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.

Here's the prompt I used on Agentic Workers with Claude Opus 4.5 + Nano Banana Image generation. "Create a image of a McKinsey Style powerpoint slide of the current market condition. Do some research before that first."

Ever wonder why the narrative around AI hasn't shifted even though Google's stock is up 67% this year?! (I should have bought GOOG instead of BTC) Everyone's still anchored to 2023: OpenAI leads, Anthropic innovates, everyone else chases. That story died somewhere between Gemini 3 and the TPU deployment numbers. Here's what actually happened: Gemini stole 8 percentage points of market share from ChatGPT in 12 months. Developers are literally ripping out OpenAI integrations mid-project to switch models. This is why its important to use tools like Agentic Workers where you can easily change models Anthropic just committed to over 1 million TPUs for Claude. They ran the numbers on H100s, Trainium, everything. Google won. By 30-40% better price-performance at the scale needed to train frontier models. Think about what that means.... Google's the only company that owns the entire stack, from silicon to software to distribution. When Nvidia raises H100 prices? Microsoft's AI margins compress. When Google raises TPU prices? That's pure rent extraction on hardware they already amortized. Microsoft has distribution but rents compute. OpenAI has models but rents infrastructure. Anthropic has models and... that's it. Google has all the layers. Google Cloud just posted high-growth profitability. Azure and AWS are still subsidizing AI workloads to buy market share because they don't control their compute costs the way Google does. The market sees a search company having a good quarter. The fundamentals show an AI infrastructure monopoly that happens to print $200B annually in search revenue while building the compute layer every AI application will eventually run on.

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Today, I'll be showing you how to get your first AI Automation client without starting an agency. These days, everyone thinks they need to start a full blown AI Agency to succeed, but that's simply not true. So in this video I'll be revealing how to get your first AI automation client without starting an agency, and the exact strategy I'd use myself if I was starting again WITHOUT a YouTube channel. Hope you enjoy!