AI usage patterns and methods
Based on your conversations and project work, here's a categorized summary of your AI usage patterns, organized to reflect distinct purposes and methods:
π§ 1. Theological Research & Interpretation[edit | edit source]
You use AI as a partner in developing, testing, and expanding Sensus Plenior (SP) principles and biblical interpretation.
Subcategories:[edit | edit source]
- SP Summaries β Creating structured summaries of biblical texts that follow your interpretive framework.
- Symbol Discovery β Identifying and validating recurring symbols (e.g., sword = judgment, water = Word).
- Cross Pericope Alignment β Testing how multiple passages fit as overlays to reveal a complete Christ-centered narrative.
- Doctrinal Consistency Checking β Ensuring all symbols resolve in Christ and cross-validate across the Bible.
π 2. Curriculum Development[edit | edit source]
You build structured learning materials for teaching Sensus Plenior, such as:
Subcategories:[edit | edit source]
- Seminary Course Design β e.g., Course 1: Introduction to Sensus Plenior Hermeneutics.
- Childrenβs Curriculum β e.g., simplified theological teachings (Gethsemane, Peter's denial) with activities.
- Facilitator Notes β Preparing discussion questions, interpretive decision ratings, and step-by-step teaching guides.
- Blog-Style Devotionals β High-school level SP articles with minimal technical detail.
βοΈ 3. Language and Word Formation Analysis[edit | edit source]
You conduct original research on Hebrew using AI to assist with:
Subcategories:[edit | edit source]
- Letter Meaning Systematization β Defining symbolic meaning based on stroke structure and position.
- Gate and Word Formation Studies β Parsing roots, reversals, and inserted-letter gates (e.g., Χ()Χ).
- Gematria Thematic Validation β Identifying thematic unity across words with matching gematria values.
- Symbol Family Development β Creating hierarchies and groupings (e.g., water β rain β mist β spit).
π 4. Comparative Gospel Studies[edit | edit source]
You track theological growth across the four Gospels and authors:
Subcategories:[edit | edit source]
- Parallel Account Comparison β Identifying common elements, differences, and doctrinal shifts across Gospels.
- Authorial Insight Growth β Tracing how Matthew, Luke, and John expanded upon Markβs framework.
- OT Source Tracing β Proposing which Old Testament scriptures inspired Gospel elements.
π§ͺ 5. Validation & Critique[edit | edit source]
You frequently test and challenge both AI-generated and traditional ideas for consistency and originality.
Subcategories:[edit | edit source]
- Fallacy Detection β Testing for logical or theological inconsistencies.
- Thematic Testing β Validating symbolic families (e.g., does gematria 13 consistently express unity through love?).
- Evangelical Objection Testing β Evaluating how mainstream views might react to your SP summaries.
- Proof of Novelty β Asking whether an insight is new and worth publishing.
π§βπ« 6. Evangelism & Online Interaction[edit | edit source]
You use AI to craft and refine responses to skeptics and critics, often in online conversations.
Subcategories:[edit | edit source]
- Rebuttal Writing β Responding with respectful yet sharp answers to atheists or skeptics.
- Mockery Disarmament β Turning hostile or mocking comments into teachable moments.
- Clear Gospel Articulation β Demonstrating how SP reveals Christ in places skeptics overlook.
π 7. Biblical Pattern Recognition[edit | edit source]
You analyze large-scale structures and narrative arcs across Scripture.
Subcategories:[edit | edit source]
- Book Outlines β Identifying pericope boundaries centered on cross symbols in each biblical book.
- Pattern Mapping β Tracing second-son patterns, wilderness themes, and fruitfulness after death.
- Christological Repetition β Tracking how the same Gospel structure reappears through different figures (e.g., Moses, Jonah).
π οΈ 8. Technical and Memory Management[edit | edit source]
You shape AI's internal settings, tools, and memory to suit your interpretive framework.
Subcategories:[edit | edit source]
- Settings File Generation β Organizing and refining your SP principles and letter definitions.
- Persistent Memory Management β Adjusting what the model remembers about your rules and preferences.
- Format Control β Directing how responses are written (e.g., wikitext, markdown, blog, etc.).