How to build a strategic question chain for any AI task
This guide is based on the Beyond Prompts: How to Avoid “Faster Mediocrity” with AI webinar, published on the AI Lab by ActiveCampaign.
Get the quick-start guide
What will I accomplish with this guide? By the end, you’ll have a repeatable method for replacing one-shot AI prompts with a chain of strategic questions—the technique Bob Pearson calls a “prompt supply chain.” It’s based on the workflow Bob walked Sean Blanda through in this webinar, where the goal is to get past surface-level AI output and reach the kind of answer you’d expect from the smartest analyst on your team.
Before you start, you’ll need:
- An account with an AI assistant that retains conversational memory inside a workspace or project (ChatGPT, Claude, or ActiveCampaign Active Intelligence)
- A specific marketing task you’ve been outsourcing to a one-shot prompt (audience research, creative direction, campaign brief, naming, repurposing)
- Any unique inputs you’d hand a colleague working on the task: customer interviews, sales call notes, past campaign briefs, product docs
Quick reference
- Total time: 45–60 minutes for your first chain; 10–15 minutes once the workspace remembers your context
- Tools needed: ChatGPT / Claude / Active Intelligence; a workspace or project so the model retains memory between turns
- Key output: A saved set of 4–6 strategic questions per decision point that you can rerun on the next campaign
Watch this section
For full context on the following topics, watch these sections of the webinar:
- Why prompt engineering is the wrong frame — [04:12]–[05:35]
- Treat AI like the smartest person you’ve worked with — [05:00]–[05:40]
- The audience definition question cascade — [05:40]–[07:30]
- Prompt supply chain: four to six questions per decision point — [10:14]–[12:00]
- Cycling through “weeks of work in an hour” — [13:25]–[14:30]
The workflow
Phase 1: Frame the decision before you frame the prompt
After this phase, you’ll have: a written list of every decision point inside the task you’re about to give AI.
- Name the task in one sentence: “I need to brief a campaign for our enterprise segment in EMEA,” not “help me with a campaign.”
- List the decision points: for an ad, that might be audience, headline, channel, creative direction, and offer. Bob’s rule of thumb is four to six decisions per task.
- Write one outcome you want from each decision: what makes a good answer here? The outcome statement is what tells you the chain is done.
We should be looking at AI as a way to mirror our own intelligence. We have to think through what are the questions we should be asking to get the outcome that will give us the edge in the market.
Phase 2: Open a workspace and ask in cascades
After this phase, you’ll have: a working answer to your first decision point, built through 4–6 questions instead of one prompt.
- Open a workspace, not a fresh chat: workspaces and projects keep memory across turns. Without that memory, every question starts from zero.
- Pick the first decision point and ask the broadest question: for audience, that might be “Where are people who buy this type of product?”
- Refine in cascades: ask the same kind of follow-up a market researcher would. “Now tell me the five subtypes of those customers.” “Now tell me how many languages they operate in.” “Now tell me geographically where most of them are.”
- Pressure-test the answer: ask “What am I missing?” or “What questions did I not ask that I should have?” The model will fill in gaps you didn’t know existed.
- Capture the working answer: save it to a doc or note before moving to the next decision. Don’t let a 12-turn conversation be the only place the answer lives.
Phase 3: Use AI to grade your own questions
After this phase, you’ll have: a saved list of the 2–3 questions per decision point that produced the best answers.
- Ask the model to evaluate your questions: paste the chain back in and ask “Did I really ask the right questions for this topic? What could I have done to improve?”
- Save the strongest 2–3 per decision point: these become your reusable starter questions for the next campaign.
- Keep them in a “questions library” doc or workspace memory: the next time you brief a campaign for the same audience, you start three steps ahead.
Phase 4: Push for volume only after the questions are right
After this phase, you’ll have: a finished output — copy, brief, audience, creative direction — that you’d be willing to hand to a colleague.
- Now ask for volume: “Give me 50 versions of this ad headline” or “Give me 100 product names in this theme.”
- Cull to a shortlist: most won’t be good. That’s expected. You’re looking for fragments that trigger your own pattern recognition.
- Refine the shortlist with a constraint prompt: “Give me five more along the lines of #14 and #37, but make them shorter.” Iterate until you have something usable.
- Stop when you have it: Sean’s example was naming a client project — partway through asking for the next 100 examples, the right name “clicked” and he didn’t need the AI anymore.
Use this prompt:
I’m working on [DECISION POINT] for [TASK]. The context you already have in this workspace applies.
Before we generate options, what 4–6 questions would the smartest [ROLE — e.g., market researcher, creative director, channel strategist] ask before answering?
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