Experiment design assistant

For growth and product teams testing new features, turn business hypothesis, baseline metrics and testing constraints into reviewed experiment design brief. Address the recurring problem: experiments begin without clear success and stopping criteria. The pilot measures protocol completeness and interpretable results against the buyer's current method, before the larger build.

Validate baseline inputs, confirm definitions and constraints, select editable assumptions, calculate feasible alternatives, inspect sensitivities, let the responsible person approve a plan, and compare later actuals with the recorded assumptions. Start with business hypothesis, baseline metrics and testing constraints and finish with reviewed experiment design brief.

How the AI works

Extract input context and explain scenario differences. Use deterministic calculations or explicit optimization for quantities, compatibility, dates and prices. Show uncertain assumptions. Never let generated prose silently change the calculation rules.

Safeguards

Use consented research and preserve contradictory evidence. Separate observed user behavior, proposed explanations and untested product assumptions. Validate source access and reviewer availability during the pilot. Maintain customer-level access, data deletion controls and a record of final approvals.

What to build first

Begin with growth and product teams testing new features and one recurring use case. Build the first two modules: clarify proposed mechanism; define primary measures. Provide operator assistance for the third module: specify guardrails. Deliver reviewed experiment design brief through a manual review queue. Perform other necessary full-scope functions manually during the pilot. Include all applicable access, accuracy and professional-review controls from the start.

What it can connect to

Product feedback, authorized interviews, usage exports and requirement records. Read-only operational exports, calendars and finance or inventory records as relevant. Start with plan exports and retain human approval for execution. These are candidate integration categories, not verified supported connectors.

The screens in detail

Place editable drivers and constraints beside a clearly labeled scenario output. Include a baseline view, comparison chart or schedule, and an assumptions history. Let users trace a proposed quantity or date back to its inputs. Keep forecasts distinct from actual results. In this product, the first view is hypothesis canvas, followed by measure definitions and decision rules.