American Heart Association · Narrative Performance

Narrative Performance Test Flight Executive orientation · Founder experience · System learning

Status Active
Mode Lab (diagnostic + artifact-driven)
Why this exists Make adoption conditions visible before scale
What we’re testing Interactive rooms + light AI signals (observational)
Who it’s for Founders + AHA teams designing readiness & validation pathways
Access Invitation-only (program activated)

Welcome

This Test Flight is a structured, interactive environment designed to help innovators and program teams see where adoption succeeds—or collapses—inside real systems.

The goal is not “better pitching.” It’s decision clarity: who decides, who carries risk, what must be true, and what breaks when a solution meets workflow, policy, incentives, and timing.

A note from the American Heart Association

Welcome to the Narrative Performance Test Flight. We’re grateful you’re here. This experience helps us understand what founders need to become truly ready for accelerated validation— and how we can improve the pathway into our Accelerator and Rapid Validation Lab.

(Placeholder message — replace with approved AHA copy, disclaimers, and program language.)

What you’ll do here

You’ll move through a small set of “rooms.” Each room isolates one component of adoption so it can be observed without guessing. This is not linear—sequence is earned based on what the system reveals.

Adoption Logic Map
Make the decision path visible.
Stakeholders · gates · decision conditions
Value Chain
Trace where value stops translating.
Created → Experienced → Recognized → Authorized → Implemented → Rewarded
Workflow / Integration Lab
Where approval collapses under workflow.
Operational absorption · handoffs · adoption cost
Stakeholder Topology
See who controls release.
Power · risk · influence
Founder Topology
How power enters the system.
Presence · proof · positioning
NPI Baseline
Is your narrative usable inside this system?
Compatibility signals (not a grade)
Tip: If you’re unsure where to begin, start with Adoption Logic Map or Value Chain—whichever matches what’s happening in your system.

AI’s role (limited, intentional)

AI is used in a light observational role to reduce blind spots—spotting ambiguity, summarizing patterns, and highlighting missing decision conditions. It does not make decisions, score founders, or replace judgment.

Field Notes (recommended)

As you test assumptions and encounter friction, capture what you’re seeing. These notes help the Lab respond with more specific guidance—and help AHA evaluate RVL readiness.

Quick prompts
  • What surprised you in the system response?
  • What broke under workflow, timing, or risk?
  • What would have to change for “yes” to be safe?