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Shadow mode and comparisons

Shadow mode lets you test a new route without showing it to the user: answer with the stable model and compare in the background.

Pattern

Terminal
primary = call_model("stable", prompt)
shadow = call_model("candidate", prompt)

log_comparison({
  "prompt_id": prompt.id,
  "primary_model": "stable",
  "shadow_model": "candidate",
  "primary_output": primary.text,
  "shadow_output": shadow.text,
  "shown_to_user": "primary"
})

What to compare

  • Perceived quality and human edit rate.
  • Cost and latency.
  • Format, citation, or safety failures.
  • Regressions by task type.

Do not switch the winning model because of one anecdote. Switch when you have enough cases per category and understand what improves and what gets worse.

Complete Aulafy mapSee how this lesson fits without leaving your path.

Complete Aulafy map

How all courses connect

This is not a checklist. Start with the foundation, choose an outcome, and go deeper only when your project needs more control.

  1. 1Understand
  2. 2Apply or build
  3. 3Operate with confidence
01

Choose an application

Turn the foundation into a visible outcome: a website, a business improvement, media, or an interactive experience.

Continue into the technical branch when you need to maintain code, data, or infrastructure.

02

Build with code

Prepare your environment, work with coding agents, and run models while keeping control of your projects.

This branch prepares you to design and operate reliable AI systems.

03

Take systems to production

Combine retrieval, agents, evaluation, security, deployment, and model adaptation when the problem requires it.

You do not need every course: choose the component your system needs and return as it grows.

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