Shared AI Harness: One Memory, Many Models

A practical guide to building shared memory, skills, loops, tools, permissions and workflows around the AI models you already use

Shared AI Harness: One Memory, Many Models

TL;DR

  • AI models are evolving into replaceable parts of a larger system.
  • The 'AI harness' is the crucial environment surrounding the model, providing tools, memory, permissions, and skills.
  • This harness allows models to act, inspect results, self-correct, and operate over extended tasks through loops and graphs.
  • Harness engineering is becoming more important than prompt engineering, focusing on the system's environment and workflow.
  • The new AI stack includes Model, Context, Harness, Loop, and Graph, working together for reliable AI operations.
  • Building an AI harness involves creating shared memory, live state, skills, policies, and evaluation mechanisms.