3 min read

Customer Profitability in the AI Era Series #5: Implementation Burden Is Part of the Product

Implementation is part of the product’s true cost, spanning integration, data, training, permissions, workflow design, and trust. Its burden is defensible when each deployment creates reusable capability; when every customer starts from zero, software economics drift toward custom consulting.
3 min read

Customer Profitability in the AI Era Series #4: Support Load Is a Margin Signal

Support volume is less revealing than what generates it. Recurring questions may expose a repeatable adoption journey, an underbuilt product, or a mismatched customer; tracking whether support declines with maturity turns service work into evidence about margin and fit.
3 min read

Customer Profitability in the AI Era Series #3: The AI COGS Problem

AI usage carries direct and indirect costs that blended gross margin can conceal. Account-level instrumentation must connect workflows, retries, model choices, human review, evaluation, and support to customer behavior, revealing whether heavy adoption creates profitable scale or margin compression.
3 min read

Customer Profitability in the AI Era Series #2: Growth Stage Changes the Answer

Unprofitable customers can represent valuable learning or permanent structural drag, and growth stage changes the acceptable tradeoff. The key is whether costly accounts produce repeatable product insight, strategic value, or future margin—or merely consume the company’s future.
3 min read

Customer Profitability in the AI Era Series #1: Good Revenue, Bad Revenue

In AI businesses, revenue is a claim on compute, support, implementation, product attention, and reliability—not proof of healthy scale. Separating booked revenue from what remains after serving customers reveals whether usage builds a repeatable product or conceals bespoke burden.
1 min read

The Design Engineer Era — Series Index

Product quality increasingly depends on closing the gap between design intent and shipped behavior. Across ten connected arguments, the sequence moves from role definition and prototypes to systems, AI, management, and a practical audit of where quality leaks.
3 min read

The Design Engineer Era Series #10: The Design Engineer Audit

A meaningful design engineer audit tests behavior, prototypes, build fluency, craft authority, systems, AI use, and role clarity against the shipped product. Its purpose is to expose where quality still disappears between intent, implementation, and release.
3 min read

The Design Engineer Era Series #9: Hiring And Managing Design Engineers

Hiring design engineers requires evidence of behavioral judgment, practical build fluency, and thoughtful tradeoffs, not polished surfaces alone. Managing them means pairing craft responsibility with time, tooling, authority, and a clear role center that prevents overload.

Choose your reading rhythm.

Start with a weekly briefing, add daily notes, or hear only when a durable essay or research update is ready.
You've successfully subscribed to Antoine Buteau
You've successfully subscribed to Antoine Buteau
Welcome back! You've successfully signed in.
Press ESC to close.