What's the simplest workflow for creating a blog post with AI without it sounding generic?

The simplest workflow that avoids generic output is a three-step process: you create the outline and key stories, the AI writes a rough draft, and then you inject the specifics that only you know. Skipping the first step is where everyone goes wrong. If you ask an AI to "write a blog post about productivity," you'll get a listicle of obvious tips anyone could guess. That's because the AI is working from common patterns, not your unique angle. Instead, start by writing a messy outline yourself. Just bullet points. Include one real story or example from your own life. For instance, if you're writing about productivity, don't say "time blocking helps." Say "last Tuesday I blocked 9-11am for deep work and finished a proposal that had been sitting for a week." That specific detail is the anchor. Feed that outline to the AI and say "expand each bullet into 2-3 sentences using a helpful, direct tone." The AI will flesh out the structure you provided, but the core insight—your Tuesday morning story—remains yours. The final step is a read-through where you add one more personal comment or a slightly messy analogy. That's the human fingerprint. This method is fast but keeps the soul in the piece. If the prompt-writing part still feels like a chore, our guide on AI content creation workflow walks through this in more detail. **Related**: How many prompts does it take to write a good AI blog post? | What's the difference between AI for drafting vs AI for final copy?