Un Segundo Intento

What the company appears to be: Un Segundo Intento is a self-reported platform for students and exam candidates that tracks study habits, energy levels, and progress. The project description states it includes features like focused study blocks, streak tracking, personalized profiles, rankings, groups, and shared challenges. It also describes an AI-powered study coach built with GPT-5.6, which is claimed to provide personalized guidance based on user data.

What changed: During the OpenAI Build Week hackathon, the author added an AI study coach powered by GPT-5.6 to the existing platform. The new functionality uses structured context from user profiles and study sessions to generate actionable recommendations.

The single most important open question: Is there evidence of real user adoption or engagement with the platform beyond the author's own development work? The description states no revenue, customers, or traction data are available.

• The description states Un Segundo Intento is a platform for students and exam candidates that makes studying easier to organize, understand, and improve.
• It includes features such as:
  • Focused study blocks
  • Energy and concentration tracking
  • Streaks and progress indicators
  • Personalized study profiles
  • Rankings, groups, and shared challenges
  • Accountability and validation systems
• For OpenAI Build Week, an AI study coach was added using GPT-5.6 that provides personalized guidance based on user data.
• The platform is built with Next.js and Supabase, and uses technologies including codex, css3, ffmpeg, html5, javascript, node.js, openai-api, postgresql, progressive-web-app, puppeteer, resend, service-worker, stripe, stripe-billing, stripe-checkout, stripe-webhooks, stylelint, supabase-auth, supabase-storage, vercel, vercel-cron-jobs, vercel-functions, web-app-manifest.

• The description states the platform was inspired by the idea that students do not need another app that expects perfect discipline every day.
• It aims to help students build routines they can actually maintain rather than just tracking study hours.
• The author claims it combines study tracking, accountability, and personalized guidance in one place.
• The AI coach is positioned as helping students understand when they focus best, whether their goals are realistic, what affects their consistency, and what they can change in their next study session.
• The platform is described as not feeling like a generic chatbot but rather being integrated into the student's actual routine.

• The description states Un Segundo Intento targets students and exam candidates.
• It is positioned for people who struggle with focus, motivation, or consistency in their study habits.
• The platform is described as helping those who want to build sustainable study routines rather than just tracking time spent studying.

• Not evidenced. The description does not state any pricing model, monetization strategy, or business model details.

• Built with Next.js and Supabase (authentication, PostgreSQL database, user activity data)
• Uses technologies including codex, css3, ffmpeg, gpt-5.6, html5, javascript, node.js, openai-api, postgresql, progressive-web-app, puppeteer, resend, service-worker, stripe, stripe-billing, stripe-checkout, stripe-webhooks, stylelint, supabase-auth, supabase-storage, vercel, vercel-cron-jobs, vercel-functions, web-app-manifest
• The AI coach uses a controlled context pipeline:
  • Selects only study data needed for recommendations
  • Turns it into structured context without unnecessary personal information
  • Sends to GPT-5.6 with clear instructions and limits
  • Validates the structured response
  • Shows student a short explanation and practical next step
• The author used Codex throughout the process for understanding codebase, planning architecture, implementing data and interface layers, testing situations, and documenting new functionality
• Development work during Build Week is separated through dated commits, clear documentation, and identifiable Codex sessions

• Not evidenced. The description states there are no archived snapshots or independent verification of the project.
• No revenue, customer, or traction data is available beyond what the author states.
• The platform existed before Build Week, but no evidence of user adoption or engagement is provided.

• Not evidenced. The description does not provide information about competitors or market positioning beyond self-reported claims.

• The platform exists only as a self-reported project with no evidence of traction, revenue, or customers
• The author states that the AI coach needs to balance accountability and sustainability, suggesting potential risks in design approach
• No evidence of user testing or feedback from real students beyond the author's own development work
• The platform is described as being built by a single person (team size: 1)
• The AI implementation relies on GPT-5.6 which may be an unverified or hypothetical technology

1. What specific user feedback have you received about the platform's functionality and value proposition?
2. How do you plan to validate that the AI recommendations are actually helpful to students rather than just appearing useful?
3. What is your strategy for user acquisition and retention in a competitive education technology market?
4. How will you ensure the AI coach doesn't become overly prescriptive or cause user burnout?
5. What metrics do you use to measure success beyond personal development experience?
6. How do you plan to scale beyond single-person development as the platform grows?