2.3 M tokens · 0 errors · $4.17 The final build was the same for both, but the path the agent took wildly differed. In both runs, the agent started with the same thing, i.e., it understood the backend before building anything, like: - Permission policies - Available storage buckets - Auth providers configured - How edge functions are deployed The first run used Firebase, which was built for a human dev using a dashboard. While the dev can read the above state by clicking through tabs, an agent has no dashboard. So it gathered the same info through API calls. And there's no single Firebase call that returned this info. The agent required to query multiple times, and each query over-returned. For instance, when the agent asked how sign-in is configured, Firebase also returned the entire auth surface and every method it supported. This was far more context than what it needed. And it repeated across every part of the backend it inspected. Some states (like which auth providers are active) weren't queryable at all. I provided it myself. Otherwise, the agent would have guessed. Errors further compounded the token usage. When a dev sees "permission denied," they can look at the console and figure out whether it's a rule, a path, or an unauthenticated request. Firebase returned the same string to the agent as well, and it had none of that surrounding context to debug. So it guessed again, picked the most likely cause, and rewrote code, utilizing more tokens. This Firebase setup cost me 5.5M tokens and 7 manual interventions during errors on a full-stack RAG app. But I brought that down to 2.3M tokens and 0 manual interventions by using InsForge as the backend context engineering layer (open-source and self-hostable via Docker). It provides the same primitives as Supabase/Firebase, but structures the entire information layer for agents, instead of dashboards. In one CLI call that consumed ~500 tokens, the agent saw the full backend topology before writing a single line of code. This included auth, database, storage, edge functions, model gateway, micro VMs, and deployment. Also, instead of loading the entire product surface into context on every task, four narrowly scoped skills activated only when relevant to keep cognitive load minimal. And to ensure efficient retries if needed, every CLI operation returned structured JSON with meaningful exit codes, so the agent never guessed what to do next. Here's the InsForge GitHub Repo: (don't forget to star it ⭐) The video below depicts the final build, comparing Firebase and InsForge. To dive deeper, I recently published a full walkthrough building the same RAG app on both backends and inspected them end-to-end. Read it below.

I cut Fable 5 token usage 2.5x with just one change! - Before: 5.5 M tokens · 7 errors · $8.94 - After: 2.3 M tokens · 0 errors · $4.17 The final build was the same for both, but the path the agent took wildly differed. In both runs, the agent started with the same thing, i.e., it understood the backend before building anything, like: - Permission policies - Available storage buckets - Auth providers configured - How edge functions are deployed The first run used Firebase, which was built for a human dev using a dashboard. While the dev can read the above state by clicking through tabs, an agent has no dashboard. So it gathered the same info through API calls. And there's no single Firebase call that returned this info. The agent required to query multiple times, and each query over-returned. For instance, when the agent asked how sign-in is configured, Firebase also returned the entire auth surface and every method it supported. This was far more context than what it needed. And it repeated across every part of the backend it inspected. Some states (like which auth providers are active) weren't queryable at all. I provided it myself. Otherwise, the agent would have guessed. Errors further compounded the token usage. When a dev sees "permission denied," they can look at the console and figure out whether it's a rule, a path, or an unauthenticated request. Firebase returned the same string to the agent as well, and it had none of that surrounding context to debug. So it guessed again, picked the most likely cause, and rewrote code, utilizing more tokens. This Firebase setup cost me 5.5M tokens and 7 manual interventions during errors on a full-stack RAG app. But I brought that down to 2.3M tokens and 0 manual interventions by using InsForge as the backend context engineering layer (open-source and self-hostable via Docker). It provides the same primitives as Supabase/Firebase, but structures the entire information layer for agents, instead of dashboards. In one CLI call that consumed ~500 tokens, the agent saw the full backend topology before writing a single line of code. This included auth, database, storage, edge functions, model gateway, micro VMs, and deployment. Also, instead of loading the entire product surface into context on every task, four narrowly scoped skills activated only when relevant to keep cognitive load minimal. And to ensure efficient retries if needed, every CLI operation returned structured JSON with meaningful exit codes, so the agent never guessed what to do next. Here's the InsForge GitHub Repo: (don't forget to star it ⭐) The video below depicts the final build, comparing Firebase and InsForge. To dive deeper, I recently published a full walkthrough building the same RAG app on both backends and inspected them end-to-end. Read it below.

Avi Chawla

113,307 次观看 • 3 个月前

After years of being absolutely tortured by expensive ad creative pipelines, I think I finally found the ultimate savior for brand growth. Most AI video tools are great at generating flashy but random clips. The real challenge starts when you need to produce high-converting ecommerce content at scale without burning your budget. I’ve been testing Wizstar_official, and it honestly feels less like a simple AI generator and more like serious production infrastructure for scaling digital businesses. What stood out to me is how their ecosystem completely automates the two biggest bottlenecks in growth marketing: Bulk Testing and Creative Adaptation. First, their Agent setup paired with Fast Mode is a cheat code for volume. Instead of spending days scripting and storyboarding, the system intelligently extracts your product selling points, writes algorithm-friendly influencer scripts, and batch-produces massive ad variations in one day. It’s ultra-low-cost, built for rapid listing, and keeps your brand logos and product textures 100% consistent and lossless across the board. Second, the Video Reference workflow is an absolute game-changer. Instead of rebuilding every ad from scratch or guessing what works, you can reference any existing successful e-commerce video. The AI reverse-engineers its exact pacing, structure, camera movement, and storytelling style, and applies that winning DNA to a completely different product. That completely changes the production workflow from: prompt → random output into something closer to: reference → structured production → scalable content system Under the hood, Wizstar doesn't just rely on one platform; it supports flexible multi-model orchestration. Driven by their newly integrated Seedance 2.0 engine, it allows direct face input, meaning your character consistency and scene continuity stay rock-solid with absolutely none of that creepy AI face warping across complex cuts. If you are running global campaigns, you can also utilize their Video Translation tool to flip master clips into 12 languages with flawless, natural lip sync in minutes. ✨ New users get free credits upon registration 💸 First month subscription is only $19 (includes a complimentary 30-second E-commerce Agent experience to test features like Product to Video) Stop letting slow pipelines bottleneck your global growth. Try it here: #Wizstar #GrowthMarketing #AIVideo

FELIX

97,682 次观看 • 4 个月前

$10,000/yr Recovered!!! I Built an AI Agent for a Car Mechanic (and am crazy for giving it away for free) The owner of this local repair shop gets tons of quote requests via email, but most are missing key details for the car (make, model, year). He only checks emails after work, so incomplete requests create a 24-48 hour delay just to ask for basic info. "I lose customers because of that delay," he told me. So I built him an AI email triage agent with n8n that: → Scans every inquiry the second it arrives → Instantly replies asking for missing details if needed → Texts him a summary when quotes are ready to process → Logs everything for tracking The result? His inbox is now full of "quote-ready" emails by the time he gets out from under the hood. No chasing customers, no wasted time, thousands in recovered sales. The best part? This system works for any service business that handles quote requests via email. With 230,000+ auto repair shops in the US alone (most with zero AI and zero automation), this represents a massive opportunity for automation consultants. I just dropped the full 25-minute build tutorial on YouTube, breaking down every component. Want the complete n8n workflow template? 1. Retweet & Like this post 2. Follow me so I can DM you 3. Comment "MECHANIC" I'll send you the entire system for free, a full setup walk-through video, including all of the prompting and the JSON output.

$10,000/yr Recovered!!! I Built an AI Agent for a Car Mechanic (and am crazy for giving it away for free) The owner of this local repair shop gets tons of quote requests via email, but most are missing key details for the car (make, model, year). He only checks emails after work, so incomplete requests create a 24-48 hour delay just to ask for basic info. "I lose customers because of that delay," he told me. So I built him an AI email triage agent with n8n that: → Scans every inquiry the second it arrives → Instantly replies asking for missing details if needed → Texts him a summary when quotes are ready to process → Logs everything for tracking The result? His inbox is now full of "quote-ready" emails by the time he gets out from under the hood. No chasing customers, no wasted time, thousands in recovered sales. The best part? This system works for any service business that handles quote requests via email. With 230,000+ auto repair shops in the US alone (most with zero AI and zero automation), this represents a massive opportunity for automation consultants. I just dropped the full 25-minute build tutorial on YouTube, breaking down every component. Want the complete n8n workflow template? 1. Retweet & Like this post 2. Follow me so I can DM you 3. Comment "MECHANIC" I'll send you the entire system for free, a full setup walk-through video, including all of the prompting and the JSON output.

David Roberts

143,057 次观看 • 1 年前

If you’re visiting Kyoto, here’s a perfect day trip you probably didn’t expect. A route where you can visit the Nintendo Museum, eat amazing mazemen, and see a World Heritage site — all in one day. Nintendo Museum — About 30 minutes by train from Kyoto Station. Tickets are distributed by lottery, and applications open three months in advance, so reservations are essential. On weekends and holidays, the odds can be 30 to 1 or even higher, making it one of the most competitive tickets in Japan. When I finally visited, it brought back so many memories. All the games I used to play as a kid kept appearing one after another. I even tried Mario Kart with a giant controller and somehow got first place🤣 The shop is full of exclusive items you can only buy here, and I definitely bought way too many T-shirts haha. Seikou Udoku — About 4 minutes by taxi or 20 minutes on foot from Nintendo Museum. I was looking for a good ramen spot in Uji and decided to try this place. It turned out to be really good. Their spicy mazemen is seriously addictive. After finishing the bowl, I immediately thought, “I want to come back again.” If you like spicy food or curry-style flavors, I highly recommend it. It’s also very highly rated, so it’s easy to see why locals love it. Byodo-in Phoenix Hall — About 7 minutes by taxi or 20 minutes on foot from Seikou Udoku. A UNESCO World Heritage site, famous for appearing on the 10-yen coin. The building looks like it’s floating on the pond, and the view is absolutely beautiful. I’ve visited several times, and every time I come back, I’m impressed all over again. If you visit Kyoto, this is a place you shouldn’t miss. Uji turned out to be a much more packed and rewarding day than I expected. I’ve attached a video from my previous visit, so feel free to check it out.

If you’re visiting Kyoto, here’s a perfect day trip you probably didn’t expect. A route where you can visit the Nintendo Museum, eat amazing mazemen, and see a World Heritage site — all in one day. Nintendo Museum — About 30 minutes by train from Kyoto Station. Tickets are distributed by lottery, and applications open three months in advance, so reservations are essential. On weekends and holidays, the odds can be 30 to 1 or even higher, making it one of the most competitive tickets in Japan. When I finally visited, it brought back so many memories. All the games I used to play as a kid kept appearing one after another. I even tried Mario Kart with a giant controller and somehow got first place🤣 The shop is full of exclusive items you can only buy here, and I definitely bought way too many T-shirts haha. Seikou Udoku — About 4 minutes by taxi or 20 minutes on foot from Nintendo Museum. I was looking for a good ramen spot in Uji and decided to try this place. It turned out to be really good. Their spicy mazemen is seriously addictive. After finishing the bowl, I immediately thought, “I want to come back again.” If you like spicy food or curry-style flavors, I highly recommend it. It’s also very highly rated, so it’s easy to see why locals love it. Byodo-in Phoenix Hall — About 7 minutes by taxi or 20 minutes on foot from Seikou Udoku. A UNESCO World Heritage site, famous for appearing on the 10-yen coin. The building looks like it’s floating on the pond, and the view is absolutely beautiful. I’ve visited several times, and every time I come back, I’m impressed all over again. If you visit Kyoto, this is a place you shouldn’t miss. Uji turned out to be a much more packed and rewarding day than I expected. I’ve attached a video from my previous visit, so feel free to check it out.

KODAI GO🇯🇵

11,003 次观看 • 6 个月前