Archive position — measured, not model output
0 likes on Devpost
2,264 of the 7,856 archived projects have more likes, and 5,592 share exactly 0 — so this project's #2,801 place in the like-ranked listing is a tie-break inside that group, not a ranking.
Projects (log scale)
Likes on Devpost. ▲ marks this project's group.
Show the figures
| Likes | Projects | Share of archive |
|---|---|---|
| 0 | 5,592 | 71.2% |
| 1 | 1,758 | 22.4% |
| 2 | 285 | 3.6% |
| 3–4 | 132 | 1.7% |
| 5–9 | 75 | 1.0% |
| 10+ | 14 | 0.2% |
Executive Summary
What the company appears to be
Auntie AI: Blackwards Route Desk is a self-reported tool that uses GPT-5.6 to help Black creators evaluate opportunities by turning public offer terms into an "owner-first route packet". The system returns a decision (Proceed, Clarify, Protect, or Pass) along with ownership checks, questions, and a 24-hour action.
What changed
The project was built during the OpenAI 2026 hackathon as a proof-of-concept app. It uses GPT-5.6 via the OpenAI API, with a D1 ledger for quota enforcement and privacy tracking. The app is described as isolated, not persisting creator summaries or generated packets.
Single most important open question
Is there any evidence of traction, revenue, or adoption beyond the hackathon submission? The description does not state whether this tool has been used by creators outside of the development context.
What The Product Actually Is
The description states that Auntie AI: Blackwards Route Desk is an app that takes a creator’s summary of an opportunity and returns a structured output using GPT-5.6. This includes:
- A decision (Proceed, Clarify, Protect, or Pass)
- Ownership checks
- Extraction signals
- Questions to ask before saying yes
- One 24-hour action
- A receipt checklist
It is described as an isolated app that does not persist user data beyond input hashes and model status. The tool uses a JSON schema for output formatting and includes server-side validation.
Evidence
- The author states the app uses GPT-5.6 with medium reasoning, strict JSON-schema output, no tools, and store:false.
- It uses a D1 ledger to enforce public quotas and store only salted actor hashes, input hashes, model status, latency, timestamps, and counters.
- Creator summaries and generated packets are not persisted.
Inference The app is designed to be privacy-preserving and non-persistent, with no long-term data retention.
Positioning & Claim Evolution
The project claims to address a gap in how Black creators are treated in opportunities — particularly around ownership, credit, rights, compensation, and audience access. It positions itself as a tool that helps creators navigate these issues by turning vague offers into structured, actionable packets.
Evidence
- The author states: “Black creators are routinely asked to move quickly through opportunities while the terms doing the most work remain vague.”
- The app is described as turning public-safe offer terms into an owner-first route packet.
- It is positioned as a tool that helps creators make decisions without legal advice or contract approval.
Inference The project is attempting to solve a problem of power imbalance in creative industries, particularly for Black creators. However, the description does not indicate whether this is a new market need or an existing one.
Target Customer & ICP
The target customer is described as Black creators who are navigating opportunities involving partnerships, funding, publishing, or other forms of collaboration where ownership and rights are unclear.
Evidence
- The inspiration section states: “Black creators are routinely asked to move quickly through opportunities while the terms doing the most work remain vague.”
- The app is designed to help creators evaluate offers in a way that prioritizes their own interests (owner-first).
Inference The ICP appears to be Black creators who are underrepresented or underserved in traditional contract negotiation and opportunity evaluation processes.
Business Model & Pricing Evidence
There is no evidence of pricing, monetization, or business model in the description. The app is described as a hackathon submission with no indication of commercial use or revenue generation.
Evidence
- No mention of pricing, subscriptions, or monetization.
- The app is described as an isolated tool built during a hackathon.
Inference The project has not yet evolved into a commercial product or service. It is currently in a proof-of-concept phase.
Technical & Delivery Signals
The app was built using:
- GPT-5.6 via the OpenAI API
- Cloudflare D1 for ledger and quota enforcement
- Medium reasoning, strict JSON schema output
- No tools, store:false
- Server-side schema validation
- Synthetic packets available if live generation fails
Evidence
- The author states: “The isolated app uses the OpenAI Responses API with GPT-5.6, medium reasoning, strict JSON-schema output, no tools, store:false.”
- D1 ledger is used to enforce public quotas and store only salted hashes and metadata.
- Creator summaries and generated packets are not persisted.
Inference The technical stack suggests a privacy-first approach with minimal data retention. The app is designed for resilience under quota pressure and includes prompt injection and timeout testing.
Traction & Maturity Signals
There is no evidence of traction, adoption, or usage beyond the hackathon submission. No customers, revenue, or user engagement metrics are provided.
Evidence
- The project was built during a hackathon.
- No mention of users, customers, or real-world application.
- No data on how many creators have used it or how often.
Inference The project is in an early stage and has not yet demonstrated any traction or user engagement beyond its development context.
Competitive Context
There is no evidence of existing competitors or a competitive landscape. The description does not mention similar tools or platforms in the space of opportunity evaluation for creators.
Evidence
- No mention of competitors.
- No indication of prior market research or analysis.
Inference The project may be addressing an underserved niche, but there is no evidence to suggest that a competitive landscape exists or has been analyzed.
Key Risks & Red Flags
- No commercial traction or revenue: The app is described as a hackathon submission with no evidence of real-world use.
- Unverified claims: The project makes strong claims about solving systemic issues but provides no data to back them up.
- Limited scope: The tool is isolated and does not persist data, suggesting it may not be scalable or useful beyond its current form.
- No pricing or monetization model: There is no indication of how the product would generate revenue.
Evidence
- No mention of users, customers, or revenue.
- No evidence of a business model or monetization strategy.
- The app does not persist user data.
Diligence Questions To Ask The Founders
- What specific problems are you trying to solve for Black creators in opportunity evaluation?
- How do you plan to scale this beyond the hackathon prototype?
- Are there any real-world users or pilot programs already underway?
- What is your long-term vision for monetization or commercial viability?
- How do you ensure that the tool doesn’t mislead users into thinking it provides legal advice?
Investment/Partnership Verdict
Not evidenced.
The project is described as a hackathon submission with no evidence of traction, revenue, or adoption. It is not clear whether this represents a viable product or service beyond its development phase.
Confidence Low. This analysis is based entirely on self-reported information and lacks any independent verification or data on usage, customers, or commercial viability.
Source
Submitted to the OpenAI 2026 hackathon on Devpost. Project home on DevPost.
The analysis above was generated by a language model from the project's own one-line description. It is not independent research and contains no verified traction, revenue or customer data.