Scouts
What should a scout clarify about attribution for an AI application startup?
an AI application startup: Clarify attribution before assuming an introduction creates compensation rights.
Clarify attribution before assuming an introduction creates compensation rights. Programs may distinguish prior contact, first submission, a warm introduction, substantive assistance, and a completed investment. The applicable agreement determines the actual arrangement.
Start with the decision
Ask how the program records a referral and handles duplicates or stale opportunities. Maintain a consent-aware timeline with the information the program actually requires. Obtain qualified legal advice for rights or disputes rather than inferring terms from marketing copy.
The illustrative scenario
This is an educational workbook. The company or fund and all numerical inputs below are fictional. They are not ADIN results, customer claims, market benchmarks, or a forecast.
The fictional team sells an AI assistant to small support departments. A demonstration works on familiar examples, but the product is still testing performance on new customers' queues. Founder time currently covers many exceptions.
Separate model output from completed customer work. A software revenue claim needs a matching view of model usage, human delivery, customer support, and rework.
Turn the scenario into an evidence decision
Consider a review of an AI application startup in which a confident explanation arrives before the supporting records. Start with the first question in the table. Write down what an answer would change: the next interview, the experiment's scope, a request for specialist review, or a decision to wait. A question without a consequence can produce a longer document while adding little understanding.
Next, inspect the record named in the table and record its date, owner, permission boundary, and limitations. Request a permissioned evaluation sample, customer usage cohorts, an exception log, and a cost model that includes human work. Keep actual results distinct from roadmap features. If the record contradicts the explanation, preserve both accounts and ask which definition, period, or workflow differs. Do not silently select the version that makes the opportunity look strongest.
Finish with a conditional statement: if the specified evidence supports the claim under these conditions, take the named next step; otherwise investigate the unresolved question. A timestamp can support a factual timeline while remaining insufficient to establish eligibility. Keep the program's acknowledgment and the governing terms distinct from the scout's own expectation of credit. This worked exercise is about the decision process. It does not assert that a fictional company has met a real diligence standard or that a template can authorize an investment.
| Item | Illustration |
|---|---|
| Decision question | What event creates credit? |
| Case-specific constraint | Separate model output from completed customer work. A software revenue claim needs a matching view of model usage, human delivery, customer support, and rework. |
| Record to inspect | Request a permissioned evaluation sample, customer usage cohorts, an exception log, and a cost model that includes human work. Keep actual results distinct from roadmap features. |
| Comparison to preserve | Compare the promised workflow with the delivered workflow. The relevant question is whether adoption and delivery economics improve together. |
| Unresolved case question | Who reviews failures? |
Use this worksheet
Answer the questions with a source, date, owner, and next action. Mark an unknown as unknown. Use public or permissioned information and involve a qualified specialist when a question requires expertise beyond the team’s competence.
- What event creates credit?
- Was there prior fund contact?
- How are duplicates handled?
- What record is required?
- Who confirms the attribution?
Questions specific to this scenario
- Who reviews failures?
- How much founder work supports each account?
- Which results hold on unseen examples?
Request a permissioned evaluation sample, customer usage cohorts, an exception log, and a cost model that includes human work. Keep actual results distinct from roadmap features.
A concrete next test
Observe a permissioned workflow where the assistant fails or needs founder intervention. Record the human time and what the customer sees. Compare that case with the demo so the diligence discussion addresses delivered work rather than only the best familiar example.
Interpret the result
A timestamp can support a factual timeline while remaining insufficient to establish eligibility. Keep the program's acknowledgment and the governing terms distinct from the scout's own expectation of credit.
Compare the promised workflow with the delivered workflow. The relevant question is whether adoption and delivery economics improve together.
Sources and method
These primary resources provide background for the concepts. The fictional scenario, calculations, and worksheet are ADIN educational examples; the sources do not report or validate those invented results. Reviewed October 11, 2026.