This is a follow-up to our previous article on prompt engineering basics, where we laid out five principles for getting more reliable output from AI. Today we’re going to expand on the first principle: Guiding the AI Along.
AI can save you a ton of time and energy, but it’s not a mind reader. It does exactly what you ask, and if what you ask is fuzzy, the output is going to be fuzzy too. Think about a long road trip. You don’t tell your travel partner, “Grab us some snacks,” and assume they’ll magically come back with Sour Patch Kids, a couple Snickers, and a Snapple. They’ll probably return with chips, beef jerky, and energy drinks, because that’s a perfectly normal interpretation of “snacks.” If you want something specific, you have to say what you mean. Same deal with your AI tool. If you want better output, you have to give it better guidance.
Guiding the AI along is just giving it the missing details up front. If you don’t, it fills in the blanks for you, and those guesses usually land on the most generic version of what you asked for. That’s why you get answers that aren’t exactly wrong, they’re just not what you meant. The fix isn’t a long prompt, it’s a clear one. Say what you want, who it’s for, what tone to use, and any rules it has to follow. Do that, and you’ll spend less time rerunning prompts and more time using the output.
Here’s a concrete example. Let’s say you need help drafting a PRD for a new feature in your project management app for remote teams, think tasks, comments, due dates, the whole thing. If you’re vague and type something like, “Write me a PRD for this feature,” the AI has to guess everything: what the feature is, who it’s for, what success looks like, what’s in scope, and what constraints matter. You’ll get a PRD-shaped doc, but it’ll be generic, and you’ll spend the next 20 minutes undoing assumptions. The better move is to give it a quick brief first, a few lines that tell it what you’re building, who it’s for, and what “done” actually means.
You don’t need to write the world’s longest prompt to get good output. You just need to stop making the AI guess. The easiest way to do that is to use a simple checklist, I call it the Direction Stack: goal, audience, context, role, tone, boundaries, and what “done” looks like. Hit these points up front and the AI usually nails it in one or two tries. Here’s the checklist I use.
Here’s the Direction Stack:
Goal: What are we trying to accomplish, and what does success look like?
Audience: Who is this for, and what do they already know or care about?
Context: What’s the situation, product, constraints, and any background the AI needs to not guess wrong?
Role: Who should the AI act as (PM, UX writer, staff engineer, marketer, editor)?
Tone and voice: How should it sound (direct, friendly, formal, blunt, playful, etc.)?
Boundaries: What should it avoid (no invented metrics, no legal claims, don’t mention competitors, don’t use jargon, etc.)?
Definition of done: What should the output look like (format, length, sections, bullets, include examples, include edge cases)?
Here’s how you use the Direction Stack without turning it into homework. Don’t write a novel. You just have to answer the questions. Most of the time, two to three lines per category is enough. The goal is to remove ambiguity, not to document your entire product strategy.
So for that PRD example, don’t prompt “write a PRD for this feature.” Prompt something closer to: “Write a PRD for a ‘Vacation Mode’ feature in a project management app for remote teams. The audience is internal engineering and design. The goal is to reduce missed handoffs when someone is out. Success is measured by fewer overdue tasks and fewer ‘who’s covering this?’ pings. The tone is direct and practical. Include scope, non-goals, user stories, edge cases (partial-day PTO, multiple assignees, recurring tasks), and the metrics we should track. Don’t invent numbers or quote fake stats.” Same request, but now the AI isn’t guessing what the feature is or what a good PRD looks like for your team.
If you’re thinking, “Cool, but I don’t always have all that figured out,” that’s fine. The Direction Stack still helps because it shows you what’s missing. When you don’t know something, say that too: “Make reasonable assumptions, but list them first,” or “Ask me 3 questions before you write.” That one line alone can save you a bunch of back-and-forth.
A few common ways people accidentally sabotage themselves: they give a goal but no audience, so the doc is the wrong level. They give a tone but no boundaries, so it gets salesy or full of buzzwords. They give context but no definition of done, so it rambles. When the output feels off, it’s usually not because the model is dumb, it’s because one of those buckets was empty.
The simple rule: if you want consistent results, stop treating prompts like one-time wishes and start treating them like reusable briefs. Save your Direction Stack as a template, then copy, paste, and fill it in each time. Do that and you’ll spend less time “prompting” and more time actually shipping whatever you’re trying to build.
In the next article, we’ll cover the second principle: Shaping the Output and how to get the AI to return exactly what you need, in the exact format you can actually use.