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 #4,746 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
JustDoThings is a self-reported tool designed to capture ideas exactly as they arrive and prepare them for use in ChatGPT, work, or Codex environments. It allows users to store immutable original text, add context, attach private images, organize ideas in an inbox, and route them via structured AI recommendations.
What changed
The project was submitted to the OpenAI 2026 hackathon by a single founder (Pablo Poo), indicating it is early-stage and likely prototypical. It was built using Next.js, OpenNext, D1, R2, and other technologies, with no evidence of revenue or customer adoption.
The single most important open question
Is there any evidence that JustDoThings has traction, users, or a path to monetization beyond the hackathon submission?
What The Product Actually Is
The description states:
- JustDoThings is a tool for capturing ideas without AI rewriting them.
- It supports adding context while keeping original text immutable.
- Users can attach private images (JPEG, PNG, WebP).
- Ideas are organized in a personal inbox.
- It uses GPT-5.6-luna to provide structured routing recommendations.
- Handoffs to ChatGPT, work, or Codex are reviewed and confirmed before sending.
Inference The tool appears to be a lightweight idea capture and handoff system, built for developers or knowledge workers who want to preserve original ideas and route them to AI tools or platforms like ChatGPT or Codex.
Evidence strength
- Evidenced: The author describes the features and functionality.
- Inferred: That it is a prototype or hackathon project due to lack of commercial evidence.
Positioning & Claim Evolution
The description states:
- “ChatGPT do not have a zone to ‘save’ ideas.”
- “This born to fix that, and the same time help you to print it to ChatGPT or codex.”
Inference Positioning is focused on solving a gap in ChatGPT’s functionality — specifically, idea capture and handoff. The claim evolution suggests a shift from a simple note-taking tool to one that integrates with AI workflows.
Evidence strength
- Evidenced: The author's stated problem and solution.
- Inferred: That this is a niche product for developers or knowledge workers using ChatGPT/Codex.
Target Customer & ICP
The description states:
- The tool is built for users who want to capture ideas and route them to ChatGPT, work, or Codex.
- It supports private image attachments and immutable text — suggesting a need for personal or team-level organization.
Inference The target customer appears to be individual developers, researchers, or knowledge workers who use AI tools like ChatGPT or Codex and want to preserve and organize their ideas before sending them into those systems.
Evidence strength
- Evidenced: The author describes the intended audience through use cases.
- Inferred: That the ICP is narrow — likely early adopters of AI tools who value idea preservation and structured handoffs.
Business Model & Pricing Evidence
The description states:
- No pricing or business model is mentioned.
- The tool was built for a hackathon, with no indication of monetization plans.
Inference There is no evidence of a business model or pricing structure at this stage.
Evidence strength
- Not evidenced: No mention of revenue, pricing, subscriptions, or monetization.
Technical & Delivery Signals
The description states:
- Built with Next.js and OpenNext.
- Uses D1 for data storage, R2 for attachments.
- Integrates with OpenAI API for structured routing.
- Codex deep links are used to prefill composers without auto-submitting.
- Original text is immutable at both API and data layers.
- User UUIDs scope all database queries.
- Attachment downloads require server-side ownership checks.
Inference The tool uses modern cloud-native stack with a focus on security, immutability, and structured workflows. It appears to be built for performance and scalability in a developer context.
Evidence strength
- Evidenced: The technical stack and architecture are described.
- Inferred: That the product is designed for developers or advanced users.
Traction & Maturity Signals
The description states:
- Built for a hackathon (OpenAI 2026).
- Deployed to ChatGPT sites.
- Team size is one person (Pablo Poo).
- No mention of customers, revenue, or usage metrics.
Inference This is an early-stage prototype with no evidence of traction or commercial adoption.
Evidence strength
- Not evidenced: No data on users, revenue, or product maturity beyond a hackathon submission.
Competitive Context
The description states:
- No mention of competitors.
- The tool is positioned to solve a gap in ChatGPT’s functionality.
Inference There may be overlap with tools like Notion, Obsidian, or other idea capture platforms, but no direct competitor is named.
Evidence strength
- Not evidenced: No competitive analysis or market positioning beyond the author's own claims.
Key Risks & Red Flags
The description states:
- The project was built in a hackathon.
- Team size is one person.
- No evidence of traction, revenue, or customer adoption.
- No pricing or monetization strategy is described.
- The tool is described as “broad access and public” in the future — but no roadmap or timeline is given.
Inference Key risks include lack of commercial viability, limited team capacity, and unclear path to product-market fit or monetization.
Evidence strength
- Evidenced: The hackathon origin and single-founder team.
- Inferred: That the project lacks traction or a clear business model.
Diligence Questions To Ask The Founders
- What is your plan for monetization beyond the hackathon?
- Have you tested JustDoThings with real users, or is it still experimental?
- How do you plan to scale from one developer to a broader audience?
- What are the key user pain points you've identified that this tool solves?
- Are there any existing tools in the market that you're directly competing with?
Investment/Partnership Verdict
The description states:
- The project is a hackathon submission by one person.
- No evidence of revenue, customers, or traction.
Inference At this stage, JustDoThings appears to be an experimental idea capture tool with no commercial viability or investment-ready features. It may have potential if it evolves into a product with clear user demand and monetization strategy.
Evidence strength
- Not evidenced: No data on commercial readiness, traction, or scalability.
- Inferred: That the project is early-stage and not yet ready for investment or partnership.
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.