---
type: "synthesis"
sources: ["cross-day"]
tags: ["taxonomy", "creative-roles", "ai-application"]
id: "arc-generation-curation-analysis-modes"
---
## The corpus's three creative roles for AI

A latent taxonomy emerges across the six videos: AI is doing one of three fundamentally different jobs. Most workflows chain two or three.

## Mode 1 — GENERATE (produce net-new artifacts)

AI produces content that didn't exist before.

- [[framework-six-hook-patterns]] (Alex) — six psychological hook patterns rendered per request.
- [[concept-beat-image-video]] (Alex) — script-to-storyboard image and video generation.
- [[concept-face-lock]] (Alex) — identity-preserving thumbnail variants.
- [[concept-remotion]] (Sabrina) — React-coded motion graphics generated by Claude Code.
- [[concept-ai-technical-seo]] (Tim, via Arvow) — fully formatted SEO articles.

**Strength:** scale. **Weakness:** generic output without strong grounding (the [[arc-brand-voice-extraction-spectrum]] problem).

## Mode 2 — CURATE / REWRITE (transform an existing artifact into a new one)

AI does *not* invent; it identifies high-signal source material and translates it.

- [[concept-viral-outlier-spotting]] (CCC) — quantitative filter (≥5× baseline) finds high-performing reels.
- [[concept-knowledge-base-priming]] (CCC) — rewrites scraped transcripts into the user's voice. **Explicitly anti-generation:** see [[contrarian-ai-generation-vs-rewriting]].
- [[concept-rss-to-social-pipeline]] (Tim) — long-form blog post → multi-platform social copy.
- [[claim-automated-blooper-removal]] (Sabrina) — transforms raw footage into edited clip via Whisper + FFmpeg.

**Strength:** quality (you're building on proven signal). **Weakness:** dependency on having something worth rewriting (and possible attribution / IP issues).

## Mode 3 — ANALYZE (extract structure or insight from a corpus)

AI produces understanding, not content.

- [[concept-ad-library-strategic-analysis]] (Dara) — competitor ad library → messaging pillars + inferred personas.
- [[framework-persona-research-automation]] (Dara) — customer reviews → persona deck with verbatim quotes.
- [[action-automate-social-reports]] (Dara) — cross-platform performance → strategic recommendations.
- [[action-competitor-reel-analysis]] (Dara) — competitor reels → pattern detection (celebrity collabs, founder-led content).

**Strength:** Decision-grade insight at speed. **Weakness:** hallucination risk (verbatim-quote requirements help, but don't eliminate).

## How the modes chain

A mature workflow often goes Analyze → Curate → Generate:

1. **Analyze** competitors and audience (Dara) → identify gaps.
2. **Curate** proven outlier content (CCC) → adapt structure.
3. **Generate** brand-voiced output (Alex / Sabrina / MAG / Tim) → publish.

## How to use this taxonomy in answers

When a user describes their pain, classify the underlying job:

- "I need ideas" → Analyze, not Generate. Push toward [[framework-persona-research-automation]] or [[concept-viral-outlier-spotting]].
- "I need 250 posts a week" → Curate + Generate. Push toward [[framework-content-automation-workflow]] and [[concept-knowledge-base-priming]].
- "I need to understand my market" → Analyze. Push toward [[action-analyze-ad-libraries]] and [[concept-ad-library-strategic-analysis]].

Most creators conflate the three. The corpus's hidden lesson is that they are different jobs with different success criteria.