Cue Good
FAQ
FAQ — Overview
This FAQ defines how the prompt systems operate as disciplined innovation infrastructure rather than generic AI interaction. It clarifies the architectural role of prompts in exposing invisible failure seams, surfacing hidden assumptions, and converting them into enforceable boundaries that govern innovation before execution begins. The content distinguishes what the prompts enable, what they deliberately exclude, and how responsibility, ownership, and validation are structurally allocated.
The purpose of this page is to remove ambiguity for founders, engineers, enterprises, and procurement reviewers by specifying the invariants, limits, and control surfaces of prompt-driven innovation. By articulating how contradictions are eliminated, cascade risks are neutralized, and correctness is designed into the build from inception, this FAQ establishes a shared understanding of how innovation remains coherent, pressure-resilient, and fully owned by the client prior to any build commitment..
General Product Scope
Q: What does the Company provide?
The Company licenses proprietary prompt systems consisting of structured prompt architectures, logic frameworks, sequencing methodologies, and implementation-ready instructional materials. These materials function as analytical and architectural tools rather than software applications or automated services.
Q: Is this software, a platform, or a service?
No. The Company does not provide software, platforms, hosted services, or managed execution. The licensed materials are intellectual property delivered for internal use by the client.
Q: Who is the intended user of these materials?
The materials are intended for internal use by the licensed entity and its authorized personnel acting within the scope of the license. They are not intended for resale, external delivery, or client-facing services.
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Intellectual Property and Ownership
Q: Who owns the outputs generated using the prompt systems?
Subject to the license terms, the client owns the outputs it generates, including internal designs, strategies, specifications, documentation, and implementations derived through use of the materials.
Q: What does the Company retain ownership of?
The Company retains exclusive ownership of the prompt structures, logic gates, sequencing, methodologies, and underlying architecture. These elements are licensed, not sold or transferred.
Q: Can outputs be shared externally?
Outputs may be shared or commercialized provided they do not disclose, reproduce, or reveal the licensed prompt materials, structures, or methodologies themselves.
Q: Do outputs grant any rights to reuse the prompt system?
No. Ownership of outputs does not grant any right to extract, reuse, sublicense, or replicate the licensed materials.
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Authorized Use and Restrictions
Q: What is considered authorized use?
Authorized use includes internal evaluation, internal operations, internal research and development, and internal workflow use solely for the licensee’s own benefit.
Q: What uses are expressly prohibited?
The licensed materials may not be used for resale, service bureau activities, external client delivery, consulting deliverables, or embedding into customer-facing systems.
Q: May affiliates or subsidiaries use the materials?
Only the named licensee and its authorized users may use the materials unless affiliate use is expressly permitted in writing.
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Pricing, Payment, and Refunds
Q: Are purchases refundable?
No. All fees are final and non-refundable once incurred, as specified in the applicable pricing and payment terms.
Q: When is payment due?
Payment timing, invoicing, and accepted payment methods are governed by the pricing schedule and payment terms incorporated into the license agreement.
Q: What happens if payment is not made?
Failure to pay amounts due may result in suspension of access and other remedies as provided in the license agreement.
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Verification, Validation, and Outcomes
Q: Does the Company guarantee results or outcomes?
No. The licensed materials provide structured analytical guidance only. No outcomes, performance levels, or results are guaranteed.
Q: Who is responsible for validating outputs?
The client is solely responsible for reviewing, validating, and approving all outputs prior to use or implementation.
Q: Is this legal, financial, or professional advice?
No. The materials do not constitute legal, financial, medical, regulatory, or professional advice.
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Iteration, Changes, and Governance
Q: Can outputs be iterated or modified?
Yes. Iteration is expected. Material changes to inputs require re-execution and revalidation of outputs.
Q: Should outputs be version-controlled?
Yes. Version control supports internal governance, traceability, and audit readiness.
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Support and Services
Q: Does the Company provide implementation or execution support?
No. Implementation, deployment, and execution remain the client’s responsibility unless separately agreed in writing.
Q: Is technical or operational support included?
No support obligations are implied. Any support services must be contracted separately.
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Compliance and Risk Allocation
Q: Can the materials be used in regulated environments?
Yes, as analytical tools. Compliance with applicable laws and regulations remains the client’s responsibility.
Q: What happens if inputs are incomplete or inaccurate?
Output limitations resulting from inaccurate or incomplete inputs do not constitute defects or failures of the materials.
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Confidentiality and Data Use
Q: Does the Company store client inputs or outputs?
The Company does not require storage of client inputs or outputs beyond delivery of the licensed materials.
Q: Is client data used to train AI models?
Data handling depends on the AI platform selected by the client. The Company does not require client data for model training.
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Termination and Post-Termination
Q: What happens if the license ends?
Upon termination, use of the licensed materials must cease. Ownership, confidentiality, restrictions, and other designated provisions survive termination as specified in the agreement.
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Precedence and Updates
Q: What controls if there is a conflict between this FAQ and the agreement?
The executed license agreement and schedules control in all cases.
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Q: “What problem do you solve for us, specifically?”
A: CueGood solves a recurring diligence and innovation failure mode: firms accumulate data, memos, and opinions, but the reasoning that converts those inputs into a defensible decision is often unstated, non-repeatable, and vulnerable to narrative drift. CueGood licenses structured prompt architectures that impose a governed sequence—definitions, constraints, assumptions, measurable indicators, dataset mapping, verification gates, and evolution rules—so investment theses and build theses become reviewable, auditable artifacts instead of persuasive stories. The operational result is not “better data,” but a materially cleaner decision record: what is known, what is assumed, what must be verified, and what would invalidate the thesis before capital or build effort is committed.
Q: “What exactly is the product, in legal terms?”
A: The product is licensed intellectual property: structured prompt architectures, including a protected sequencing logic, controlled vocabulary, artifact schemas, and verification mechanics that govern how a user converts ambiguity into a blueprint-grade governance draft. CueGood is not selling a software application, hosted platform, implementation service, or advisory engagement. The license grants internal-use rights to employ the prompt architectures for internal evaluation, diligence, planning, and specification. The client’s outputs belong to the client; the underlying prompt architecture remains CueGood’s retained IP and is provided under license, not transfer of ownership.
Q: “What do we actually receive—what are the deliverables?”
A: The client receives a defined artifact set generated through use of the licensed prompt architecture. In plain terms: governance-grade blueprints and decision objects that can be reviewed by an investment committee, counsel, procurement, or engineering leadership without interpretive guesswork. Typical deliverables include: (i) a scope-locked architecture map (modules/nodes/responsibilities), (ii) a constraint and invariants register, (iii) an assumptions register with test conditions, (iv) a metric definition list tied to datasets and collection feasibility, (v) option sets with explicit trade-offs and dependency disclosures, (vi) verification gates that identify what must be true before proceeding, and (vii) evolution rules that preserve correctness when conditions change. CueGood does not deliver code, deployments, compliance determinations, or operational custody of the client’s program.
Q: “How does this work, operationally, without becoming consulting?”
A: Operationally, CueGood functions as a governed method the client can run internally. The client supplies context through defined control points; the licensed prompt architecture forces ordered progression through intent clarification, constraint definition, gap isolation, demand articulation, architectural specification, dependency mapping, and verification control design. CueGood’s role is limited to licensing that architecture and describing its intended use; the client runs it, produces outputs, and decides whether to act. Any optional assistance beyond licensing—such as training sessions or workshops—must be separately contracted and does not convert the relationship into implementation or advisory work absent explicit written terms.
Q: “How is this different from a standard quantitative evaluation workflow?”
A: Standard quantitative workflows are often data-rich and method-thin: they compute ratios, benchmarks, and dashboards but may fail to record the governing logic that determines why a metric was chosen, what dataset supports it, what assumptions are embedded, and what evidence would disconfirm the thesis. CueGood does not replace statistical tools; it governs the translation from data to decision. It requires the user to define terms, select measurable indicators with stated rationale, bind each indicator to a dataset source and collection method, declare assumptions as explicit objects, and establish verification gates that determine whether the decision is permitted to proceed. The result is a decision framework that can be reproduced across deals and audited after the fact.
Q: “Show me what the output looks like and how reliable it is.”
A: CueGood outputs are structured artifacts designed to be reviewable, not free-form prose. Their reliability is not framed as predictive accuracy; it is framed as structural integrity: the artifacts explicitly separate known facts from assumptions, record dependencies, and require verification checkpoints before action. Each output is designed to be interrogated: reviewers can locate where a conclusion depends on a dataset, where it depends on an assumption, what test would validate it, and what condition would invalidate it. This makes the output dependable as a governance instrument—because it does not require trust in narrative; it requires traceable reasoning and client-side validation.
Q: “How do you identify unmet demand without turning this into market research or advice?”
A: CueGood does not claim to forecast markets or guarantee demand. The system surfaces candidate unmet demand by forcing explicit articulation of: (i) the user pain in operational terms, (ii) the constraints producing that pain, (iii) why incumbent solutions fail structurally (not rhetorically), and (iv) the value-release conditions if constraints are removed. The output is a demand hypothesis expressed as testable statements tied to measurable signals and verification plans. This preserves the boundary: CueGood supplies a governed method for forming and stress-testing demand hypotheses; the client validates through its own diligence, customer discovery, experiments, or third-party research.
Q: “How does this translate into ROI for a VC or portfolio company?”
A: CueGood is sold as pre-execution governance infrastructure. The primary economic value is reduction of avoidable waste: ambiguity-driven rework, scope churn, unowned dependencies, and late-stage reversals caused by unstated assumptions. For a VC firm, the benefit presents as a cleaner investment committee record and faster internal alignment because the thesis is decomposed into decision objects and verification gates. For a portfolio company, the benefit presents as faster specification and fewer design resets because constraints, interfaces, and acceptance criteria are defined before build. ROI is measured by the client using its own internal metrics (cycle time, iteration counts, rework rates, decision latency), without any claim that a particular return will occur.
Q: “What is the moat—why can’t we replicate this ourselves after one use?”
A: The client can reproduce its own outputs indefinitely because it owns them. The non-replicability is in the licensed framework: the protected sequencing logic, controlled vocabulary, artifact schemas, and governance mechanics that produce consistent results across contexts. That framework is retained IP and is licensed for internal use only; it is not authorized for redistribution, resale, publication, or use as a service for third parties. In other words: the client owns what it produces; CueGood retains what makes the method systematically reproducible as a product.
Q: “Can we deploy this across the whole firm and portfolio—what are the usage rights?”
A: Usage rights are governed by the license scope. A VC purchaser typically wants (i) internal use at the firm level and (ii) controlled extension to portfolio companies. CueGood can accommodate that, but it must be explicit: who is an authorized user, whether portfolio use is included, whether affiliates are included, and whether there are boundaries on external sharing of the licensed materials. Outputs remain owned by each generating entity; the licensed framework remains CueGood’s retained IP and must not be transferred except as expressly permitted under the agreement.
Q: “What are the confidentiality, security, and data-handling implications?”
A: CueGood does not require custody of deal data to license the framework. The client controls what information is entered into any AI system and remains responsible for platform selection, access controls, and confidentiality safeguards. The safest operational posture is that sensitive investment data and proprietary portfolio data are either anonymized or processed under the client’s own approved tooling environment. CueGood’s product is the methodology and prompt architecture; it does not require ingestion of client data into CueGood systems as a condition of use unless separately agreed.
Q: “What are the legal boundaries—advice, reliance, liability, and responsibility allocation?”
A: CueGood is not a provider of legal, financial, regulatory, or professional advice, and it does not certify outcomes, performance, compliance status, or market success. The product is a licensed governance instrument that structures how the client reasons and documents decisions. Responsibility allocation is explicit: the client validates outputs, makes decisions, and implements deployments; CueGood supplies the licensed prompt architecture and its documentation. The legal objective of this boundary is to prevent implied advisory reliance and to preserve clear ownership: the client owns outputs and downstream implementations; CueGood retains ownership of the underlying prompt architecture and licenses it under defined permitted-use and restriction terms.
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Q: 1) “What problem do you solve that PitchBook/AlphaSense/Carta do not?”
A: Those tools are inputs (data, documents, benchmarks). CueGood is the governance layer that converts inputs into a structured, auditable decision artifact by forcing: (i) explicit definitions, (ii) constraint enumeration, (iii) assumption registration, (iv) measurable metric selection, and (v) verification gates. CueGood does not replace data providers; it formalizes how the firm reasons from them.
Q: 2) “Are you claiming better investment performance?”
A: No. CueGood makes no representation or warranty of returns, deal outcomes, or accuracy of market predictions. CueGood licenses a structured methodology that improves process integrity—clarity, traceability, and disciplined evaluation—while decision authority and validation remain exclusively with the client.
Q: 3) “Define ‘quantitative, data-driven evaluation’ the way you use it.”
A: A controlled process in which a firm selects measurable indicators and relevant datasets, applies consistent analytic methods, and produces a decision record that is reviewable, comparable across opportunities, and resistant to narrative drift—without reliance on subjective impressions as the controlling basis.
Q: 4) “Show me what you produce—concretely.”
A: CueGood prompt architectures yield client-owned artifacts such as:
• a requirements list for the evaluation tool/process,
• a metric-to-dataset mapping (what is measured, from where, and why),
• a JSON-like schema for measurable metrics and datasets (for internal tooling),
• If/Then decision logic suitable for algorithmic screening,
• a weakness/strength/opportunity register with evidentiary hooks (what would prove or disprove each claim),
• and a governance draft that can be handed to an analyst team without ambiguity.
CueGood does not deliver code, deployments, compliance determinations, or operational custody of the client’s program.
Q: 5) “How is this ‘more effective’ than our current system?”
A: CueGood is more effective in method, not by promising outcomes. It increases effectiveness by reducing common diligence failure modes:
• Unstated assumptions (now enumerated and testable),
• Metric confusion (now defined and bound to datasets),
• Inconsistent scoring across deals (now standardized),
• Narrative substitution for evidence (now flagged and gated),
• Non-reproducibility (now versioned and auditable).
CueGood is not “a million times better” as a factual claim; it is materially more disciplined because it structures the reasoning and forces verification duties into the artifact.
Q: 6) “Does this integrate with our tools?”
A: CueGood does not require integration to function because it is a licensing of prompt architectures. Operationally, it can be used alongside existing systems (PitchBook, AlphaSense, Carta exports, portfolio monitoring tools) by treating their outputs as inputs into the governed evaluation sequence.
Q: 7) “What’s the moat? Why can’t we replicate the prompts?”
A: The protectable asset is the prompt architecture: sequencing logic, controlled vocabulary, decision templates, verification gates, and governance structure. The client owns the outputs it generates; the underlying framework remains CueGood’s retained IP, licensed for internal use only.
Q: 8) “Is this consulting?”
A: No. The product is licensed intellectual property. Any services—if ever offered—would require a separate written agreement and do not alter the baseline allocation: the client validates, decides, and implements.
Q: 9) “If we give this to portfolio companies, what happens to ownership?”
A: Portfolio companies own their generated outputs and downstream implementations. They do not acquire rights to extract, sublicense, or redistribute CueGood’s underlying framework unless the licensing instrument expressly grants such rights.
Q: 10) “What about confidentiality and sensitive deal data?”
A: CueGood does not need custody of deal data to license the framework. The client controls what inputs are provided to any AI system and retains responsibility for confidentiality controls, access policies, and platform selection.
Q: 11) “What makes your method ‘quant’ rather than just structured writing?”
A: CueGood enforces quant-readiness by requiring: measurable metrics, dataset identification, method selection, and explicit If/Then logic—so a qualitative thesis is converted into structured objects suitable for statistical review, scoring, or automation by the client.
Q: 12) “What is the deliverable we can show Investment Committee?”
A: A governed IC-ready packet format: definitions, metrics, datasets, analytic methods, key findings, failure modes, verification gates, and a record of what is known vs assumed—so IC discussion is anchored to testable claims rather than persuasion.
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Q: 1) What exactly is the “Product” I am purchasing?
A: CueGood licenses proprietary prompt architecture—i.e., structured prompt frameworks, sequencing logic, and governed reasoning methodology—delivered as intellectual property for internal use by the licensee; it is not a software application, hosted platform, managed service, automation system, or advisory engagement.
Q: 2) What do we receive, in concrete deliverable form?
A: You receive the licensed prompt materials and the associated methodology documentation sufficient for internal users to generate client-owned outputs such as architectures, designs, specifications, workflows, strategies, and governance drafts; CueGood does not deliver implementation artifacts as a matter of product scope.
Q: 3) Are you selling “innovation” or “diagrams”?
A: CueGood sells governance of innovation specification—a disciplined method that structures intent, constraints, architecture, verification, and evolution—where diagrams may be included as an output form, but the deliverable category is broader: governance drafts and blueprint-grade specifications generated by the licensee under the framework.
Q: 4) Is this consulting disguised as a product?
A: No. The product is licensed intellectual property delivered for internal use; no managed execution, implementation support, or implied support obligation attaches absent a separate written agreement.
Q: 5) If this is not execution, what is the actual value to a VC?
A: The value is pre-execution discipline: the framework forces assumptions, constraints, dependencies, and verification checkpoints into visibility before commitment—reducing “narrative diligence,” preventing unowned responsibility, and accelerating the formation of internally operable, reviewable blueprints that your investment team and portfolio teams can validate and act upon.
Q: 6) Are you claiming you can “find unmet demand” and “solve the biggest problems”?
A: CueGood makes no guarantee of market success, outcomes, or demand realization; rather, the framework requires explicit articulation of user pain, constraints, failures of existing solutions, and value-release conditions, thereby structuring evaluation of unmet demand and converting uncertainty into defined decision objects for client validation.
Q: 7) What prevents this from being “speculation dressed up as structure”?
A: The framework is expressly designed to eliminate reliance on ad hoc ideation by requiring ordered progression (intent → constraints → architecture → verification → evolution) and by requiring assumptions, boundaries, failure-mode consideration, and verification checkpoints; the client remains responsible for truth-testing and validation.
Q: 8) What do you guarantee?
A: CueGood guarantees only what can be warranted as a licensor of IP: delivery of the licensed materials as described; no outcomes, performance levels, or results are guaranteed, and no reliance is invited as a substitute for client judgment.
Q: 9) Who owns what? (Outputs vs framework)
A: Subject to the license terms:
• The licensee owns the outputs it generates, including internal designs, specifications, documentation, implementations, and derivative systems; CueGood asserts no ownership over such outputs.
• CueGood retains exclusive ownership of the prompt structures, sequencing logic, methodologies, and protected core frameworks, which are licensed, not sold, and remain non-transferable.
Q: 10) Can we share outputs externally (e.g., with founders, co-investors, customers)?
A: Outputs may be shared or commercialized provided they do not disclose, reproduce, or reveal the licensed prompt materials, structures, or methodologies; ownership of outputs does not grant any right to extract, reuse, sublicense, or replicate the underlying framework.
Q: 11) Can we use it across our portfolio? What about affiliates?
A: Authorized use is internal to the named licensee and authorized personnel; affiliate/subsidiary use is not presumed and must be expressly granted in writing if required.
Q: 12) What uses are prohibited?
A: The licensed materials may not be used for resale, service bureau activities, external client delivery, consulting deliverables, or embedding into customer-facing systems; the framework is intended for internal evaluation, operations, R&D, and internal workflow use.
Q: 13) Is this legal/compliance advice?
A: No. The materials do not constitute legal, financial, medical, regulatory, or professional advice, and the system does not interpret law, determine regulatory sufficiency, or issue compliance conclusions.
Q: 14) If we use it in regulated environments, what is CueGood’s responsibility?
A: CueGood’s role remains limited to licensing analytical instruments; responsibility for validating outputs, ensuring compliance with applicable law, and approving implementation remains entirely with the client, including the client’s counsel and compliance functions.
Q: 15) What about confidentiality and data handling?
A: CueGood does not require storage of client inputs or outputs beyond delivery of the licensed materials; data handling depends on the AI platform selected by the client, and CueGood does not require client data for model training.
Q: 16) How is “independence / no dependency” enforced?
A: The methodology forces identification of reliance points (vendors, opaque services, non-auditable components) and requires that each dependency be justified, replaced with an internally operable alternative, or explicitly accepted as a bounded exception—so that outputs can be internally executable without ongoing operational reliance on CueGood.
Q: 17) How do we evaluate ROI if you refuse outcome claims?
A: ROI is evaluated as risk reduction and decision efficiency: reduction of ambiguity, earlier visibility of constraints/dependencies, fewer late-stage reversals, and improved auditability/traceability of reasoning; CueGood does not represent that any particular ROI will be achieved, but the artifact structure is designed to make those efficiencies measurable by the licensee.
Q: 18) How do updates work? Do you maintain version control or backward compatibility?
A: The framework expects iteration and revalidation upon material input changes; where updated prompt materials are provided, the executed agreement governs precedence and update rights, and version control is recommended as an internal governance measure.
Q: 19) What happens if our inputs are wrong?
A: Limitations arising from inaccurate or incomplete inputs do not constitute defects or failures of the licensed materials; outputs remain subject to client review and validation before use.
Q: 20) What is your support model?
A: No support obligations are implied by default; any support services must be contracted separately in writing, and implementation/execution remains the client’s responsibility unless separately agreed.
Q: 21) What are commercial terms: payment, refunds, remedies?
A: Fees are final and non-refundable once incurred; payment timing and remedies for non-payment are governed by the pricing schedule and incorporated license terms.
Q: 22) What happens at termination?
A: Upon termination, use of the licensed materials must cease; surviving provisions (ownership boundaries, confidentiality, restrictions, etc.) remain enforceable as specified in the agreement.
Q: 23) “What is the smallest ‘wedge’ use case you win consistently?”
A: CueGood is designed for pre-execution phases where failure is cheapest to prevent—e.g., investment diligence, architecture formation, constraint and dependency mapping, and governance draft creation—prior to build commitment.
Q: 24) “How do we avoid IP leakage inside a portfolio?”
A: Use is limited to authorized internal personnel; redistribution, resale, disclosure of the underlying logic, and service-bureau use are prohibited; outputs may be shared only insofar as they do not reveal the protected framework.
Q: 25) “If this is so powerful, why can’t we replicate it after one purchase?”
A: You can replicate outputs (you own them). You cannot replicate or transfer the protected prompt architecture and sequencing logic, which remains CueGood’s retained IP and is licensed, not sold; output ownership does not grant extraction, reuse, sublicensing, or replication rights in the framework.
Q: 26) “Does this create an implied advisory relationship or fiduciary duty?”
A: No. The product is expressly framed as licensed analytical guidance; it does not constitute advice, does not make decisions, does not certify outcomes, and does not assume responsibility for implementation—thus preventing reasonable reliance as a substitute for professional judgment or client governance.
Q: 27) “What is the ‘truth test’—how do we know outputs are not hallucinated?”
A: The framework does not purport to be a truth oracle; it is a governance instrument that requires explicit assumptions, constraints, and verification checkpoints, and it allocates validation duty to the client before any use or implementation.