The Decision Packet Pattern: Get Better AI Answers With Less Back-and-Forth

When an AI assistant gives a weak answer, the instinct is to ask again —add another sentence, clarify one more detail, paste one more snippet… and hope the next reply lands. That works, but it’s slow. You’re paying (in time and attention) for something you could do upfront: send a small, structured bundle of context and constraints so the assistant can produce a recommendation you can actually act on. I call this bundle a Decision Packet . It’s not a “better prompt” in the clever-wording sense. It’s a format —like a good GitHub issue template—that makes it easier for you to provide the right inputs and for the assistant to produce an answer that’s specific, scoped, and checkable. Below is the template, plus concrete examples you can copy into your own workflow. What a Decision Packet is (and isn’t) A Decision Packet is: A 1–2 minute structured context dump Optimized for recommendations (what to do next), not just explanations Designed to reduce “it depends” by forcing trade-offs into t