Build Fast. The Patterns Will Emerge.
The AI stack is changing faster than enterprise planning cycles. Build targeted capabilities that deliver value now, then standardize based on what actually works.
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Strategic perspectives on enterprise AI, technology architecture, and the decisions that shape how organizations adopt and operate intelligent systems.
The Over-Specialist Is the New Technical Debt
Large SaaS platforms created a class of over-specialists whose entire value was platform-specific. AI-assisted development just turned that dependency into a liability.
Read on LinkedInModel choice isn't the bottleneck anymore
Model choice still matters, but the harder problem is turning capable models into dependable systems — reliable tool use, structured outputs, and operational control over time.
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6 of 36 Essays
AllAgentic AIAI EngineeringAI GovernanceAI StrategyBuild vs BuyData QualityEnterprise AILeadershipLegacy SystemsLegal TechLife SciencesModel SelectionProductivitySoftware Architecture
September 2025
LLMs are the UI. Integration is the product.
Foundation models are commoditizing fast. The real competitive edge is integration — how efficiently you wire AI into workflows, manage token costs, and architect for production.
September 2025
Fixing AI Project Failures: Structure Over Culture
AI projects fail structurally, not culturally. Coordination overhead, disconnected compliance teams, and too many stakeholders stall initiatives before the model ever becomes the issue.
January 2023
Small Code and the Rules That Made It Work
Arguing for small composable services before 2010, well before microservices had a name. The technical case was only half the story — the other half was making engineers run what they built.