Despite being heavy AI users, these speakers show minimal GPT-distinctive vocabulary and speak in highly informal patterns—the opposite of what academic speakers showed post-ChatGPT. Notably, the Anthropic engineer speaks the most informally of all.
Understanding the Metrics
- Formality Ratio
- Formal markers ÷ informal markers. Higher = more polished, AI-like speech. Lower = more casual, human conversation. The group average is 0.02 (very informal).
- "Like" Rate
- How often speakers say "like" as a filler word. High usage suggests spontaneous, unscripted speech, something AI doesn't do.
- Vocabulary Diversity
- Percentage of unique words used. Higher = richer, more varied language.
Speaker Rankings
Most Formal
Closest to AI-like speech patterns
Most Informal
Most natural, conversational speech
Highest "Like" Usage
Most spontaneous, unscripted delivery
Richest Vocabulary
Greatest variety of unique words
Speaker Comparisons
Formality Ratio
Higher values indicate more AI-like speech patterns. Top speakers highlighted.
Informal Speech Rate
Markers per 1,000 words. AI company employees (Anthropic, Notion) highlighted in red.
"Like" Usage Rate
Filler word frequency—a spontaneity indicator. High users highlighted.
Complete Speaker Data
| Speaker | Org | Words | Informal* | Formal* | Ratio† | "Like"* | Profile‡ | GPT |
|---|
*Per 1,000 words.
†Formal ÷ Informal; higher = more AI-like.
‡Bars show informal rate, "like" rate, vocabulary diversity. Red = outlier.
Methodology
Analysis applies the methodology from Yakura et al. (2024) "Empirical evidence of Large Language Model's influence on human spoken communication" to a Vibe Code Camp livestream transcript.
Metrics: GPT Word Rate (top-20 ChatGPT-distinctive words per Yakura), Formal/Informal marker rates, "Like" usage as spontaneity indicator.
Excluded: Three co-presented sessions (Natalia Quintero & Nityesh Agarwal, Logan Kilpatrick & Ammaar Reshi, Kevin Rose & Kieran Klaassen) were removed because speech could not be individually attributed.
Note: The only GPT word found ("intricate," Tina He) appears in natural context, not as meta-commentary about AI language.