Narrative Intelligence Lab Adoption Logic · Lobby
Why This Lab Exists
The Narrative Intelligence Lab is designed to make adoption logic visible before founders invest time, capital, or credibility in the wrong direction.
You are not here to pitch. You are here to observe how your story meets real systems — where belief forms, where alignment breaks down, and where adoption stalls.
While narrative intelligence spans multiple forms of decision logic, this initial Test Flight is focused specifically on Adoption Logic — how ideas move from belief to alignment to real-world uptake inside complex systems. Other logic models are in development as adjacent Labs and will be introduced deliberately over time.
Adoption Logic refers to the underlying pattern that determines who can say yes, when they can say yes, and under what conditions your idea can realistically be adopted. When that logic is unclear, even strong ideas stall.
How This Lab Works
The Adoption Logic Lab within the Narrative Intelligence Lab is designed as a guided diagnostic environment, not a traditional accelerator module.
In this Lab, storytelling and narrative are treated as related but distinct. A story is how you explain what you’re doing. A narrative is the larger logic that determines whether others can believe it, align with it, and act on it. This Lab focuses on understanding the narrative conditions for adoption before refining stories or pitches.
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Current Adoption RealityYou will begin by describing how your idea is actually being adopted today — who is saying yes, where momentum slows, and what is already working (even imperfectly).
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Adoption ConditionsYou will examine the conditions required for adoption to occur reliably, including roles, dependencies, constraints, and system-level dynamics.
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Experiments & LearningYou will design and run a small number of focused tests to surface real-world signals about adoption — not to prove success, but to reduce uncertainty.
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Synthesis & SignalsYou will reflect on what changed in your understanding and what that means for how you explain, sequence, or scale your work.
Throughout the Lab, AI is used in a limited, observational role — surfacing patterns and ambiguity, not providing answers or recommendations. Facilitators observe and support learning, rather than evaluate performance.
The goal is not to “get it right.”
The goal is to make adoption logic visible before larger bets are placed.
A short check to support honesty, clarity, and psychological safety.
- A current understanding of how your idea is being adopted today
- Willingness to describe reality as it is, not as you wish it to be
- Approximately 30–45 minutes for your initial diagnostic
Everything you share in the Lab is treated as confidential within the context of this Test Flight. Your inputs are used to support your learning and to surface system-level patterns across the cohort — not to evaluate individual performance publicly. Aggregated, anonymized insights may be used to improve future Labs and program design. Individual company details are not shared outside the facilitation and program team.