Field notes from the frontier of applied AI.
Practical, no-hype writing on building AI, data, and voice systems that actually ship.
The FinOps of AI: Proving ROI in 2026
AI budgets are under scrutiny in 2026. Only a minority of firms report significant returns. Here's how to measure, control, and defend the economics of AI.
Your Data Is Your AI Ceiling
In 2026, RAG and agents put 100% of the performance burden on your data. Most failures are freshness and consistency — not clever retrieval. Here's how to raise the ceiling.
AI Governance Is Now a Board Problem
The EU AI Act's high-risk deadline moved to late 2027, but the obligations didn't disappear. A pragmatic 2026 governance playbook for enterprises.
Right-Sized AI: The Small-Model Shift
In 2026, smaller language models are quietly winning enterprise work — cheaper, faster, private, and good enough. Here's when to reach for small over large.
Closing the 2026 AI Production Gap
Most AI pilots never reach production. Here's why the pilot-to-P&L gap is widening in 2026 — and the operating model that actually closes it.
The 2026 Executive Guide to Agentic AI
Agentic AI moves from chat to action — systems that plan, use tools, and complete multi-step work. Here is what leaders need to know to adopt it safely and profitably in 2026.
Cutting Operational Costs by 60% Without Cutting Corners
Cost reduction and quality are usually framed as a trade-off. With the right strategy — and the right use of automation and global talent — they don't have to be.
From Pilot to Production: The MLOps Checklist That Actually Matters
Most machine-learning projects die in the gap between a promising notebook and a reliable production service. This is the checklist we use to cross it.
Grounding Generative AI in Your Own Data: A Practical Guide to RAG
Retrieval-augmented generation is the difference between a chatbot that hallucinates and an assistant your teams actually trust. Here is how we build RAG systems that hold up in production.