> For the complete documentation index, see [llms.txt](https://oodlz-ai-studio.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://oodlz-ai-studio.gitbook.io/docs/outbound-agents/awareness/1-topics/loop-2-emotive-engine.md).

# Loop 2: Emotive Engine

6 psychological seed states drive a parallel emotional topic engine — calibrated to the brand's specific audience, scored on psychological accuracy not SEO signals.

> **Topics that resonate before they rank — psychological seeds, second-order emotion, audience-specific.**

Loop 2 runs an independent emotional topic engine alongside Loop 1's keyword discovery. It does not use SEO data. Instead, 6 psychological consumer states — pain, aspiration, life moments, social comparison, fear/risk, curiosity — are seeded into a generation step that produces awareness-stage headlines designed to make the reader feel seen, not informed.

## How It Works

The 6 seed states are not used at the surface emotional layer. The engine works at the second-order layer: not "I am stressed" but the private shame underneath the stress; not "I want to retire" but the longing for self-respect underneath the want. The seeds are generated with full awareness of the brand's audience portrait — the actual human being the brand serves, not a generic lifestyle string.

Each seed produces topic headlines compressed to a maximum of 10 words in Title Case, written for emotional accuracy rather than SEO ranking. Emotional topics carry source `emotional`, search volume 0, and a neutral keyword difficulty of 50 — DataForSEO validation does not apply to intent-based content. Appeal scoring runs on psychological accuracy and rawness, not utility or shareability.

The output joins Loop 1's keyword-validated topics in the same downstream pipeline. Both feed into the same clustering, deduplication, balancing, and approval steps.

## What You Get

* 6 psychological seed states covering the breadth of consumer emotional intent.
* Second-order emotional layer — topics target what the audience privately feels, not what they say they feel.
* Audience-portrait calibration — emotional topics are written for the brand's specific human, not a generic demographic.
* Headlines under 10 words in Title Case — written to provoke recognition, not to rank.
* Same downstream pipeline as keyword topics — emotional and rational topics share clustering, dedup, scoring, and approval.