Idea · Developing
AI Foundations for Product Leaders
The hard part of building with AI is rarely the model - it is everything the model is wired into. This idea gathers the foundations product leaders need to make AI architecture decisions on purpose: what changes when software stops being deterministic, and what those choices commit a team to long after launch.
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Product leaders are increasingly asked to make architectural calls about AI before they have the language for them - enabled or native, prompt or fine-tune, where the differentiation actually lives. Get those wrong and the cost tends to resurface later, disguised as an operations problem.
The through-line here is that building with AI is a product decision before it is a technology one. The model commoditizes; the architecture around it, and the obligations that architecture creates, are what an organization actually lives with.
Artifacts advancing this idea
- AI-Enabled, or AI-Native, That Is the Question Article / AI The model is the most replaceable part of what you build. The decision that actually holds is made earlier, and rarely on purpose: whether what you're building can survive the model being wrong.
- Four Gates Before You Build AI Article / AI Cheap prototyping removed the filter that used to kill weak AI ideas before they shipped. Four gates put it back - each one far cheaper to check now than to regret later.