OpenAI 2026 hackathon

Quackive — Turn Saved Posts Into Shared Plans

Turn scattered saves into things worth doing together—with the right person, in the right place, at the right time.

Solo project by Tong Shan · 3 likes · 0 comments

Archive position — measured, not model output

3 likes on Devpost

128 of the 7,856 archived projects have more likes, and 93 share exactly 3 — so this project's #191 place in the like-ranked listing is a tie-break inside that group, not a ranking.

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Likes on Devpost. ▲ marks this project's group.

Show the figures
LikesProjectsShare of archive
05,59271.2%
11,75822.4%
22853.6%
3–41321.7%
5–9751.0%
10+140.2%
Devpost like counts for all 7,856 archived projects, captured when this archive was built.

Executive Summary

What the company appears to be

Quackive is a self-reported project that aims to transform saved content into shared plans, with an emphasis on coordination and collaboration around saved items.

What changed

The project was submitted to the OpenAI 2026 hackathon. No further development or public updates are evidenced.

Single most important open question

What is the actual user problem being solved, and how does Quackive propose to solve it in a way that creates value for users beyond simple content saving?

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What The Product Actually Is

The description states: “Turn Saved Posts Into Shared Plans.” It also includes the tagline: “Turn scattered saves into things worth doing together—with the right person, in the right place, at the right time.”

  • The product is described as a tool for converting saved content (posts) into shared plans.
  • It implies coordination or collaboration features around saved items.
  • The author declares that it was built with technologies including React, Python, FastAPI, Supabase, PostgreSQL, Expo.io, GPT-5.6, and others.

Not evidenced What the product actually does beyond this high-level description; no screenshots, demos, or functional details are provided.

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Positioning & Claim Evolution

The author states that Quackive “Turns scattered saves into things worth doing together—with the right person, in the right place, at the right time.”

  • This suggests a positioning around shared planning and coordination.
  • The claim is framed as improving upon simple content saving by enabling collaborative action.

Not evidenced How this differs from existing tools like Pinterest, Notion, or other content-saving platforms; no evolution of claims or prior versions are mentioned.

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Target Customer & ICP

The description does not state who the target customer is. It only implies a need for coordination around saved items.

  • The tagline suggests collaboration as a key feature.
  • No explicit ICP (Ideal Customer Profile) is defined.

Not evidenced Who uses this, what their job function or persona is, or whether it targets individuals, teams, or specific verticals.

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Business Model & Pricing Evidence

There is no evidence of pricing structure, monetization strategy, or business model in the provided description.

  • The author does not state how the product will be sold or who pays for it.
  • No mention of subscriptions, freemium tiers, or any revenue mechanism.

Not evidenced How the company intends to make money.

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Technical & Delivery Signals

The author declares that the project was built using:

  • Codex
  • Expo.io
  • FastAPI
  • Google Places
  • GPT-5.6
  • Native
  • PostgreSQL
  • Python
  • Railway
  • React
  • Supabase
  • TomTom
  • TypeScript
  • These technologies suggest a modern, full-stack application with AI integration and geolocation features.
  • The use of GPT-5.6 indicates an emphasis on generative AI.

Not evidenced Whether the product is functional or deployed; no live demo or working prototype is shown.

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Traction & Maturity Signals

The only evidence of traction is that this project was submitted to a hackathon (OpenAI 2026).

  • No customer base, user engagement, or usage metrics are reported.
  • No funding rounds, partnerships, or product launches beyond the hackathon submission.

Not evidenced Any form of traction, adoption, or maturity beyond the initial concept.

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Competitive Context

The description does not mention any competitors or market context.

  • It is unclear what existing tools Quackive aims to compete with or complement.
  • No competitive analysis or positioning relative to similar platforms (e.g., Pinterest, Notion, Feedly) is provided.

Not evidenced The competitive landscape or how this product fits into it.

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Key Risks & Red Flags

  • Lack of clarity on user problem and solution. The description does not explain what specific issue the product solves.
  • No evidence of functionality or deployment. It's unclear if Quackive is more than a concept or prototype.
  • Unverified claims. All statements are self-reported, with no independent verification.
  • No monetization strategy. No indication of how the company will generate revenue.

Inference If this is a hackathon project, it may not yet be ready for market or product-market fit.

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Diligence Questions To Ask The Founders

  1. What specific user problem does Quackive solve that existing tools do not?
  2. How does the platform enable coordination around saved content?
  3. Is there an MVP or prototype available for review?
  4. What is the intended business model and monetization approach?
  5. Who are the target users, and how did you identify them?
  6. What is the roadmap for development beyond this hackathon submission?

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Investment/Partnership Verdict

Not evidenced No basis to assess investment or partnership potential.

  • The project is described as a hackathon submission with no further development or traction.
  • No evidence of product-market fit, revenue model, or customer validation.
  • The description lacks any indication that Quackive has progressed beyond an idea or prototype stage.

Inference At this point, it is unclear whether Quackive represents a viable business opportunity or a concept in early-stage development.

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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.