OpenAI 2026 hackathon

Screenshot Studio

Create polished screenshots for every platform.

Solo project by Vitalii Lavreniuk · 0 likes · 0 comments

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 #6,586 place in the like-ranked listing is a tie-break inside that group, not a ranking.

Projects (log scale)

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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

Screenshot Studio is a self-reported tool for creating polished screenshots for app stores, built as a full-stack TypeScript application using Next.js, React, and Konva. The author describes it as a visual workspace that allows users to build reusable layouts, manage assets, and export images at platform-specific dimensions.

What changed

The project was submitted to the OpenAI 2026 hackathon on Devpost by one developer (Vitalii Lavreniuk), who states he built it in a short time using modern web technologies. It is described as intended to be free and open-source, with plans for AI agent integration.

Single most important open question

Is there any evidence of actual usage or adoption beyond the author's own development work?

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What The Product Actually Is

The description states that Screenshot Studio is a visual workspace for creating marketing screenshots for app stores. Users can build reusable layouts, add screenshots and device frames, manage fonts and assets, prepare designs for different locales, and export images at exact platform dimensions.

It uses a schema-validated JSON document as its single source of truth for layouts, screens, locales, assets, fonts, and export targets.

The tool includes:

  • A browser-based rendering pipeline used across the editor, previews, CLI, and final exports
  • Data-driven platform configuration instead of hard-coded dimensions
  • A CLI for automated exports and repeatable workflows

Evidence The author's own write-up.

Inference The product appears to be a developer-facing tool focused on app store screenshot creation, with an emphasis on reusability and automation.

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Positioning & Claim Evolution

The description states that Screenshot Studio was inspired by the repetitive and time-consuming task of creating polished App Store screenshots. It is positioned as a solution that combines elements from various existing tools (paid, free, open-source, Fastlane, AI-assisted) but aims to be a complete long-term solution.

It is described as:

  • A tool for saving developers time
  • Intended to reduce the cost of publishing an app
  • Free and open-source
  • Designed to be reusable, automatable, and version-controlled

The author also mentions future plans including built-in AI agent support, which suggests a shift toward more automated workflows.

Evidence The author's own write-up.

Inference The positioning evolved from solving a personal pain point into a broader developer tool with potential for AI integration.

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Target Customer & ICP

The description states that Screenshot Studio is aimed at iOS developers who need to create marketing screenshots for app stores. It is described as a tool that helps reduce the time and cost of publishing an application.

It also mentions that it supports multiple platforms (iOS, Android, etc.) through data-driven platform configuration.

Evidence The author's own write-up.

Inference The primary customer segment appears to be mobile developers working on app store submissions. There is no evidence of other target segments or personas beyond this.

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Business Model & Pricing Evidence

The description states that Screenshot Studio is intended to be free and open-source, allowing other developers to use it, improve it, and build on top of it.

There is no mention of any commercial pricing model or monetization strategy in the provided text.

Evidence The author's own write-up.

Inference No evidence of revenue streams or pricing models beyond the stated intention to make it free and open-source.

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Technical & Delivery Signals

The project was built using:

  • Next.js, React, Konva
  • TypeScript
  • Node.js
  • Playwright for testing
  • Vitest for unit tests
  • Zod for schema validation
  • Zustand for state management
  • Tailwind CSS for styling
  • PNPM as package manager

It uses a shared browser-based rendering pipeline across editor, previews, CLI, and exports to ensure consistency.

The architecture includes:

  • Schema-validated JSON document as single source of truth
  • Data-driven platform configuration
  • CLI support for automated workflows

Evidence The author's own write-up and technology tags.

Inference The technical stack suggests a modern web application with strong emphasis on developer experience, automation, and consistency.

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Traction & Maturity Signals

The description states that the project was submitted to the OpenAI 2026 hackathon on Devpost. It is described as being built in a short period by one developer (Vitalii Lavreniuk).

There is no evidence of:

  • Revenue
  • Customers
  • User adoption
  • Product-market fit
  • Market traction

The author notes that the project is intended to be released as open-source and to collect feedback from the community.

Evidence The author's own write-up.

Inference No evidence of traction or maturity beyond initial development and submission to a hackathon.

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Competitive Context

The description states that the author tried various paid tools, free solutions, open-source projects, Fastlane workflows, and AI-assisted approaches before building Screenshot Studio. None felt like a complete long-term solution.

It is positioned as an alternative to these existing tools, with a focus on:

  • Reusability
  • Automation
  • Version control
  • Cross-platform support

There is no mention of direct competitors or competitive positioning beyond the author's own experience with other tools.

Evidence The author's own write-up.

Inference The competitive landscape includes a range of existing solutions, but there is no evidence of specific competitor names or market share data.

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Key Risks & Red Flags

  • Lack of traction: No evidence of users, customers, or adoption beyond the author’s own development.
  • Single-person team: Only one developer (Vitalii Lavreniuk) is mentioned, which raises concerns about scalability and long-term maintenance.
  • Unproven market demand: The tool is described as intended to be free and open-source, suggesting no commercial revenue model or clear monetization path.
  • AI integration uncertainty: Future AI agent support is described but not demonstrated in current functionality.
  • No external validation: No third-party reviews, testimonials, or community engagement beyond the hackathon submission.

Evidence The author's own write-up.

Inference These are risks based on absence of evidence rather than explicit claims.

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Diligence Questions To Ask The Founders

  1. What specific problems do you observe in current workflows for creating app store screenshots?
  2. How many developers have expressed interest in using this tool beyond the author's own use case?
  3. Are there any early adopters or users who have provided feedback on usability or features?
  4. What is your plan for community engagement and open-source contribution?
  5. How do you intend to sustain development if it remains free and open-source?
  6. What are the key technical challenges that remain unresolved in the current version?
  7. Have you considered how AI integration will be implemented and tested?
  8. What metrics or KPIs would indicate product success for this tool?

Evidence The author's own write-up.

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Investment/Partnership Verdict

Not evidenced.

The description provides no information about:

  • Revenue
  • Customers
  • Market traction
  • Financial performance
  • Strategic fit for potential investors or partners

This is a self-reported, unverified account of a tool built by one developer as part of a hackathon submission. There is no evidence of commercial viability, market demand, or any form of traction.

Evidence The author's own write-up.

Inference No basis for investment or partnership consideration based on the provided information.

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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.