AI for social posts sounds like salvation. Write prompt, get text, publish. In reality, most get stuck with generic posts that all sound the same. Issue: AI generates statistically probable text. Probable = average.
But those who get real results use AI differently.
Why AI Output Feels Generic
AI trained on millions of texts defaults to statistically common patterns. "In today's world, communication is important..." — statistically common, creatively dead.
To break out: give model context. Who are you, for whom, what's specific about your view. Without this, AI guesses.
Workflow That Works
Step 1: Generate angles from your topic (not full posts). "Give me 10 angles on productivity." Pick 2–3 that resonate.
Step 2: Create draft for one angle with detailed context about your audience and your voice.
Step 3: Edit heavily. This isn't optional. You remove corporate speak, add personality, cut clichés.
Step 4: Adapt for platform if needed.
Time: 20 minutes for quality post. Better than hours manually, worse than just hitting publish on AI output.
Where AI Fails
Personal stories — AI invents plausible fakes. You write your own.
Humor on social media — AI misses cultural nuance and tends to fall flat.
Opinions on current events — needs real reaction, AI lags.
These 40% of content should be fully yours. Let AI handle 60% that's structural or rework-able.
Tools That Help
ChatGPT for raw generation and ideas.
Claude for better tone maintenance.
Voxplit for adapting existing content across platforms (repurposing, not generation).