Udacity \USA

STEP 2 - Validation (Weeks 5-12, $15K budget): Launch paid tier at $99/month with 5 learning paths (Prompt Engineering, LLM Fine-Tuning, AI Product Management, AI-Assisted Coding, AI Ethics & Safety). Each path has 30-50 AI-generated lessons, 10 hands-on projects, and a final capstone. Add blockchain credential minting ($299 one-time) on Polygon with embedded proof-of-work (GitHub repo links, project demo videos via Mux, AI-proctored quiz scores). Build employer-facing landing page showcasing graduate portfolios (public GitHub profiles + project demos). Cold outreach to 100 AI startups and tech companies: 'Hire our verified AI-skilled grads, $2K placement fee only if they pass your interview.' Goal: 100 paid subscribers ($9,900 MRR), 50 credential certifications ($14,950 one-time), 5 employer partnerships, 2 successful placements ($4K revenue). Key metric: paid conversion rate (target: 10% of free users), completion rate (target: 40% with AI tutoring), employer interest (target: 5% response rate).

STEP 3 - Growth (Months 4-9, $50K budget): Launch the two-sided marketplace—'SkillForge Challenges' where employers post real-world problems (e.g., 'Build a RAG chatbot for our docs,' 'Fine-tune Llama 3 for customer support') with $500-2,000 bounties. Learners submit solutions, AI grades them (GPT-4 evaluates code quality, documentation, performance), and winners get paid + credential boost. This creates three flywheels: (1) Learners earn while learning (reducing price sensitivity), (2) Employers get pre-vetted talent and solutions (reducing hiring risk), (3) Public leaderboard creates social proof and competition (increasing engagement). Add cohort-based learning: monthly cohorts of 50-100 learners with Slack community, weekly live Q&A with AI experts, and peer code reviews. Invest in content SEO: publish 100 AI-generated blog posts on 'How to become an AI engineer,' 'Prompt engineering examples,' etc., targeting 50K monthly organic visitors. Goal: 500 paid subscribers ($49,500 MRR), 200 credentials ($59,800 one-time), 20 employer partners, 50 challenge completions ($50K in bounties paid to learners, $10K in platform fees). Key metric: marketplace liquidity (challenges posted vs. solved), NPS score (target: 50+), CAC payback (target: <3 months).

STEP 4 - Moat (Months 10-18, $200K budget): Build the proprietary skill assessment engine—'SkillForge Verify'—a standardized, AI-proctored test (like SAT for AI skills) that takes 3 hours and evaluates prompt engineering, code generation, model fine-tuning, and AI product thinking. Charge employers $99/assessment to screen candidates (like HackerRank or Triplebyte). This becomes the moat: employers trust SkillForge credentials because they're backed by a standardized, third-party assessment, not self-reported projects. Launch B2B tier: $10K-50K annual contracts for companies to upskill existing employees (e.g., 'Turn your PMs into AI PMs in 90 days'). Include admin dashboard, team analytics, and custom learning paths. Add AI career coach: GPT-4 agent that analyzes learner's background, suggests optimal learning path, reviews resume, and does mock interviews. Expand to 20 learning paths covering all AI-era skills (AI sales, AI marketing, AI ops, AI legal). Goal: 2,000 paid subscribers ($198K MRR), 1,000 credentials ($299K one-time), 100 employer partners, 10 B2B contracts ($300K ARR), 500 SkillForge Verify assessments ($49,500). Total ARR: $2.67M. Key metric: employer NPS (target: 60+), assessment adoption rate (target: 50% of employers use Verify for screening), B2B expansion revenue (target: 30% of total).