AAI PRESS
Book cover: Applied Super Intelligence (ASI), Putting the White House Accord into Practice, by Javid Ur Rahaman and Bharathram Nagaiah, AAI Press. Gold title lettering on deep navy above an ivory panel.

Super Intelligence Frontier · Book 1

Applied Super Intelligence (ASI)

Putting the White House Accord into Practice

By Javid Ur Rahaman and Bharathram Nagaiah

A field handbook for federal departments, agencies and state governments on building SI that exceeds expert performance on bounded mission decisions while staying governable.

Kindle eBook · Pre-order now · Releases October 9, 2026

Pre-order on Amazon For federal & state departments

Independent publication by AAI Press. Not affiliated with, sponsored by, or endorsed by the White House, any federal or state agency, America.gov, or any signatory of the White House Accord on Super Intelligence.

Why this book

From an accurate model to a changed decision

Super Intelligence earns its place only when it improves a real decision with a measurable outcome. This handbook closes the gap between a promising pilot and a decision your organization makes differently, month after month, under audit.

Built for deployers

The Accord binds frontier developers. This book serves the departments and agencies that deploy their systems, and shows how to carry the Accord's aims into daily operations.

Governable by design

Bounded authority, logged human command, evaluation harnesses, safety cases and immutable decision logs, so every system can be approved, operated and defended.

Practical, end to end

One worked program, runnable Python, reference tables and operating runbooks, plus a crosswalk to the federal requirements each chapter touches.

The authors' framework

The Seven Accord Practices

Seven practices that translate the intent of the White House Accord on Super Intelligence into deployment discipline. Each chapter links its controls to them.

  1. Decisions, Not Demos

    Every investment is justified by a named decision and a measured outcome.

    Chapters 1, 9, 10

  2. Shared, Open Architecture

    A six-layer reference architecture with open interfaces and portable components avoids lock-in.

    Chapters 2, 3

  3. Readiness Before Autonomy

    EDMAR data-readiness levels gate how much autonomy a system earns.

    Chapter 4

  4. Accountable Agency

    Every agent has an identity, least-privilege tools, bounded authority and a kill switch.

    Chapters 5, 6, 8

  5. Human Command

    A named human stays accountable, and each decision runs in a logged HITL mode set by stakes and reversibility.

    Chapter 7

  6. Evidence by Default

    Evaluations, safety cases, immutable decision logs and evidence bundles are produced continuously.

    Chapters 3, 6, 8

  7. Measured Public Value

    Value and risk are reported in an ROI² (Return on Intelligence Squared) ledger.

    Chapters 9, 10

The Seven Accord Practices are the authors' own framework. They are not part of the Accord and are not adopted or endorsed by the White House or any agency.

Contents

Inside the book

Chapters

  1. From Artificial to Applied: The Case for Applied Super Intelligence
  2. The ASI Reference Architecture
  3. Foundation and Frontier Models: Selection, Evaluation, and Economics
  4. Enterprise Data Readiness with EDMAR
  5. Agentic Systems: Planning, Tool Use, and Multi-Agent Orchestration
  6. Reinforcement Learning and Self-Improving Systems
  7. Human-in-the-Loop: Control, Oversight, and Trust Architecture
  8. Governance, Safety, Alignment, and Regulation
  9. Measuring Value with ROI²: Return on Intelligence Squared
  10. Capstone: Building an Applied Super Intelligence Program End to End

Appendices and reference

  • Federal crosswalkMaps every chapter to OMB memoranda, the NIST AI Risk Management Framework, FISMA and FedRAMP, the Privacy Act and Section 508.
  • Northwind referenceProfile, decision domains, systems estate and architecture of the book's fictional worked example.
  • GlossaryEvery framework term and the agent, reinforcement learning, evaluation and governance vocabulary used in the book.

Each chapter pairs design trade-offs with runnable Python 3.11 listings, reference tables and operating runbooks.

Public-sector use

For federal and state departments

Written for Chief AI Officers, CIOs, CDOs, CISOs, program executives and AI governance boards, and for state CIO and CDO offices standing up their own SI programs.

Map to your obligations

The federal crosswalk pairs each chapter and practice with OMB memoranda M-25-21 and M-25-22, the NIST AI RMF, FedRAMP, the Privacy Act and Section 508, so teams can trace controls to requirements.

Apply to mission decisions

The worked program translates directly to benefits adjudication exceptions, grants and payment integrity, acquisition and supply chain risk, and asset and fleet maintenance.

Briefings and review copies

Department, agency and state teams can request author briefings and review copies by message on LinkedIn.

A privately published handbook, not official guidance. Confirm current obligations with your Chief AI Officer, General Counsel and CIO before acting.

Editions

Formats

  • Pre-order

    Kindle eBook

    Releases October 9, 2026.

    Find on Amazon (Kindle eBook)
  • Coming soon

    Paperback

    6 × 9 in, 538 pages.

  • Coming soon

    Hardcover

    6 × 9 in, 538 pages.

  • Coming soon

    Audiobook

    Narrated edition to follow.

The authors

About the authors

Dr. Javid Ur Rahaman

Head of Applied Intelligence at AAI Applied Agentic Intelligence Research Labs®, a CxO board advisor and a program architect, and developer of the EDMAR and ROI² frameworks. He holds a PhD in Machine Intelligence (Time Series) from Golden Gate University and spent twenty years at Oracle, as Vice President of Software Engineering and then Senior Program Architect. He is the author of Modern Oracle Enterprise Architecture (BPB Publications, 2022) and the named inventor on US patent publication 2021/0382868 A1. He lives in Irving, Texas.

Bharathram Nagaiah

A technology futurist, strategist, author, researcher and advisor with more than twenty-three years of experience in enterprise architecture, digital transformation, multi-cloud strategy, data and SI, enterprise applications and IT governance. He advises C-level leaders on technology direction and investment, translating complex business requirements into scalable, sustainable technology solutions. He co-authored this book and served as its technical reviewer.

Dedication

Dedicated to NARA.GOV and AMERICA.GOV, and to the public servants across the departments and agencies of the United States who carry the public trust in every decision they make.