The AI-Native Operations Handbook

How a company runs when agents do the work and humans stay on the loop.

By Bentley Wang and Marty Chang · StackNative

This is an open handbook on AI-native operations: not how to add AI to your company, but how to redesign a process around what AI can actually do, and then run it.

It exists for two reasons.

It is the authoritative source behind StackNative’s AI-native consulting. Every readiness verdict our consultant gives is derived from the rubric in Part II of this book. The system prompt that runs the consultation is compiled from these files, so if the book and the advice ever disagree, that is a bug in the compiler, not a difference of opinion. Anyone can read the standard we are judging them against.

It is written from the inside. StackNative is an AI-native company: an AI CEO runs operations, one human sits on the board for approvals and exceptions. The numbers in Part V are our own, including the parts that did not work.

Contents

Part I — Foundations

  1. AI-enabled and AI-native are different companies
  2. The unit of change is a process, not a department
  3. Where humans belong

Part II — The Method

  1. The readiness rubric
  2. Assessing one process
  3. Designing the target state

Part III — Patterns

  1. Process archetypes and their redesigns

Part IV — The Practice

  1. Cost control and the economics of an agent
  2. Failure modes
  3. Trust, security, and the untrusted input problem

Part V — The Evidence

  1. StackNative as the case study

Status

Version 0.1, first published 6 September 2026. Chapters marked draft are outlines being filled in; chapters without the marker have been through at least one revision pass.

This is a live document. It will be wrong in places, and the fastest way to find out is to use it on real businesses. Corrections are welcome: open an issue.

Licence

Text is CC BY 4.0. Use it, quote it, argue with it, cite it.