2026-02-12

Persistent Context Architecture for Copilot and ChatGPT

This episode of the M365.FM Podcast — “The Architecture of Persistent Context: Why Episodic AI Is Slowing You Down” — explains that persistent context is not a convenience feature but a foundational architectural layer that determines whether AI systems can scale reliably and productively in the enterprise. The host argues that most organizations treat AI as a “session”, where each interaction starts from scratch based on immediate prompts. This episodic design prevents agents and Copilots from becoming truly effective because context — identity, goals, constraints, history, and provenance — is never carried forward in a structured, auditable, and bounded way. Without persistent context, systems repeat effort, generate inaccurate decisions, and create inconsistencies that amplify risk and operational debt. The episode prescribes architectural principles for implementing persistent context, including clear context boundaries, governed memory stores, provenance tracking, and lifecycle controls, so that AI systems can accumulate useful knowledge over time while remaining secure and compliant.

Apple Podcasts · Spotify · YouTube · YouTube Music

Persistent Context Architecture for Copilot and ChatGPT (English)