Research & Methodology

This chapter is part of the book The Sacred Editors: Christianity.

Transparency in the Age of AI

As mentioned in the introduction, this book emerged from a personal journey of exploration—what some traditions call bhāvanā, or disciplined cultivation of understanding. While my focus this time was not comparative theology but the history of how the Bible came to be, I approached the subject with the same intellectual curiosity, reverence for tradition, and openness to whatever might be uncovered.

This project also represented my continued exploration of artificial intelligence as a research and writing partner. Given the growing importance—and legitimate concerns—around AI's role in content creation, I want to be completely transparent about how this book was developed, how facts were verified, and how potential errors were addressed. My aim is to offer both confidence in the integrity of this work and a replicable model for others navigating similar terrain in an age of rapidly evolving digital tools.

A Multi-Platform Workflow

Rather than rely on a single AI system, I developed a structured process using multiple large language models (LLMs), each selected for their particular strengths and used within carefully defined parameters. The workflow follows a six-stage process, refined through earlier projects and adapted specifically for historical research requiring both scholarly rigor and narrative accessibility.

Stage 1: Idea Development with ChatGPT

Each chapter began with exploratory conversations using ChatGPT (GPT-4, accessed through OpenAI's interface). This included brainstorming narrative hooks, historical scenes, and methods for presenting complex scholarly debates in accessible language. ChatGPT proved particularly effective for drafting initial outlines, integrating structural elements, and identifying key scholarly voices for inclusion (such as Bruce Metzger, Bart D. Ehrman, Timothy Michael Law, and Emanuel Tov). Its conversational strengths made it ideal for exploring different approaches to contentious or nuanced historical questions.

Stage 2: Source Verification with Perplexity

All drafts and citations underwent verification using Perplexity (accessed through perplexity.ai), a research-focused AI platform capable of locating specific scholarly claims, cross-referencing publication details, and assessing source reliability through real-time web searches. This stage ensured that paraphrased material and citations actually existed in the works of named scholars and that claims aligned with current academic consensus. Where possible, complete primary and secondary source citations were added, and questionable or outdated references were flagged for revision.

Stage 3: Writing and Coherence with Claude

For certain chapters and major revisions, Claude (Anthropic's Claude 3.5 Sonnet) was employed to refine and synthesize drafts—particularly for longer or structurally complex chapters. Claude's particular strength in maintaining consistent tone and preserving cross-chapter continuity proved invaluable for ensuring the book's unified voice and format while handling substantial amounts of source material.

Stage 4: Recursive Fact-Checking

Following initial synthesis, all chapters underwent additional rounds of verification using Perplexity's updated databases. This iterative process frequently caught subtle errors, outdated scholarly references, or unsupported generalizations that had slipped through earlier stages. Corrections were implemented systematically, with particular attention to ensuring that historical claims aligned with current archaeological and textual evidence.

Stage 5: Expert Human Review

Following the model established in my previous book project, all technical and historical content was reviewed by Dr. [Name Withheld], a biblical scholar with expertise in textual criticism, canon formation, and early church history. This expert review proved crucial for correcting oversimplifications, ensuring balanced presentation of interpretive debates, and identifying subtle biases or gaps that even sophisticated AI systems consistently miss. The reviewer's feedback shaped both factual corrections and interpretive nuance throughout the manuscript.

Stage 6: Final Human Integration and Editorial Review

The concluding drafts underwent comprehensive review and revision by me as both author and student of the material. This stage involved structural adjustments, tone calibration for lay accessibility, and careful decisions about including or removing material based on both historical accuracy and narrative effectiveness. Every word in the final manuscript reflects human judgment about how best to serve readers seeking both intellectual rigor and engaging storytelling.

Why Multiple AI Systems?

Different platforms demonstrate distinct capabilities and limitations. This multi-system approach created a form of technological peer review:

ChatGPT excelled at conversational flow, narrative structure, and translating complex scholarly positions into accessible language. However, it occasionally drifted toward oversimplification and required constant verification for factual precision.
Perplexity proved essential for scholarly verification, connecting named researchers to their actual published work, checking biblical cross-references, and identifying weak or disputed claims through real-time source checking. Its limitations included occasional over-reliance on secondary sources and difficulty with very recent scholarship.
Claude provided superior long-form synthesis and stylistic consistency when integrating multiple revisions or complex source materials. It maintained narrative coherence across lengthy passages while preserving technical accuracy, though it sometimes required guidance on balancing scholarly precision with readability.

Using multiple systems allowed each to check and balance the others, creating a form of technological triangulation that enhanced both accuracy and comprehensiveness.

The Critical Role of Contextual Prompting

Success with AI tools depends heavily on precise, expert-level prompting. All systems were consistently primed with detailed expert personas:

"You are a PhD-level scholar in biblical studies and church history, with specialization in canon formation, translation history, and textual criticism. You are familiar with current archaeological evidence, manuscript traditions, and ongoing scholarly debates. You write clearly for educated lay readers, accurately represent diverse scholarly perspectives, avoid speculation not grounded in evidence, and distinguish clearly between established facts and interpretive questions."

Each chapter prompt included detailed structural requirements, tone guidelines, and references to previously established material. This approach minimized factual drift, reduced anachronistic interpretations, and maintained consistency across chapters while respecting the complexity of historical questions.

Addressing AI Limitations and Ensuring Human Responsibility

No AI tool can replace lived expertise, cultural sensitivity, or human discernment. While these systems significantly accelerated research and synthesis, they consistently demonstrated important limitations:

Struggle with interpretive nuance when representing complex theological or historical positions, often flattening debates into overly simplified binaries
Potential underrepresentation of Global South, non-Western, or marginalized Christian perspectives, reflecting biases in their training data
Inability to engage emotionally with the spiritual or personal stakes of the stories being explored, sometimes missing the human significance of historical events
Occasional conflation of secondary sources with primary evidence, requiring careful verification of all factual claims

To address these limitations, I incorporated specific strategies: seeking out non-Western scholarly voices where available, explicitly acknowledging interpretive complexity in Scholar Debate sections, and ensuring that human experience and spiritual significance remained central to all narrative elements.

Ultimately, I—not any AI system—remain fully responsible for every claim, interpretation, and narrative choice in this book. AI provided research acceleration and organizational support; human judgment, expert consultation, and ethical responsibility shaped the final content.

Verification Standards and Quality Control

All chapters underwent systematic review for multiple dimensions of quality:

Factual accuracy through cross-platform verification and expert review
Scholarly alignment via direct citations, proper attribution, and balanced representation of academic debates
Narrative integrity through stylistic consistency and reader accessibility
Cultural sensitivity regarding religious traditions and contemporary faith communities
Ethical transparency about speculative content, interpretive limitations, and areas of ongoing scholarly debate

Where historical events remain contested or interpretations are disputed, the chapter format explicitly accommodated multiple scholarly perspectives, ensuring readers understand what is established, what is debated, and what remains speculative or unknown.

Ethical Framework and Future Implications

This project represents more than an exploration of biblical history—it serves as a case study for how future researchers might responsibly engage with sacred and sensitive topics in an age of artificial intelligence.

The goal was never to automate insight or replace human scholarship, but to amplify curiosity and enhance access to complex historical materials. If this methodology has enabled a richer, more nuanced exploration of how sacred texts are shaped by human communities—scribes and emperors, theologians and translators, communities of faith across centuries and cultures—then it has served its purpose.

The rapid evolution of AI capabilities means that specific tools and approaches will continue to change. What remains constant is the need for transparency, verification, expert oversight, and ethical responsibility when using these powerful technologies to explore questions that matter deeply to human communities.

A Note for Future Researchers

For others considering similar projects, several principles emerge from this experience:

Transparency builds trust: Readers deserve to know how content was created, especially when AI is involved
Multiple verification layers are essential: No single system or approach is sufficient for ensuring accuracy
Expert human review cannot be replaced: AI augments but cannot substitute for domain expertise
Ethical responsibility remains with human authors: Tools are powerful, but humans must remain accountable for their use

In the end, methodology is simply a means to an end. The deeper work—the patient, careful, sacred work of understanding how human communities preserve and transmit their most treasured wisdom—requires not just sophisticated tools but humble hearts and curious minds willing to be changed by what they discover.

This book's methodology aimed to honor both the rigor that historical investigation demands and the reverence that sacred traditions deserve. Whether it has succeeded is for readers to judge.