Hey everyone, I am currently looking forward to connect with some E-com coaches. If you know any E-com coach with whom you can connect me with. Then you can DM me on Skool or email me at - munawar.017m@gmail.com

OpenAI engineers use a prompt technique internally that most people have never heard of. It's called reverse prompting. Most people write prompts like this: "Write me a strong intro about AI." The result feels generic. This is why 90% of AI content sounds the same. You're asking the AI to read your mind. The Reverse Prompting Method: Instead of telling the AI what to write, you show it a finished example and ask: "What prompt would generate content exactly like this?" The AI reverse-engineers the hidden structure. AI models are pattern recognition machines. When you show them a finished piece, they can identify: Tone, Pacing, Structure, Depth, Formatting, Emotional intention Then they hand you the perfect prompt. https://www.agenticworkers.com/reverse-prompt-engineer Here's a tool that lets you pass in any text and it'll automatically reverse it into a prompt that can craft that piece of text content.

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An automation agency was stuck at $5K/mo. I showed them a clean path to an extra $20K/month in pipeline. They tried everything — ads, cold calling, more volume, more templates. Pipeline didn’t move an inch. They were blasting 200+ emails/week. Generic. Forgettable. Messages that could’ve gone to anyone. Result? 0.9% reply rate. Maybe 1 SQL/month on a “good” month. And they wondered why outbound “doesn’t work anymore.” So I rebuilt the entire thing from scratch (I was using for myself). I built a Python-based outbound engine that: Pulls the prospect’s latest posts (real-time intent) Extracts the pain they’re literally talking about online Crafts ROI-driven pitches (“Cut CAC 25%… improve LTV:CAC to 3x…”) Sends personalized outreach at scale without slowing down Here’s what changed: Before → 200 emails/week 1% reply 1 SQL After → 150 emails/week 6% reply 8 SQLs Same effort. 6× more pipeline. Let’s do the math: 8 SQLs × $2,500 ACV = $20,000 added pipeline Close rate didn’t change → more revenue, automatically. Why the jump? Because we fixed the only 3 levers that actually matter: Target. Copy. Offer. Everything else is noise. Here’s the real principle: Relevance scales replies. Generic outreach → 1% Signal-targeted outreach → 8% This is literally the difference between: Empty calendar vs Consistent weekly calls Most agencies can’t break their revenue plateau because: Their ICP is “anyone who might need us” Their message fits 1,000 companies Prospects delete it in 3 seconds Your real competition isn’t other agencies. It’s the delete key. If your agency is stuck: It’s not your service. It’s not your pricing. It’s not the market. It’s your outbound strategy. Fix outbound → everything compounds. (P.S. Currently talking to them to fix their offers. Wish me luck)

There's a number of repos like this. Now with Claude Code, Codex, Antigravity, cto.new , Cursor, and all these other Agentic IDE's on the market, I imagine the utility of these repos will only go up with time https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main You could create a full blown SaaS (with costs) out of any of these multi-agent builds, especially since it's open source and you only get charged for API + cloud use I've run a few Perplexity reports on these agents, they're remarkably competitive. There's people out there collecting arbitrage on these purely out of market ignorance. Heavy hitters all around A few highlights: (Junior) Real Estate Agent Team - Scrapes for properties, evaluates them based on scoring criteria, and creates a report for you. When I renew my real estate license in April, I'll be coming back to this AI Services Agency Team - 5 agents that would work in any services-based business. CEO (strategy) CTO (architecture mapping) Product manager (strategy + architecture, product market fit) Developer agent (implementation guide) Client success agent (GTM strategist) Built on top of CrewAI, IBM and NVIDIA's architecture of choice. They got over $18M in funding for this, and you could import it for free RAG-as-a-Service - Imagine you could point a laser and that laser just generates a memory lake for LLMs to feed from. That's the promise behind this one. There's over a hundred companies that have this as their core offering, and they EAT with a handful of a clients