Archive position — measured, not model output
1 like on Devpost
506 of the 7,856 archived projects have more likes, and 1,758 share exactly 1 — so this project's #1,561 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
NurseList is a scheduling tool for operating-room staff, built as a hackathon project using GPT-5.6 and deterministic mathematical planning. It claims to offer "fair" weekly scheduling with constraints managed by AI.
What changed
The project was submitted to the OpenAI 2026 hackathon, indicating it is in early development or prototype stage. No commercial traction, revenue, or customer data are evidenced.
Single most important open question
Is there a viable market need for this type of scheduling tool, and does the author have a plan to move beyond the hackathon prototype?
Analysis basis
Self-reported only. The description is from a Devpost submission for a hackathon project. No external verification or evidence of traction, revenue, customers, or product-market fit is provided.
What The Product Actually Is
The description states:
- NurseList is a scheduling tool for operating-room staff.
- It uses GPT-5.6 constraints and deterministic mathematical planning.
- It claims to offer "fair" weekly scheduling.
- Built with Cloudflare D1, Cloudflare Workers, Codex, GPT-5.6, React, and TypeScript.
Inference The product appears to be a prototype or proof-of-concept built for a hackathon. It is not evidenced to be in production or used by any organization.
Positioning & Claim Evolution
The description states:
- Tagline: “Fair weekly operating-room scheduling with GPT-5.6 constraints and deterministic mathematical planning.”
Claim
The product positions itself as an AI-powered, fair scheduling solution for hospital operating rooms.
Inference This is a self-stated positioning, not validated by market data or customer feedback.
Target Customer & ICP
The description states:
- It targets operating-room staff scheduling.
- No further segmentation or customer profile is provided.
Not evidenced No information on hospital size, type of facility, or specific user roles (e.g., nurses, anesthesiologists, administrators) is given. The ICP is not defined.
Business Model & Pricing Evidence
The description states:
- No pricing model, subscription details, or monetization strategy are provided.
Not evidenced There is no evidence of a business model, pricing structure, or revenue streams. The project is described as a hackathon submission.
Technical & Delivery Signals
The description states:
- Built with Cloudflare D1, Cloudflare Workers, Codex, GPT-5.6, React, and TypeScript.
- Uses "deterministic mathematical planning" alongside GPT-5.6 constraints.
Inference The technical stack suggests a lightweight, serverless architecture. The use of GPT-5.6 implies AI integration, but no evidence of performance, scalability, or delivery mechanism is provided.
Traction & Maturity Signals
The description states:
- Submitted to the OpenAI 2026 hackathon.
- Team size: 1 (Deniz Arda Aslan).
- No mention of users, customers, revenue, or product usage.
Not evidenced There is no evidence of traction, adoption, or maturity beyond a hackathon submission. The project is in early development.
Competitive Context
The description states:
- No mention of competitors or market landscape.
Not evidenced No information is provided about existing solutions for operating-room scheduling or how NurseList compares to them.
Key Risks & Red Flags
- The project is a hackathon submission with no evidence of commercial viability.
- One-person team implies limited development capacity.
- Use of GPT-5.6 suggests reliance on an unproven or hypothetical technology.
- No evidence of market need, customer feedback, or product-market fit.
Inference The lack of traction and business model raises concerns about scalability and commercial potential.
Diligence Questions To Ask The Founders
- What is the specific problem you're solving in operating-room scheduling?
- How did you identify this market need?
- Are there any hospitals or healthcare systems interested in testing or using this tool?
- What is your plan to move beyond the hackathon prototype?
- How do you intend to monetize this product?
Investment/Partnership Verdict
Not evidenced No evidence of a business case, traction, or commercial potential exists.
Inference At this stage, NurseList appears to be an early-stage idea or prototype with no demonstrated path to market or revenue. It is not ready for investment or partnership consideration based on the provided information.
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.