Resources
Practical writing on AI architecture.
No trend-chasing. No hype. Architecture, delivery methodology, and honest perspective on what AI systems actually require to work in production.
Downloads
Free checklists.
AI Readiness Assessment Checklist
A 40-point checklist covering data readiness, tooling, team capability, and organizational process. Score your organization before committing to AI investment.
Download →ChecklistAI Architecture Checklist
What to verify before your architecture is ready for implementation. Covers agent schema, knowledge model, integration contracts, and validation.
Download →Articles
Everything else.
Why AI Projects Fail Before They Ship
The structural reasons most AI initiatives stall at POC — and what architecture-first delivery changes.
AI Architecture vs AI Prompting
Why the prompt-engineering mindset produces different systems than the architecture mindset. How to know which you need.
What to Expect in a Weekend Sprint
The full picture of a 72-hour intensive: what preparation is required, what happens each day, what gets handed off.
AI Portfolio Strategy for Technical Founders
How to sequence AI investments for maximum leverage. Build vs buy decisions. When to prototype vs architect.
Agent Architecture: Tool Schema, Memory, and Handoff
The three structural decisions that determine whether an agent system is composable or a dead end.
Why Ontology Matters for AI Systems
Domain ontology isn't an academic exercise — it's the knowledge layer your agents depend on. How to design one that works.
Knowledge Graphs for AI: Practical Guide
Structured knowledge representation for agent consumption. Entities, relationships, claims, and sources — and how agents use them.
Executive Guide to AI Investment
What boards and executives need to understand about AI investment decisions. Buy vs build, readiness signals, and how to evaluate claims.