xpost·Content and growth
3,282 posts, eight questions each
I gave Jev 3,282 of my X posts across 100M views and asked it to find what actually works for growth. 4,252,330 tokens $0.1282 for the full 8m 34s run! Each post got 8 questions about the topic, hook, tone, whether it teaches something, etc. How-to posts got 150 median likes vs the average median of 44. AI and coding was a 1.9x multiplier topic compared and SEO, despite recent posts, was right at base median 1.0x - surprisingly. The recommended topic + angle + voice formula was: AI coding + teach something + provocative
Open X (@iannuttall) ⚡ 8 m 34 s · $0.1282
Ian Nuttall
@iannuttall
I gave Jev 3,282 of my X posts across 100M views and asked it to find what actually works for growth. 4,252,330 tokens $0.1282 for the full 8m 34s run! Each post got 8 questions about the topic, hook, tone, whether it teaches something, etc. How-to posts got 150 median likes vs the average median of 44. AI and coding was a 1.9x multiplier topic compared and SEO, despite recent posts, was right at base median 1.0x - surprisingly. The recommended topic + angle + voice formula was: AI coding + teach something + provocative
Evaluate input state with calibrated confidence (latency: 8 m 34 s, cost: $0.1282)
Jev sits between the incoming context and the next system action. Rather than generating lengthy, slow natural language that requires brittle regex parsing, Jev returns non-autoregressive, calibrated probabilities that downstream code can immediately execute.
01actionPrimary action
02confidenceConfidence score
03fallbackFallback route
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