DegenSing

I tested 7 AI tools on my own Twitter account this year. Most made me sound like everyone else. The ones that grew it? They trained on how I actually write. Full scorecard, pros, cons and pricing for all 7 👇

Two links if you want to go deeper: Free 30-second gut-check on how AI-average your drafts read: The full category-by-category comparison of all 7 tools: Which one are you using right now? Curious what is working for you.

His image posts earn 4x his text posts. 1.3k avg vs 321. And yet 64% of what he posts is still plain text. The lever is right there, half-used.

Reach and resonance are different games. A like is a nod. A comment means you sounded like a person. That's the whole point of audenAI: write in your voice, get replies.

The tell: 86% of his engagement is one tap. Reactions 85.5%, comments 10.4%. Reach without conversation.

Hooks: bold statements (698 avg) beat stats (605). Say it with a spine, not a stat.

Two links if you want to go deeper:
Free 30-second gut-check on how AI-average your drafts read:
The full category-by-category comparison of all 7 tools:
Which one are you using right now? Curious what is working for you.

I tested 7 AI tools on my own Twitter account this year. Most made me sound like everyone else.
The ones that grew it? They trained on how I actually write.
Full scorecard, pros, cons and pricing for all 7 👇

The pattern: he commits. An edge, a format, a rhythm. Break down any creator you follow the same way, free. Then write it in your own voice:

He posts images, not paragraphs. 84% of his posts are quote-cards. They pull ~5x his plain text. Same words. Better wrapper. More reach.

He picks a side. 1,787 comments on his best post. Strong opinions start arguments. Arguments are reach. Vague takes get ignored.

Demo:

everyone's shipping faster. that's the problem.
vibe coding, no-code, ai scaffolding. the floor dropped out. a working app in 48 hours is table stakes now.
so why are most products still broken?
because "working" means two different things:
• working code runs without errors.
• working products run without confusion.
• working code passes the build.
• working products survive the second session.
one is a technical bar. the other is a human one.
founders optimized for the first bar and called it shipping. then wondered why retention was flat and support queues were full.
the real cost of shippi

a founder i know spent 8 months building on a no-code platform. beautiful UI. fast to ship. clients loved the demo. then the platform pivoted its pricing. then a core feature got deprecated. then the workarounds started stacking up. by month 11, he had a codebase nobody wrote

a founder i know spent 8 months building on a no-code platform.
beautiful UI. fast to ship. clients loved the demo.
then the platform pivoted its pricing.
then a core feature got deprecated.
then the workarounds started stacking up.
by month 11, he had a codebase nobody wrote and nobody owned.
here's what nobody says about no-code tools: they don't fail because of technical limits.
they fail because they solve the wrong problem.
coordination, not code, is what kills most teams. who owns the logic? who decides when a rule changes? who fixes it at 2am?
boring spreadsheets outlast shiny builders