Beginning My Journey to Become a Full-Stack AI Web Developer & AI Engineer

A longform introduction to my learning-in-public path

I’m starting something long-term, challenging, and ambitious: building the skills to become a full-stack web developer and AI engineer from the ground up. My background isn’t in computer science—I completed 12th-grade PCB—so this is a complete transition into software development. I’m documenting the entire process publicly to create accountability, measure my progress, and eventually build a transparent, verifiable portfolio of work.
This is not a fast-track attempt or a pursuit of shortcuts. It’s a structured, multi-phase journey based on a detailed set of roadmaps that outline exactly what I need to learn and in what order. The goal is to understand both the fundamentals and the practical engineering skills required to build real AI-powered applications.

Why I’m Learning in Public

My motivations are simple and practical:

1. Accountability: Publishing my progress forces me to stay consistent and disciplined over months, not days.
2. Clarity: Writing publicly helps me understand what I’m learning and why.
3. Transparency: I want a portfolio that doesn’t just show final projects but the process behind them: the trade-offs, mistakes, and decisions.
4. Community: By building openly, I can learn from others who have taken similar paths. This isn’t about building a personal brand. It’s about documenting reality—slow improvement over time, grounded in structured practice and honest reflection. The Road Ahead: My Learning Blueprint My roadmap breaks the journey into clear, progressive phases. Each phase builds on the previous one and ends with a small but functional project to ensure the concepts are not just theoretical. Phase 0 — Foundations Before writing production code, I need underlying mental tools: • logic and computational thinking • basic statistics • foundational linear algebra concepts • the core ideas behind how software works This phase sets the base for both programming and future AI reasoning. Phase 1 — Programming Fundamentals (Python) Python is my starting point because it's widely used in backend development, automation, and AI systems. I’ll be learning: • syntax and control flow • data structures • error handling • writing clean, readable code • testing fundamentals • version control with Git The goal is not “knowing Python”—it's being able to use it to solve real problems. Phase 2 — Frontend Development To build end-to-end applications, I need to understand how users interact with software. That means: • HTML structure • CSS layouts and responsive design • modern JavaScript • React and eventually Next.js The emphasis here is on fundamentals first—understanding how the web actually works before frameworks. Phase 3 — Backend Development & Databases With frontend basics established, I’ll learn how real applications operate behind the scenes: • APIs and backend architecture • FastAPI or Express.js • authentication flows • relational and NoSQL databases (PostgreSQL, MongoDB) • Docker and containerization basics This is where engineering habits form: structure, clarity, reliability, and maintainability. Phase 4 — Full-Stack Integration & Deployment I’ll connect frontend, backend, and databases into functional systems. This includes: • API consumption • user flows • CI/CD fundamentals • deploying full-stack apps By the end of this phase, I should be able to ship simple production-ready applications. Phase 5 — AI & LLM Engineering Once the full-stack foundation is solid, I’ll move into modern AI engineering: • prompt design principles • embedding models • vector databases • retrieval-augmented generation (RAG) • evaluating AI system performance • managing latency, cost, and context windows The focus is integration, not training custom models. I’m learning how to build real features with existing tools. Phase 6 — Capstone Projects Using everything above, I’ll design and build 3–5 full-stack AI-powered projects such as: • a personalized RAG chatbot • AI-driven automation tools • workflow assistants • domain-specific knowledge systems Each project will include a write-up explaining engineering choices, trade-offs, and limitations. Phase 7 — Portfolio, Interviews, and Career Preparation Finally, I’ll refine my portfolio, build case studies, practice interviews, and start applying for opportunities that match the skills I’ve proven through the projects. How I Will Document Everything This is a learning-in-public journey with structured reporting: • Weekly summaries What I learned, what I built, what I struggled with, and what I improved. • Public code repositories Every phase will have its own folder, projects, and documentation. • Full write-ups for capstones Architecture decisions, system diagrams, and reasoning behind design choices. • Occasional deep dives Reflections on debugging issues, patterns, and insights gained. I’m focused on clarity and honesty rather than perfect results. My Starting Point (Week 1) I’m beginning with: • setting up my development environment • creating a structured learning log • starting the foundations phase—logic, statistics, and problem-solving basics • practicing Python fundamentals daily The early weeks are about building mental models, not rushing into frameworks. What You Can Expect Next Over time, you’ll see: • consistent weekly updates • deployed mini-projects at each phase • gradually more complex full-stack systems • eventually: polished AI-powered capstones This journey will take months, not weeks, and that’s deliberate. My goal is competence, not shortcuts. Closing Thoughts This longform introduction marks the beginning of a disciplined, transparent, and technically grounded learning journey. I expect setbacks, slow progress at times, and difficult concepts—but I also expect steady improvement through deliberate practice. If you’re on a similar path or have experience in full-stack or AI engineering, I’m always open to learning from others. But above all, this process is about accountability and long-term skill-building. More updates to come. — Arham Ghori