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Right now everyone is trying to crack AI static ads the same way. JSON prompts. 4 different LLMs. Copy-pasting between tools. Tweaking parameters. Debugging hands. Fixing garbled text. Spending 45 minutes on one ad that still needs a designer to clean up. I know because I built that exact workflow. I shared it publicly. 859 people wanted it. And then I stopped using it. Here is what most people are doing right now: 1. Write a detailed JSON prompt with product specs, persona, angle, layout. 2. Feed it to GPT or Gemini for the image. 3. Realize the text is wrong. 4. Open Canva or Figma to fix it. 5. Try again with a different model. 6. Repeat 10 more times. 6 steps. 4 tools. 45 minutes. One static ad. Here is what I do now: Pick a product. Pick a theme. Pick an angle. Click generate. Launch. 3 clicks. Done. No JSON. No prompt engineering. No bouncing between tools. The strategic thinking is already built into the system. Hooks. Layouts. Visual hierarchy. What actually converts on Meta. Trained on what we have learned managing millions in ad spend across 150+ brands. This is the difference between engineering a prompt and engineering a system. One makes you feel productive. The other makes you profitable. I put together a breakdown showing exactly how the old prompt workflow compares to the 3-click system we use now. Comment "STATIC" and I will send it over.

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🚨 This is probably the largest resource I've ever shared. Throughout 2025, my team and I have been keeping something very concrete: Winning Email Templates. Not to be inspired. Emails from top brands from the USA, Australia and Europe that sell every day. Today I decided to give it all together. 👉 I've created a library with 250+ EDITABLE EMAIL TEMPLATES. Each email has the original of the brand and, next to it, the version converted into a template so that you can adapt it to your design and branding in less than 5 minutes. Everything organized in Figma, so you finally have a system and don't start from scratch every time. This resource has taken us 1,000+ hours to assemble. It could be sold perfectly for $100 And it saves you dozens of hours of design and testing. I'm giving it away for a very simple reason: 👉 I know how frustrating it is to design emails without a clear system. If this can help you sell more and work with less friction, it's worth sharing. 🎁 To get FREE access: 1️⃣ Connect with me 2️⃣ Comment on "TEMPLATES" 3️⃣ React to this post PS: help me give this resource to more people, share the post with your contacts, it would be a great help!

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I replaced ChatGPT with Claude 4.5. Here's exactly how to get the most out of it: THE MODELS 1 - Claude Opus 4.5 ↳ What: Most capable model for complex reasoning ↳ Use: Advanced code, research, strategic analysis ↳ Best for: Hardest problems requiring deep thinking 2 - Claude Sonnet 4.5 ↳ What: Balanced model for everyday tasks ↳ Use: Writing, editing, summarising, Q&A ↳ Best for: Fast performance with strong output 3 - Claude Haiku 4.5 ↳ What: Fastest model for simple tasks ↳ Use: Quick answers, high-volume work ↳ Best for: Speed and saving credits THE TOOLS 4 - Artifacts ↳ What: Interactive editor inside chat ↳ Use: Build apps, dashboards, documents live ↳ Best for: Real-time collaboration and iteration 5 - Web Search ↳ What: Live internet search with citations ↳ Use: News, pricing, trends, fact-checking ↳ Best for: Current events and real-time info 6 - Analysis Tool ↳ What: JavaScript code execution for data ↳ Use: Process CSVs, create charts, run calculations ↳ Best for: Complex data analysis 7 - File Upload ↳ What: Accepts PDFs, CSVs, images, docs ↳ Use: Review, extract, summarise, analyse ↳ Best for: Multi-format document support 8 - Google Drive ↳ What: Direct access to your Drive files ↳ Use: Search, cite, and pull context ↳ Best for: Connected Google Drive workflows 9 - Projects ↳ What: Organise multiple chats and files ↳ Use: Manage long-term projects, track context ↳ Best for: Multi-session goal tracking 10 - Research ↳ What: Deep web research with synthesis ↳ Use: Market research, competitor analysis ↳ Best for: Research-heavy topics 11 - Claude Code ↳ What: Terminal agent for coding ↳ Use: Build, debug, refactor entire repos ↳ Best for: Developers (Max plan only) 12 - Claude Cowork ↳ What: Agentic assistant for non-coders ↳ Use: Organise files, browse web, automate tasks ↳ Best for: Everyone else (Max plan only) 13 - Long Context ↳ What: Handles 200k+ tokens ↳ Use: Full transcripts, audits, manuals ↳ Best for: Large document analysis 14 - Multimodal ↳ What: Understands text, images, code, audio ↳ Use: Blend visuals with explanations ↳ Best for: Mixed input tasks PROMPT PATTERNS ☑︎ Research: "Research [topic] comprehensively" ☑︎ Content: "Write a [proposal] for [audience]" ☑︎ Artifacts: "Create a [budget tracker app]" ☑︎ Projects: "I'm working on [new strategy]" ☑︎ Cowork: "Organise [folder] by [file type]" ☑︎ Be Specific: Add details and constraints ☑︎ Analysis: "Analyze this [CSV]" + upload ☑︎ Code: "Help me [task] in [Python]" ☑︎ Search: "Latest on [Tesla stock]?" ☑︎ Files: Upload + "Summarise this" ☑︎ Iterate: "Make it more [concise]" I'm using Claude 4.5 for all written tasks. I'm using Gemini 3 for all visual tasks. That's the new power duo in 2026. Want the high-res PDF? 1. Repost ♻️ this to your network 2. DM me the word "Claude" I'll personally send it to you.

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Most founders think building AI agents requires technical skills they don't have. (hint: it doesn't) I hear this constantly. "I'm not a developer." "I don't know how to use APIs." "I can't write code." Here's what actually stops founders: It's not missing technical skills. It's missing architectural thinking. Inside my community, we've been building agents using nothing but growthub.ai No API access. No custom code. Just smart architecture. And here's the pattern I keep seeing: The founders who struggle aren't the ones who can't code. They're the ones building agents like they're building tools. • One Project for content. • Another for client work. • Another for sales. • Another for research. A couple of months later, they're context-switching between 12 different Projects... spending more time managing agents than building business capacity. That's not an autonomous system. That's operational debt in a new format. The founders who break through? They're building around a simple 4-layer setup: 1. Instructions → Who your agent is, what it does, how it behaves 2. Memory → Context it maintains so you don't repeat yourself 3. Knowledge → Documents and files it can search and cite 4. Skills/Knowledge → Reusable capabilities that work across any Project This isn't just about making agents "smarter." It's about making them compound value instead of fragment your attention. A skill built once works everywhere. Memory that builds over time makes every conversation better. Knowledge that's centralized stays current. This is how you architect agents that create capacity for strategic work—not just automate tasks. Want the complete framework? I broke down all 4 layers, showed exactly how to build each component, and mapped the architecture that makes agents scale without code. 1. Connect with me 2. Like this post 3. Comment "AGENT" I'll send the full guide. Let's build.

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