OpenAI 2026 hackathon

Resonance

Resonance is a ChatGPT plugin; it turns a ChatGPT conversation into a plan users can execute, track, and adapt as progress, priorities, and life circumstances change in a dedicated workspace.

Solo project by Azhagarsu Anbarasu · 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 #6,394 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

Resonance is a ChatGPT plugin that aims to bridge conversation and execution by turning structured ChatGPT conversations into persistent, trackable plans. The author describes it as a tool for transforming intentions into guided execution paths, with features like plan validation, progress tracking, and revision proposals.

What changed

The project was built as a hackathon submission (OpenAI 2026) and is described as an MVP focused on professional capability development. It uses ChatGPT, Codex, and GPT-5.6 for reasoning and plugin architecture, with a focus on stateful workflows and persistent execution environments.

Single most important open question

Is there evidence of user adoption or traction beyond the author’s own use case? The description does not indicate any customers, revenue, or usage metrics — only a self-reported MVP built in a hackathon context.

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What The Product Actually Is

The description states that Resonance is a ChatGPT plugin designed to transform conversational intelligence into a persistent execution plan. It allows users to:

  • Begin with a new objective or import an existing ChatGPT plan
  • Clarify outcomes, success criteria, timeframes, and constraints
  • Validate the plan before publishing it to a dedicated workspace (a "ChatGPT Site")
  • Track progress, record reflections, and adapt plans over time

It includes features such as:

  • Milestone-based planning
  • Resource verification
  • Plan versioning
  • Revision proposals with impact analysis
  • Owner-scoped access and authentication

The system is built using ChatGPT (with GPT-5.6), Codex, TypeScript, MCP, and ChatGPT Sites, with a focus on separating reasoning from authority to maintain control over user data.

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Positioning & Claim Evolution

The author positions Resonance as a solution to the problem that valuable insights from ChatGPT conversations often disappear after the conversation ends. The core claim is:

“What if the valuable outcome of a ChatGPT conversation could become a living, trackable, and measurable plan in a dedicated workspace?”

This positioning evolves from:

  • A conceptual gap in AI-assisted planning
  • To an MVP solution that demonstrates a conversation-to-execution loop
  • To a future vision of broader application across personal goals, projects, strategic initiatives, etc.

The author also notes that the MVP currently focuses on professional capability development but has potential for expansion into other domains.

“The underlying idea is broader: plans created through conversation should remain useful after the conversation ends.”

This evolution suggests intent to scale beyond its current narrow scope, though no evidence of such scaling exists in the description.

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Target Customer & ICP

The description states that Resonance targets users who want to turn their ChatGPT conversations into actionable plans. It is initially focused on professional capability development, but the author implies a broader audience.

There is no explicit segmentation or persona described beyond:

  • Users seeking structured follow-up from ChatGPT
  • Individuals looking for persistent execution environments
  • People needing tools to track progress and adapt plans over time

No evidence of specific customer types, job functions, or decision-makers is provided. The ICP remains undefined beyond the general user base of ChatGPT users who seek planning tools.

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Business Model & Pricing Evidence

There is no evidence in the description of a business model or pricing structure. The author describes Resonance as an MVP built for a hackathon and does not mention monetization, subscriptions, or any revenue-generating mechanisms.

The project is presented as a prototype with no indication of paid features or commercial viability.

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Technical & Delivery Signals

Resonance is built using:

  • ChatGPT (with GPT-5.6)
  • Codex for development and collaboration
  • TypeScript, MCP, Next.js, Node.js, React, Vite, Wrangler
  • OpenAI plugins and ChatGPT Sites

Key technical elements include:

  • A stateful workflow driven by confirmation steps
  • A separation of reasoning from authority, where models interpret goals but server logic manages scheduling, authorization, and state transitions
  • Use of MCP tools (12 focused tools) for plugin functionality
  • Persistent storage via ChatGPT Sites
  • Authentication and access control using Sign in with ChatGPT
  • Plan versioning, revision history, and progress tracking

The system supports:

  • Resource verification
  • One-time plan-claim links
  • Email transport layer (for future continuity)
  • Demo mode without sign-in

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Traction & Maturity Signals

There is no evidence of traction or maturity beyond the author’s own development and testing. The project is described as a hackathon MVP, with no mention of:

  • Users or customers
  • Revenue or monetization
  • Product usage metrics
  • Market validation
  • Adoption beyond the creator

The author mentions early challenges in workflow design and real-world testing, indicating that the product is still in an experimental phase.

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Competitive Context

There is no evidence in the description of competitors or competitive positioning. The author does not reference existing tools for:

  • AI-powered planning
  • Execution tracking
  • ChatGPT plugin ecosystems
  • Goal management platforms

The project appears to be self-contained within its own conceptual framework, without comparison to other offerings.

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Key Risks & Red Flags

Several risks and red flags are present based on the description:

  1. No traction or user validation: The product is described as an MVP with no evidence of real-world usage.
  2. Unproven commercial viability: No pricing model, monetization strategy, or revenue streams are mentioned.
  3. Dependency on ChatGPT ecosystem: Reliance on OpenAI’s platform and plugin infrastructure introduces risk if those systems change or become unavailable.
  4. Limited scalability claims: While the author envisions expansion into multiple domains, there is no evidence of progress toward that vision.
  5. Single-person team: The project is built by one individual (Azhagarsu Anbarasu), which may limit development speed and long-term sustainability.

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Diligence Questions To Ask The Founders

  1. What specific user problems are you solving, and how do you know?
  2. Have you tested the product with real users beyond yourself?
  3. How does Resonance differentiate from existing planning or task management tools?
  4. What is your path to monetization and customer acquisition?
  5. Are there any technical dependencies or limitations in the ChatGPT ecosystem that could affect scalability?
  6. What are the key assumptions behind your vision for expanding beyond professional capability development?

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Investment/Partnership Verdict

Not evidenced.

There is no evidence of revenue, customers, traction, or financial performance to assess investment potential or partnership viability. The project is described as a hackathon MVP with no indication of commercial readiness or market validation.

The author’s claims about functionality and future scope are self-reported and unverified. Without external data or user feedback, any assessment of strategic value or return on investment remains speculative.

The product shows promise in concept but lacks the signals typically required for due-diligence evaluation — particularly around adoption, scalability, and business model viability.

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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.