Writing
Notes on building AI and SaaS products: how I work, working with founders, and lessons from my own studio products.
AI-generated UI still needs an accessibility review
Why an interface that looks right in the browser is not finished, what recent research says about AI-generated code and accessibility, and what I check by hand.
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Pricing an AI feature for your customers
How to choose between including an AI feature in the plan, per seat, usage or credits, or a premium tier, and how running costs, limits and real customer tests should shape the choice.
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Do you need an AI agent, or just a better workflow?
The difference between a workflow and an agent, where fixed rules beat model decisions, and how I decide how much freedom an AI system actually needs.
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AI governance for a small team: the one-page version
A one-page AI policy a 5 to 20 person company can copy: approved tools, what data can go in, who approves AI features, what gets logged, how mistakes are handled and who reviews it.
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The new model looks better. Should you actually switch?
A model release is a candidate for testing, not an automatic upgrade, so here is how I check whether a new model is better for your product and how to switch safely.
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How I ship a v1 in weeks with AI
The seven steps I use to take a founder's idea to a working v1 in weeks, and the two ways to get it live: I build it, or I lead it with your team.
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Cash, equity or both: how I structure build partnerships
Why I rarely work for equity alone, how a part-cash, part-equity build partnership works, and what to agree in writing first.
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What a fractional product and AI lead actually does
What a fractional product and AI lead does, when you need one instead of a full-time hire, and what the first weeks look like.
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