<p><b>Startup description</b></p><p>My product is an agent that teaches while you build. Beginners and CS undergrads can ship projects fast, but they often can’t debug or explain what they made. My product fixes that with Learn Mode (personalized language learning) and Build Mode (real-time teaching + debugging while code is being written). We started in Jan 2026 and launched on 21 Mar 2026.</p><p><b>Key highlights:</b></p><ul> <li>Beta downloads: 500+</li> <li>DAUs: 70+</li> <li>Revenue: $160</li> <li>Usage: 1100+ hours spent inside the IDE in 3 days</li> <li>Paid acquisition: 0 (organic)</li> <li>-Product Hunt: #1 Product of the Week twice, #6 on launch day</li> </ul> <p><b>Team</b></p><ul> <li>CEO: product + engineering, IDE build, AI workflows, shipping, roadmap.</li> <li>COO: ops, content/distribution, user interviews, onboarding, partnerships.</li> </ul> <p><b>Tech Stack</b></p><ul> <li>Core: TypeScript</li> <li>IDE: Theia-based (Monaco), desktop/local-first</li> <li>Backend: Node/TypeScript, auth + database/progress tracking</li> <li>AI: Claude Opus 4.5 API (model-agnostic design)</li> <li>Dev workflow: Cursor + Claude Code</li> <li>Infra: lightweight + scalable (rate limits, queues for heavy analysis)</li> </ul> <p><b>Marketing and growth</b></p><ul> <li>Product Hunt launch: #1 Product of the Week twice, #6 launch day.</li> <li>Community growth: Reddit + developer communities, organic traction</li> <li>Content engine: daily shorts on IG/YouTube (demos + updates)</li> <li>Direct user discovery: constant interviews with students/devs + fast iteration</li> <li>Result: 300+ downloads, 50+ DAUs, 1000+ hours usage in 3 days, 100+ waitlist</li> <li>NVIDIA Inception member</li> </ul> <p><b>Revenue and profit</b></p><ul> <li>Model: freemium to Pro / Pro+ upgrades (subscriptions)</li> <li>Revenue: $160</li> <li>MRR/ARR: too early to annualize reliably</li> <li>CAC: effectively ~$0 right now (organic)</li> <li>LTV / churn / retention: 33%</li> <li>Margins: high potential, biggest variable is model + compute costs ~ $0 spent on compute</li> </ul> <p><b>Return on investment</b></p><ul> <li>For individuals: faster project shipping + less time stuck/debugging + better interview/viva readiness</li> <li>For institutions (future Teams plan): reduces instructor support load, improves completion rates, and gives measurable progress per cohort (seat-based ROI)</li> </ul> <p><b>Startup assets<b></b></b></p><ul> <li>Product: IDE + extension/teaching layer</li> <li>Brand + domain</li> <li>Socials: Instagram + YouTube</li> <li>Product Hunt listing + reviews/credibility</li> <li>Total users: 530+ emails</li> <li>Codebase + launch assets (demo videos, pitch deck, onboarding copy)</li> </ul> <p><b>Risks</b></p><ul> <li>Retention risk: must prove D7/D30 retention as cohorts scale</li> <li>Competition: Copilot/Cursor/Replit/Codecademy can add “teaching” features</li> <li>Infra costs: AI usage can spike; needs strong limits + caching + unit economics</li> <li>Education sales cycle: university contracts can be slow (clubs/professors faster).</li> </ul> <p><b>Summary</b></p><p>Our startup is already a live product with real usage, early revenue, and strong organic traction (0 paid). It’s positioned as the missing “understanding layer” in the AI coding era, with a clear B2C wedge and a B2B expansion path(institutions/bootcamps). The core asset is a working devtool + distribution momentum, not a concept.</p><p>✅ $160 TTM revenue</p><p>✅ 5 customers</p><p>✅ Business model: SaaS</p><p>✅ Built with TypeScript, React Native</p>