Your first test

Before you start

• SwiftCNS installed and your AI tool connected.
• An idea you're working on that would cost real time or money if it's wrong.
• SwiftCNS open in the browser beside your AI tool. You'll watch each step land there.
• Any plan. Free is enough to take one idea to a decision (Plans and usage).

Steps

1. Describe the idea

   Use SwiftCNS to evaluate the riskiest idea we've been working on. Tell me which idea you picked and why, then show me what it rests on.

   Your AI tool picks the idea from what it knows about your work. If it picks the wrong one, describe yours in two or three sentences: what you want to do, for whom, and the numbers you have. The running example started like this:

   Use SwiftCNS to test this: we want to launch a $79/month Team plan. About 50 new trial teams a month, and a third of them try to invite a teammate. We want to know whether teams will pay for sharing before we spend on billing.

   SwiftCNS replies in about half a minute with the assumptions the idea rests on, each scored for importance and evidence.

   

2. Choose what to test

   Pick the riskiest assumption: high importance, low evidence. SwiftCNS turns it into a hypothesis with provisional success criteria, then proposes experiment designs scored for setup, run time, cost and data reliability. Choose one. Tell your AI tool which, or click it in the app.

   

3. Assign and approve

   Give the experiment an owner and, if you like, a due date. Then approve it. Approving commits you to the design and its success criteria; they can't change after this.

   

4. Run it and log the evidence

   Set up the tracker (one row per thing you count), run the experiment in the real world, and log rows as results come in: type them, paste them, import a CSV, or ask your AI tool to add them. When you're done, choose Complete tracker. It saves the rows as a fixed snapshot and completes the experiment.

   

5. Call the result and write what you learned

   SwiftCNS drafts observations and insights from the snapshot. You decide whether the result Met, did Not met or is Unclear against the success criteria, and write what you learned in your own words. Then Publish Learning.

   

6. Record the Decision

   Nothing prompts this step, so ask for it:

   Prepare a SwiftCNS decision review for this experiment. Cite the Learning. Don't recommend a choice; I'll decide.

   Choose Move forward, Change course, Test again or Drop it, write why and what happens next, then Record decision.

   

What you get

A Decision Record: the question, the assumption, the experiment and its criteria, the evidence, your Learning and your decision, linked together.

SwiftCNS's part took about 20 minutes; the experiment itself takes as long as it takes.

Done when

• The experiment shows under Decided on the project's Experiments board.
• Your Learning is under Learnings, and your decision under Decisions.

Common mistakes

• Stopping at the Learning. A published Learning doesn't record a decision. Ask for the decision review.
• Letting your AI tool call the result. The result and the decision are yours. Your tool should only do them if you explicitly tell it to.

For agents: MCP tools and gotchas

• Setup: generate_resource_id (PROJECT), create_project, generate_resource_id (CONVERSATION), create_conversation (a title is required, such as the question). Every write takes a stable requestKey; reuse it only to retry identical input.
• After each send_message or continuation, poll get_message until execution.status is SUCCEEDED (the message status may read requires-action when a card is waiting), then reload get_conversation_progress.
• Flow: send_message → select_assumptions → select_hypothesis → select_experiment → assign_experiment → approve_experiment → configure_data_tracker → add_data_tracker_rows → complete_experiment (with continueConversation: true) → update_learning_draft → publish_learning → prepare_decision_review → submit_decision.
• Each step's step-by-step detail is in the method.

Next

The method: why each step works, and how to do it well.