Insights for the people who have to make AI work.
Field guides on the architecture, governance and operating decisions behind production AI. Written by practitioners, for architects and the executives they report to.
AI Model Inventory Template: Fields, Model Cards and an Example
Every AI framework starts by asking what AI you have. This template covers the inventory fields worth recording, how a model card fits alongside it and how to keep the list true, including vendor and embedded AI.
October 16, 2026 · 11 min read
- Architecture
Architecture Decision Record Template for AI Systems
AI design choices expire faster than most. An architecture decision record captures why a model, host or guardrail was chosen, what evidence backed it and what would reopen the question.
October 15, 2026 · 11 min read
- Governance and risk
AI Agent Registry Template: The Fields Every Enterprise Should Track
An agent registry is the system of record for every AI agent you run. This template lists the fields worth recording, shows a filled-in entry and explains how to keep the registry true without policing it.
October 14, 2026 · 10 min read
- Governance and risk
AI Architecture Review Board Charter: A Template You Can Adapt
A review board without a charter reviews whatever arrives, at whatever speed it can manage. A one-page charter fixes its scope, its decision rights and the turnaround it owes delivery teams.
October 13, 2026 · 10 min read
- Governance and risk
AI Agent Governance: Controls for Agents That Act on Your Systems
Agents do not only produce answers. They take actions with someone's authority. Governing them means deciding who each agent acts for, what it may touch and how you would prove what it did.
October 12, 2026 · 9 min read
- Platform and operations
AI-Ready Data: What It Means and How to Get Your Enterprise There
Most enterprise AI programs stall on data, not models. AI-ready data is a testable standard, judged one use case at a time, and you can reach it without rebuilding the platform first.
October 10, 2026 · 9 min read
- Strategy
AI Use Case Prioritization: A Scoring Framework for Enterprise Portfolios
Most enterprises have more AI ideas than they can fund. A shared scorecard turns the argument about which ones to build into a decision that survives budget season.
October 9, 2026 · 10 min read
- Strategy
Enterprise AI Consulting Firms Compared: Six Types and Who Each One Fits
Most 'best AI consulting firms' lists are written by a firm that ranks itself first. This one has no ranking. It compares the six types of firm you will actually meet, what each is good at, and where each goes wrong.
October 1, 2026 · 9 min read
- Architecture
Agentic AI Architecture: Patterns, Controls and What It Takes to Run Agents in Production
Agents are models that decide what to do next and then do it. The architecture around them decides whether that is useful or dangerous.
September 30, 2026 · 8 min read
- Strategy
How to Build an AI Center of Excellence That Ships, Not Just Advises
An AI center of excellence earns its place by making good AI work faster and safer across the business. The operating model, intake process and funding design decide whether it does that or becomes a bottleneck.
September 30, 2026 · 8 min read
- Strategy
AI Pilot to Production: Why Pilots Stall and How to Ship Them
Most AI pilots prove the model can do the task. Few prove the organization can run it. The gap between the two is architecture and operations, and it can be closed deliberately.
September 30, 2026 · 8 min read
- Strategy
AI Readiness Assessment Checklist: Seven Dimensions, Scored
An AI readiness assessment is only useful if it produces decisions. This checklist scores seven dimensions and shows how to turn the scores into a sequenced plan.
September 30, 2026 · 8 min read
- Strategy
AI Total Cost of Ownership: A Cost Model for Enterprise AI
Token prices are the most visible line in an AI budget and rarely the largest. A complete cost model covers the platform, the people and the controls that keep a system in production.
September 30, 2026 · 8 min read
- Strategy
Build vs Buy AI: A Decision Framework for Enterprise Leaders
Build vs buy is rarely a binary choice for enterprise AI. The real decision is which layers you own, which you rent, and how you keep the option to change your mind.
September 30, 2026 · 8 min read
- Governance and risk
How to Build an AI Governance Framework That Teams Can Actually Follow
Governance that lives in a policy document slows teams down without reducing much risk. Governance built into the platform does both jobs. Here is how to design it.
September 30, 2026 · 8 min read
- Architecture
Enterprise AI Reference Architecture: Layers, Components and Key Decisions
Every AI workload needs model access, data, retrieval, tools, security and evaluation. A reference architecture decides how those pieces work once, so each team does not reinvent them.
September 30, 2026 · 8 min read
- Governance and risk
The EU AI Act for US Companies: Scope, Roles and What to Do Now
A US headquarters does not put you outside the EU AI Act. If your AI systems or their outputs reach the EU market, the regulation can reach you. Here is how to work out your exposure and what to build now.
September 30, 2026 · 8 min read
- Strategy
How to Choose an AI Consulting Firm: Criteria, RFP Questions and Red Flags
The right AI consulting firm leaves you with systems in production and a team that can run them. Here is how to tell which firms can do that before you sign.
September 30, 2026 · 8 min read
- Governance and risk
ISO 42001 Readiness Guide: Building a Certifiable AI Management System
ISO/IEC 42001:2023 is the first certifiable management system standard for AI. Readiness is less about writing documents and more about proving that AI decisions follow a system you can show an auditor.
September 30, 2026 · 8 min read
- Platform and operations
LLM Gateway Architecture: Routing, Cost Control and Guardrails for Enterprise AI
One controlled path between your applications and every model you use. The single component that makes multi-model AI governable, observable and affordable.
September 30, 2026 · 8 min read
- Governance and risk
LLM Security: A Threat Model for Enterprise LLM Apps and Agents
Prompt injection cannot be patched out of a model, so LLM security has to be designed into the system around it. Here is the threat model we use and the controls that map to each layer.
September 30, 2026 · 10 min read
- Platform and operations
LLMOps and AI Observability: Evals, Tracing and Release Gates
LLM applications fail quietly: answers get worse, costs creep up, and nobody notices until a user complains. LLMOps is the discipline that makes those changes visible and controllable.
September 30, 2026 · 8 min read
- Architecture
Model Context Protocol (MCP) for the Enterprise: Architecture and Controls
MCP gives AI applications a standard way to reach tools and data. That is exactly why it needs enterprise controls: every MCP server you connect extends what a model can see and do.
September 30, 2026 · 8 min read
- Governance and risk
NIST AI RMF Implementation Guide: From Framework to Working Program
The NIST AI Risk Management Framework is voluntary, flexible and short on prescriptions. That is its strength and the reason most teams stall. Here is how to turn it into a program that runs.
September 30, 2026 · 9 min read
- Architecture
RAG Architecture for the Enterprise: From Ingestion to Evaluation
Retrieval-augmented generation is easy to demo and hard to run well. Here is how the pieces fit, where they fail, and how to tell whether yours is working.
September 30, 2026 · 8 min read
- Strategy
What Is an Enterprise AI Architect? Role, Skills and When to Hire One
The role that turns a pile of AI pilots into a platform people can build on. What the job covers, how it differs from adjacent roles, and how to staff it.
September 30, 2026 · 8 min read
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