coil

What the company appears to be:

coil is an AI-powered hair care companion for people with textured hair. The author states it is designed to analyze hair health and create personalized routines based on user goals, lifestyle, and hair profile. It uses AI to diagnose issues like heat damage or breakage from uploaded photos and generates tailored recommendations.

What changed:

The project was built as a hackathon submission (OpenAI 2026) by one person (Alsade Daley). The author describes it as a prototype with ambitions for future development, including progress tracking, calendar reminders, stylist networks, and expanded hair texture support.

Single most important open question:

Is there evidence of user engagement or adoption beyond the single developer’s personal experience? The description contains no data on users, usage, revenue, or traction — only claims about intent and product design.

The description states that coil is an AI-powered hair care companion for textured hair. It allows users to create a personalized hair profile by inputting information about their hair type, concerns, goals, lifestyle, current products, and history. Users can upload photos of their hair for AI analysis to identify issues such as heat damage, split ends, dryness, breakage, or chemical damage.

Using this data, coil generates personalized recommendations and routines tailored to each user’s unique needs. Unlike existing solutions, the product is described as a long-term companion rather than just a diagnostic tool.

Evidence:

• The author states: “coil is an AI-powered hair care companion designed specifically for people with textured hair.”
• Users can upload photos for AI analysis to detect specific hair issues.
• Recommendations are generated based on user inputs and AI diagnostics.

Inference:

• The product uses GPT-5.6 for reasoning and structured recommendation generation (inferred from tech stack and write-up).
• It is built with Next.js, FastAPI, Supabase, and OpenAI tools (inferred from tech tags).

The author positions coil as a tool that makes expert hair care guidance more accessible and personalized for people with textured hair. The inspiration stems from personal experience growing up in Jamaica, where she lacked access to structured hair care knowledge.

The product is described as evolving beyond diagnosis into a long-term companion that adapts to user needs over time. Future features include progress tracking, calendar reminders, stylist networks, and adaptive recommendations based on feedback.

Evidence:

• “I wanted to build a tool that makes expert guidance more accessible and personalized for people with textured hair.”
• “Unlike existing solutions, coil is designed to become a long-term hair care companion rather than simply diagnosing a problem.”
• “Future features include AI-powered progress tracking using before-and-after photos.”

Inference:

• The positioning implies a shift from one-off diagnostics to ongoing personalization and coaching (inferred).
• The vision includes community-driven product recommendations and stylist discovery (inferred).

The author states that coil is designed for people with textured hair, particularly those seeking personalized guidance. The inspiration comes from her own experience as a young Black girl in Jamaica who struggled to understand proper hair care.

Evidence:

• “coil is an AI-powered hair care companion designed specifically for people with textured hair.”
• “I grew up in Jamaica as a young Black girl...”
• “Thousands of people ask questions like: Why is my hair breaking? Why are my edges thinning?”

Inference:

• The ICP likely includes individuals with textured hair who are looking for structured, personalized advice (inferred).
• Likely demographic: young women or girls in communities where traditional hair care education is lacking (inferred).

Not evidenced.

The description does not contain any information about pricing models, monetization strategies, or business structure. No mention of subscriptions, freemium tiers, or paid features.

The project was built using the following technologies:

• GPT-5.6 for intelligent reasoning and structured recommendation generation
• OpenAI Codex for development assistance (planning, debugging, code generation)
• Next.js for frontend
• FastAPI for backend services
• Supabase for authentication, database management, and Row Level Security
• Tailwind CSS for UI

Codex reportedly accelerated development by reducing time spent on scaffolding, configuration, and debugging.

Evidence:

• “GPT-5.6 for intelligent reasoning and structured recommendation generation”
• “OpenAI Codex throughout development for planning, architecture, debugging, project scaffolding, code generation, and troubleshooting”
• “Built with: codex, fastapi, gpt-5.6, next.js, node.js, openai, python, supabase”

Inference:

• The use of Codex suggests a rapid prototyping approach (inferred).
• Supabase integration implies secure user authentication and data handling (inferred).

Not evidenced.

There is no mention of users, customer acquisition, retention metrics, or product usage. No revenue, ARR, headcount, or adoption data are provided.

Absence of evidence:

• No information on how many people have used the tool.
• No indication of user feedback or engagement beyond the developer’s own experience.
• No mention of any live version or production deployment.

Not evidenced.

The description does not reference existing competitors, market size, or competitive positioning. It does not describe what other tools exist in this space or how coil differentiates from them.

1. Single-person development: The project was built by one person (Alsade Daley) and lacks any evidence of team scaling or operational infrastructure.
2. No traction or user data: There is no indication that the product has been tested with real users or that there is demand for such a service.
3. Unverified claims: All statements are self-reported and unverified — including the effectiveness of AI diagnostics, user engagement, or scalability.
4. Prototype nature: The project is described as a hackathon prototype, not a mature product.
5. Lack of business model clarity: No indication of how the company intends to monetize or sustain itself.

1. What specific user feedback has been gathered so far?
2. How many people have actually used the tool beyond the developer?
3. Are there any plans for user onboarding, retention, or engagement strategies?
4. What is the intended monetization model (e.g., subscription, freemium)?
5. How does the AI diagnosis compare to expert hair care advice in terms of accuracy and reliability?
6. Is there a plan to expand beyond the current scope (e.g., more hair types, languages, regions)?
7. What are the key technical challenges that remain unresolved before launch?