AI Scenario Review

Critically test the quality, consistency and readiness of AI Scenario Review. The objective is to remove ambiguity around which assumptions move runway, revenue, cash and survival outcomes, give the founder a decision-ready output, and make it clear whether the venture should progress, repeat the task with stronger evidence, escalate to expert support, or move into a linked stage.

Bertie or a programme manager assigns AI Scenario Review when the venture needs a decision-ready output for this group. Typical triggers include group-gate reviews, evidence gaps identified by the co-pilot or founder request.

current venture DNA; latest task outputs; data-room state; open assumptions; programme or founder goal; existing artefact to review; specific context for which assumptions move runway, revenue, cash and survival outcomes.

1. 1Gather Core Scenario Inputs and Venture Evidenceexpand_more

   Pull together the current financial model, scenario parameters, baseline metrics, and supporting data-room evidence required for the scenario review. Consolidate current assumptions regarding cash burn, pricing, sales velocity, and fundraising timelines into a structured review package. Ensure all underlying files, advisor notes, and operational logs are fully accessible for systematic audit.

   Objective

   Completing this action compiles a single source of truth containing all quantitative inputs and qualitative context required to model venture scenarios. It establishes the baseline data set for the AI scenario review, ensuring subsequent stress-testing is grounded in current operational reality rather than outdated figures.

   What's expected

   The founder must deliver an organised data-room folder containing the active financial model, historical cash flow statements, and documented operational metrics. A clear inventory of key scenario variables and underlying evidence sources must be formally recorded.

   Consultant stress-test · 5 questions

   1. 1.What primary data sources validate the baseline burn rate and revenue velocity used in this scenario package?
   2. 2.How recently were the operational assumptions in this data room updated to reflect actual performance?
   3. 3.Which key financial inputs currently rely on founder intuition rather than empirical data-room evidence?
   4. 4.How have you ensured that offline commitments or unwritten advisor feedback are captured in this review file?
   5. 5.Why is this specific dataset sufficient to run a meaningful scenario audit at this stage of venture maturity?

   Open action arrow_forward
2. 2Isolate High-Impact Survival and Growth Driversexpand_more
3. 3Audit Scenarios Against Venture DNA and Criteriaexpand_more
4. 4Uncover Strategic Contradictions and Evidence Gapsexpand_more
5. 5Prioritise Evidence-Gathering Experiments and Model Correctionsexpand_more
6. 6Execute Decision Governance and Update Venture Journeyexpand_more

• A data-room asset titled AI Scenario Review
• A review note with a verdict, evidence gaps, risks, recommended corrections and a clear continue / repeat / escalate decision
• It should update the venture DNA with specific evidence or decisions about which assumptions move runway, revenue, cash and survival outcomes, create a visible milestone in the founder journey, and generate one or more recommended next tasks

A mentor or evaluator can review the output at the group gate. Programme managers can require an advisor checkpoint before Bertie moves the venture forward.

Draft your output and let Bertie review it