Portfolio
aienabler.tech — AI-Powered Learning Platform
EdTech / AI Education
10
courses on production AI engineering
458
lessons delivered
297
AI-generated quizzes and assessments
Overview
aienabler.tech is an AI-powered e-learning platform built from scratch to fill the gap between generic programming courses and real-world AI engineering. The platform features a unique two-dimensional personalization system matching content to both the learner's background (backend, frontend, data engineering) and skill level (junior, mid, senior). Every course is built around production-ready examples — the same patterns used daily at Insly under real compliance constraints.
Business Context
After 20 years of engineering and years of teaching at conferences and workshops, I identified a clear market gap: experienced developers wanting to adopt AI in production had no high-quality, practical resource. Bootcamps teach toy projects. Academic courses ignore regulatory constraints. aienabler.tech was built to fill that gap — production-grade AI education for engineers who ship code professionally, built by someone who does it daily.
Challenge
Experienced developers wanting to adopt AI in production had no high-quality, practical resource. Generic bootcamps teach toy projects; academic courses ignore compliance and legacy constraints.
- Generic e-learning platforms offer one-size-fits-all content that wastes experienced developers' time on basics they already know
- AI courses teach toy examples disconnected from production realities: compliance, GDPR, legacy integration, and real error handling
- Building a SaaS platform solo requires balancing feature development, content creation, and infrastructure operations simultaneously
Solution
Built the entire platform end-to-end: Symfony 7 backend with hexagonal DDD architecture, React 18 frontend with TypeScript, and an AI layer for content personalization and quiz generation. Launched with 10 courses and 458 lessons focused on practical AI engineering, with integrated Stripe billing and AWS deployment.
- Two-dimensional personalization engine: Path × Skill Level content matrix
- AI-generated quiz questions and knowledge gap analysis per learner
- Dynamic pricing with course bundles and Stripe subscription management
Approach & Methodology
Content-first: outlined all 10 course structures before writing a single line of platform code. Built the MVP as a minimal Symfony app, validated with early learners from conference audiences, then added personalization features incrementally. Every technical decision was evaluated against two criteria: does this let me ship courses faster, and does this give learners better retention outcomes?
Implementation Details
Two-Dimensional Personalization Engine
Designed a Path × Skill Level content matrix allowing learners to experience the same concepts through their own domain lens. A backend engineer and a data engineer get different code examples, project structures, and domain contexts — same learning goal, personalized execution. The matrix drives content selection, quiz difficulty, and recommended next steps.
Full-Stack SaaS Architecture
Symfony 7 backend with DDD aggregates and a clean REST API, React 18 with TypeScript for the frontend, PostgreSQL for persistence. Deployed on AWS with infrastructure as code. Stripe integration handles payments, subscriptions, and trial management. Built to be maintainable solo — every architectural choice was evaluated against 'can one person debug this at 11pm?'
AI Content and Quiz Layer
Integrated Claude API for quiz question generation from lesson content and personalized learning path recommendations. Careful prompt engineering for technical accuracy — the system generates questions grounded in actual lesson material, not generic AI knowledge. Used spaced repetition tracking to surface knowledge gaps per learner.
Key Decisions
- Symfony 7 over Go for the backend — DDD patterns are natural in Symfony, and the ecosystem (Doctrine, Messenger) saved months of development. Go is the right choice for APIs; Symfony is right for complex domain logic.
- Built own platform rather than Teachable or Udemy — needed full control over personalization logic, learner data for future AI features, and pricing flexibility. Platform cost savings fund course development.
- React 18 with server-side rendering from day one — course discovery is search-driven, and SSR SEO foundations were critical for organic growth without paid acquisition budget.
Tech Stack
Related Services
The following services were utilized in this project to deliver successful outcomes.
Lessons Learned
- Content creation is the hardest part of an e-learning business — the technical platform is 20% of the work. Two-dimensional personalization requires 2x the content for the same number of topics.
- Two-dimensional personalization resonates strongly with senior developers who feel condescended to by beginner-focused courses. 'Finally a course that doesn't explain what a for loop is' was the most common early feedback.
- Building in public — sharing progress on LinkedIn and conference talks — generated early adopters more effectively than any paid acquisition. Conference credibility converts better than ads.
Project Information
Timeline
8 months to launch, ongoing
Team
Solo project (design + development + content)
Results
10
courses on production AI engineering
458
lessons delivered
297
AI-generated quizzes and assessments
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