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 #1,663 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
The description states that Pine is a ChatGPT plugin designed to help users make better shopping decisions based on personal taste, values, budget, and history. It allows users to buy items, skip them, or save them to a wishlist. The author built it using OpenAI's tools and frameworks including Codex, GPT-5.6, the Responses API, Apps SDK, Next.js, Supabase, and Railway.
The project appears to be an early-stage prototype submitted to the OpenAI 2026 hackathon. It is not evidenced to have any revenue, customers, or traction beyond its submission. The author pivoted from a standalone web app to a ChatGPT plugin due to market context suggesting high usage of ChatGPT for shopping.
The single most important open question is whether Pine has any commercial viability or traction beyond the hackathon submission — this cannot be determined from the self-reported description alone.
What The Product Actually Is
The description states that Pine works inside ChatGPT and helps users make shopping decisions based on their own taste, values, budget, and history. It enables actions such as buying items, skipping them, or saving to a wishlist.
It is described as a plugin built using OpenAI's Apps SDK, connected to ChatGPT through MCP (Model Control Protocol). The author built it with technologies including Codex, GPT-5.6, the OpenAI Responses API, Next.js, Supabase, and Railway.
The product is presented as an AI-powered shopping assistant integrated into ChatGPT, allowing users to make more thoughtful purchasing decisions.
Positioning & Claim Evolution
The description states that Pine was inspired by a desire to create "a moment of reflection before checkout" rather than traditional shopping tools that aim to increase purchases. It positions itself as helping users decide better rather than buy more.
The author describes a pivot from an initial plan to build just a web app to creating a ChatGPT plugin, citing that many shoppers already use ChatGPT for shopping (80 million shopping questions weekly according to the author).
This evolution suggests a shift toward leveraging existing ChatGPT usage patterns rather than competing with existing wishlist apps.
Target Customer & ICP
The description states that Pine helps users make shopping decisions based on their own taste, values, budget, and history. It targets consumers who use ChatGPT for shopping and want to reflect before purchasing.
The author notes that 80 million shopping questions are received by ChatGPT weekly (source: Stackline), suggesting a large potential user base among ChatGPT users seeking shopping assistance.
No specific customer segments or personas are described beyond general shoppers using ChatGPT for shopping decisions.
Business Model & Pricing Evidence
Not evidenced. The description does not state any pricing model, monetization strategy, or business model details.
Technical & Delivery Signals
The description states that Pine was built with:
- OpenAI tools: Codex, GPT-5.6, Responses API
- Frameworks: Next.js, React
- Infrastructure: Supabase, PostgreSQL, Railway
- Integration: ChatGPT via Apps SDK and MCP (Model Control Protocol)
It is described as a plugin that connects to ChatGPT through the Apps SDK.
Traction & Maturity Signals
Not evidenced. The description states this was submitted to the OpenAI 2026 hackathon and does not provide any evidence of revenue, customers, usage metrics, or product maturity beyond its prototype status.
Competitive Context
The description states that there are "lots of wishlist apps that already exist" but only a few users will use them. It also mentions that "lots of shoppers (80 million shopping questions, source: https://www.stackline.com/news/chatgpt-is-becoming-a-shopping-destination...)" already use ChatGPT to help with shopping.
This suggests Pine is positioned in a competitive landscape where existing wishlist apps exist but are underused, while ChatGPT usage for shopping is high enough to justify the pivot toward a ChatGPT plugin approach.
Key Risks & Red Flags
- The project is described as a hackathon submission with no evidence of traction or revenue
- No pricing model or monetization strategy is provided
- The author states that 80 million shopping questions are received weekly by ChatGPT, but this source is not independently verified
- The product appears to be a prototype with no evidence of commercial viability or user adoption beyond its submission
- The description does not indicate any competitive advantage or defensible position
Diligence Questions To Ask The Founders
- What specific market problem are you solving that existing solutions don't address?
- How do you plan to monetize this product beyond the hackathon prototype?
- Can you provide evidence of user interest or demand for this solution beyond your own usage?
- What is your go-to-market strategy and how will you acquire users?
- How do you plan to scale this beyond a single-person prototype?
- What are the technical challenges in building out this product at scale?
Investment/Partnership Verdict
Not evidenced. The description does not provide sufficient information to assess commercial viability, traction, or investment potential. It is presented as a hackathon submission with no evidence of revenue, customers, or product-market fit beyond its prototype status. The author's own account indicates this is an early-stage idea without demonstrated traction or business model.
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.