Frameworks
The Transparency Framework explains how Anapoly AI Labs discloses the level of AI involvement in all published material. It defines a set of standard transparency labels, ranging from Human-only to AI-only , and gives clear descriptions for each. The framework outlines when and how to apply these labels, allows for optional justifications and chat summaries, and provides examples to ensure consistency. Its purpose is to maintain trust and credibility by making AI’s role in content creation explicit and easy for readers to understand.
The Lab Framework is a facilitator-facing guide that sets out how Anapoly AI Labs are planned, run, and closed down. It defines different types of labs, the roles involved, and the lifecycle from planning through launch, operation, review, and wrap-up. It specifies the tools and technologies used, describes the assets created at each phase, and includes templates, naming conventions, and configuration practices. Its purpose is to ensure every lab is purposeful, well-documented, and capable of producing reusable, trustworthy outputs.
Goal-Directed Context Management explains how to organise collaboration with AI so its contributions stay relevant, precise, and grounded throughout the development of a knowledge-based product. It uses contextual scaffolding to give the AI the right background, an up-to-date picture of progress, and clear direction for the next step. Like a satnav updating in real time, the scaffolding keeps the AI aware of where you are, what matters most, and how best to move forward.