ET.

Original writing · Ideas from the work

Making better decisions
before building faster.

Practical essays about AI products, prototyping, and the decisions that connect emerging technology to useful outcomes.

01

AI product strategy · 6 min read · Draft

Before You Build an AI Product, Decide What It Needs to Prove

A working prototype should reduce a specific uncertainty—not simply demonstrate that AI can produce an impressive result.

02

AI product strategy · 4 min read · Draft

The Most Expensive AI Mistake Is Solving the Wrong Problem

A capable AI system can still be a poor investment when the team has misunderstood the work that needs to change.

03

AI product strategy · 4 min read · Draft

Why AI Demos Create Excitement but Fail to Create Alignment

A demo can make an AI opportunity feel real while leaving stakeholders with very different ideas about the product being proposed.

04

AI prototyping · 4 min read · Draft

How to Turn an AI Opportunity into a Testable Prototype

A practical sequence for narrowing an AI opportunity into a working experience that can produce useful evidence.

05

AI investment · 4 min read · Draft

Five Questions to Ask Before Funding an AI Initiative

A funding decision should test the strength of the opportunity, not reward the polish of the proposed solution.

06

AI leadership · 4 min read · Draft

What Product Leaders Need to Know About AI—Without Becoming AI Experts

Product leaders do not need to master model architecture, but they do need a practical understanding of behavior, evidence, and operating responsibility.

07

AI prototyping · 4 min read · Draft

Why Prototyping Matters More When the Technology Is Uncertain

When teams cannot predict behavior from requirements alone, a working prototype becomes a tool for product, technical, and organizational learning.