Frameworks and field notes on designing enterprise AI prompts that hold up under cost, governance, and scale.
A deep dive on the Context lever of prompt discipline — why the discipline is subtractive, and how the smallest context wins on cost and accuracy at once. The half test: could I remove half of this context and still get the right answer?
A Copilot Studio governance teardown. Five decisions that determine whether an agent ever leaves pilot, each with the trade-off shown: which environment it is born in, whose permissions its answers inherit, who can change it, how a change ships, and what happens when it is wrong.
A deep dive on the Intent lever of prompt discipline — why one plain sentence at the top of a prompt cuts cost, ends re-prompt loops, and beats a model upgrade.
Most AI conversations focus on models, licensing, and infrastructure. The biggest swings in cost and quality come from a layer almost no one is governing: the prompts themselves. A five-lever framework for designing enterprise AI prompts that hold up under cost, governance, and scale.