The difference between AI LinkedIn content that performs and AI LinkedIn content that gets ignored comes down to one thing: voice. Here's how to get it right.
How to write LinkedIn posts with AI is a process of providing a specific idea, selecting your voice profile, reviewing the generated draft, and publishing — taking under two minutes per post. It is used to go from idea to published post in minutes without rewriting for tone.
Real examples of what Bloomberry generates.
The worst hiring mistake I made was hiring for skills I didn't have. The thinking was logical: we need X capability, find someone who has it. The problem: I had no way to evaluate how good they actually were, and no framework to manage them effectively. The second-worst hiring mistake: hiring people I liked instead of people who were genuinely excellent. These two failures compound each other. Now I only hire in areas where I understand the craft well enough to recognize excellence — even if I can't do the work myself. And I ask specific, uncomfortable questions about their best and worst work. Hire slow. You'll still make mistakes. Make fewer.
Three steps from idea to published post.
What is the best process for writing LinkedIn posts with AI?
Start with a clear idea, provide context, and refine outputs to match your voice.
What input should I give AI?
Provide a specific idea, examples of your writing, and the intended audience.
How is this different from Buffer?
Buffer handles scheduling, while this system focuses on generating the content itself.
See the content repurposing tool →How do you avoid sounding like AI?
Use voice-matched generation and edit outputs to reflect your natural tone.
What post length performs best?
Medium-length posts that are clear and structured tend to perform well.
Generate posts that match your tone instead of generic AI output.
Drop in an idea and see what Bloomberry generates in your voice.