End-to-End Reference Architectures and Feedback Loops
Explore how to assemble individual AI components into a coherent end-to-end Claude architecture. Learn to identify key reference architectural patterns and design effective feedback loops that allow systems to measure and improve outputs. Understand why feedback loops are essential and how to incorporate human-in-the-loop checkpoints in AI workflows for better decision quality and monitoring.
Over the last three lessons, we made every individual pattern decision Atlas Financial needed. Document intake became an augmented LLM. Policy checking became a workflow. The borderline-application investigator became a genuine agent, and we worked out when that investigator should grow into a coordinator with specialists. Each of those decisions was correct in isolation. None of them, on its own, is an architecture.
An architecture is what you get when those components are wired together into one system with a defined input, a defined output, and, critically, a way for the system to learn from what it gets wrong, the full input, processing, output, feedback loop shape. This lesson closes out solution design by teaching that assembly, and by giving the feedback loop the attention it usually does not get. In this lesson, we will cover:
The four-stage shape every Claude architecture shares, and why stopping short of the fourth stage is the most common design gap
A small set of reference architectures you will reach for repeatedly, and the signal that tells you which one fits
How to assemble Atlas’s separately chosen components into one coherent, end-to-end system
What actually belongs in a feedback loop, and why “we log everything” is not the same as designing one
The four-stage shape
Every Claude architecture, no matter how simple or how elaborate, can be described in four stages:
Input: What enters the system and in what form.
Processing: What happens to it, using whichever patterns the earlier lessons in this chapter taught you to choose per task.
Output: What the system produces and who or what consumes it.
Feedback loop: How the system’s outputs get checked against reality so the system can be measured and improved.
The first three stages get drawn on almost every whiteboard. ...