When the model has never seen your code

**Microsoft Dev Blogs (Eng)** published **When the model has never seen your code**, marking the **fifth article** in an ongoing technical series dedicated to **Agent Experience (AX)**. The article addresses **Agent Experience (AX)** as the practice of ensuring **AI coding agents** work accurately and reliably with custom or internal technology.

The technical framework focuses on defining what developers can and cannot control within the **agent stack**. It outlines product mechanics for measuring whether specific **extensions** improve or impair agent performance, establishing a structured methodology to **iterate toward better outcomes**.

For engineers and system builders, the emphasis centers on eliminating guesswork when integrating **AI coding agents** into proprietary codebases. Understanding control limits within the **agent stack** allows developers to build targeted **extensions** and objectively quantify whether those additions enhance agent execution or introduce errors.

In the broader market context, **Microsoft Dev Blogs (Eng)** is formalizing **Agent Experience (AX)** as an engineering discipline. As deployment of **AI coding agents** expands across custom software environments, establishing standards for measuring **extensions** addresses a common operational challenge when models encounter unfamiliar code.

The practical takeaway for technical teams is to audit existing **extensions** in their **agent stack** using empirical measurements to verify performance impacts. Teams should focus on iterative adjustments grounded in test outcomes and monitor future installments of the **Agent Experience (AX)** series for further stack optimization practices.