Prism

Project: Prism

Tagline: Prism: An AI Native Decision Workspace

Author's Self-Description: A single-person hackathon project built with Next.js, React, Tailwind CSS, and OpenAI’s GPT 5.6 API. The author states that the product is an AI-native workspace to help users reason through complex decisions, rather than simply recommend a path forward.

What Changed: The author reports building a tool that shifts from providing direct answers to helping users understand the reasoning process behind decisions. It is described as a structured decision-making interface that explores goals, constraints, risks, and assumptions using AI.

Key Open Question: Is there evidence of a real user need or market traction for this type of AI-powered reasoning workspace? The description contains no data on usage, adoption, revenue, or customer feedback beyond the author’s own account.

The description states that Prism is an AI native Decision Workspace. It is described as a tool that:

• Helps users understand complex decisions before making them.
• Identifies goals, constraints, assumptions, risks, opportunities, and unknowns.
• Explores the decision through dynamic reasoning lenses.
• Generates alternative scenarios and stress-tests assumptions.
• Ends with thoughtful reflections to support informed decision-making.

It is built using:

• Frontend: Next.js, React, Tailwind CSS, Framer Motion
• Backend/API: OpenAI Responses API with GPT 5.6
• Development Tools: Codex, GitHub, Vercel

Inference: The product appears to be a web-based interface that uses AI to structure decision-making processes. It is not a chatbot or a general-purpose assistant but a specialized tool for reasoning.

The author states that the inspiration came from personal uncertainty about academic decisions (GATE vs placements), and that existing AI assistants were too quick to give answers without explaining the thinking process.

Claim: Prism is designed to help users reason through decisions rather than simply recommend one path.

Inference: The positioning evolved from a personal problem-solving tool into a broader concept of an AI-powered decision workspace. It is not described as competing with existing AI assistants but as offering a different interaction model — one that emphasizes understanding over recommendation.

The author states that the long-term vision includes:

• Students
• Professionals
• Founders
• Anyone facing important decisions

Inference: The target audience is broad and not yet defined by specific personas or use cases. The description does not indicate a clear customer segment or early adopter profile.

Not evidenced.

The author does not describe any pricing model, monetization strategy, or business model. There is no mention of subscriptions, freemium tiers, enterprise licensing, or revenue streams.

The project was built using:

• Frontend: Next.js, React, Tailwind CSS, Framer Motion
• Backend/API: OpenAI Responses API with GPT 5.6
• Development Tools: Codex, GitHub, Vercel
• Deployment: Vercel
• Demo Mode: Included to allow judges to explore the workflow without API access

Inference: The product is a web application built in a modern stack and deployed on Vercel. It includes a demo mode for limited access during development or presentation.

Not evidenced.

There is no mention of:

• Users
• Customers
• Revenue
• Usage metrics
• Product adoption
• Feedback loops
• Iteration history beyond the hackathon

The project is described as a hackathon submission, and the author notes it was built within a short timeframe.

Not evidenced.

There is no mention of competitors, market analysis, or positioning relative to existing tools for decision-making or AI reasoning. The author does not reference any similar products or services in the market.

• No traction or user data: The project is described as a single-person hackathon effort with no evidence of real-world usage.
• Unproven commercial viability: No business model, pricing, or revenue streams are described.
• Limited scope and maturity: The product is presented as a proof-of-concept, not a production-ready solution.
• No competitive differentiation: The author does not explain how Prism differs from existing AI tools or decision-making frameworks.
• Self-reported only: All claims are based on the author’s own description — no independent verification.

1. What specific user problems are you solving, and how do you know they exist?
2. Have you tested this with real users or potential customers?
3. How do you plan to monetize this product?
4. What is your roadmap for moving from a hackathon prototype to a scalable product?
5. Are there any existing tools that perform similar functions? How does Prism differ?
6. What are the technical limitations of relying on GPT 5.6 for decision reasoning?