Building modern fullstack applications powered by AI, one project at a time.
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Fullstack AI Engineer is a structured 90-day learning repository designed to build real, practical skills in modern fullstack development and AI engineering — documented publicly as a proof-of-work portfolio.
The journey starts from fundamental computer & web concepts, then progresses through frontend development → backend engineering → databases → AI engineering → AI agents → DevOps → cloud deployment, and ends with real, production-oriented projects.
💡 The focus here is not just learning technologies — it's learning how to build, integrate, deploy, and maintain real applications, the way it's actually done in the industry.
By the end of this journey, the target is to be able to:
| Category | Skills |
|---|---|
| 🌐 Fullstack Development | Build modern web applications with React & Next.js |
| ⚙️ Backend Engineering | Build REST APIs with FastAPI, design relational databases |
| 🤖 AI Engineering | Integrate LLM APIs, build AI-powered applications |
| 🔎 RAG & Vector Search | Implement Retrieval-Augmented Generation systems |
| 🕹️ AI Agents | Build autonomous agents that use external tools |
| 🔗 Automation | Automate real-world workflows with AI |
| 📦 DevOps | Containerize apps with Docker, deploy to the cloud |
| 💼 Career-Ready | Build a professional GitHub portfolio for remote/global roles |
flowchart TD
A[Fundamental] --> B[Git & GitHub]
B --> C[Linux]
C --> D[HTML]
D --> E[CSS]
E --> E2[Tailwind CSS]
E2 --> F[JavaScript]
F --> G[TypeScript]
G --> H[Python]
H --> I[PostgreSQL]
I --> I2[ORM: SQLAlchemy / Prisma]
I2 --> J[React]
J --> K[Next.js]
K --> K2[shadcn/ui]
K2 --> L[FastAPI]
L --> L2[Swagger / OpenAPI]
L2 --> M[Authentication]
M --> N[Docker]
N --> N2[Docker Compose]
N2 --> O2[Prompt Engineering]
O2 --> O[LLM API]
O --> O3[Streaming Response]
O3 --> P[RAG]
P --> Q[Vector Database]
Q --> R[LangChain]
R --> R2[LLM Observability]
R2 --> S[LangGraph]
S --> U[AI Agent]
U --> T[MCP]
T --> T2[Testing: Pytest / Vitest]
T2 --> T3[CI/CD: GitHub Actions]
T3 --> V[Automation]
V --> V2[Background Jobs]
V2 --> W[Deployment]
W --> W2[Payment Integration]
W2 --> X[AI SaaS 🚀]
📋 Click to view the full phase breakdown
| Phase | Topics | Focus |
|---|---|---|
| 01 · Foundations | Fundamental, Git & GitHub, Linux | Core computing & version control literacy |
| 02 · Frontend | HTML, CSS, Tailwind CSS, JavaScript, TypeScript | Building interactive, type-safe, professionally styled UIs |
| 03 · Backend & Data | Python, PostgreSQL, ORM (SQLAlchemy/Prisma) | Server-side logic, database modeling without raw SQL overload |
| 04 · Modern Fullstack | React, Next.js, shadcn/ui, FastAPI, Swagger/OpenAPI, Authentication, Docker, Docker Compose | Production-grade fullstack apps, documented APIs, multi-service containerization |
| 05 · AI Engineering | Prompt Engineering, LLM API, Streaming Response, RAG, Vector Database, LangChain, LLM Observability | Building & monitoring real AI-powered applications |
| 06 · AI Agents | LangGraph, AI Agent, MCP (advanced) | Autonomous, tool-using AI systems |
| 07 · Quality & Delivery | Testing (Pytest/Vitest), CI/CD (GitHub Actions) | Reliable, professionally-verified code |
| 08 · Ship It | Automation, Background Jobs, Deployment, Payment Integration, AI SaaS | Real, deployed, revenue-ready products |
🆕 Bold items are additions to the original roadmap — added because they reflect what's actually expected in real-world fullstack/AI engineering jobs and production AI SaaS products (styling standards, API documentation, testing, monitoring, and monetization — not just "getting AI to respond").
| Frontend | Backend | Database | AI / LLM | DevOps & Delivery |
|---|---|---|---|---|
| HTML5 | Python | PostgreSQL | Prompt Engineering | Docker & Compose |
| CSS3 | FastAPI + Swagger | ORM (SQLAlchemy/Prisma) | LLM API + Streaming | Git & GitHub |
| Tailwind CSS | Authentication (JWT/OAuth) | Vector DB | LangChain / LangGraph | Linux |
| JavaScript | RAG | CI/CD (GitHub Actions) | ||
| TypeScript | MCP | Testing (Pytest/Vitest) | ||
| React | AI Agents | Background Jobs | ||
| Next.js | LLM Observability | Cloud Deployment | ||
| shadcn/ui | Payment (Stripe) |
Each project below is built to be portfolio-ready — deployed, documented, and demo-able.
| # | Project | Stack | Status |
|---|---|---|---|
| 01 | Coming soon | HTML / CSS / JS | ⬜ Not Started |
| 02 | Coming soon | React / Next.js | ⬜ Not Started |
| 03 | Coming soon | FastAPI / PostgreSQL | ⬜ Not Started |
| 04 | Coming soon | LLM / RAG | ⬜ Not Started |
| 05 | Coming soon | AI Agent / LangGraph | ⬜ Not Started |
| 06 | Coming soon | Docker / Cloud Deployment | ⬜ Not Started |
| 07 | Coming soon | AI SaaS (Capstone) | ⬜ Not Started |
This table will be updated as each project is completed — see the /projects folder for details.
Day 0 / 90
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| Week | Focus | Status |
|---|---|---|
| 1–2 | Fundamentals, Git & GitHub, Linux | ⬜ |
| 3–4 | HTML, CSS, Tailwind CSS | ⬜ |
| 5–6 | JavaScript, TypeScript | ⬜ |
| 7–8 | Python, PostgreSQL, ORM | ⬜ |
| 9–10 | React, Next.js, shadcn/ui | ⬜ |
| 11–12 | FastAPI, Swagger, Authentication | ⬜ |
| 13 | Docker & Docker Compose | ⬜ |
| 14–15 | Prompt Engineering, LLM API, Streaming | ⬜ |
| 16–17 | RAG, Vector Database, LangChain | ⬜ |
| 18 | LLM Observability | ⬜ |
| 19–20 | LangGraph, AI Agent, MCP | ⬜ |
| 21 | Testing (Pytest/Vitest) | ⬜ |
| 22 | CI/CD (GitHub Actions) | ⬜ |
| 23 | Automation, Background Jobs | ⬜ |
| 24 | Deployment, Payment Integration | ⬜ |
| 25–26 | AI SaaS Capstone Project | ⬜ |
⏱️ Note: Original scope was ~90 days (≈13 weeks). With the added production-grade skills above, the realistic timeline is closer to ~26 weeks (6 months) at a steady, sustainable pace — or faster if you dedicate full-time hours. Better to build it right than rush and skip fundamentals.
fullstack-ai-engineer/
├── 01-fundamental/
├── 02-git-github/
├── 03-linux/
├── 04-html/
├── 05-css/
├── 06-tailwind-css/
├── 07-javascript/
├── 08-typescript/
├── 09-python/
├── 10-postgresql/
├── 11-orm-sqlalchemy-prisma/
├── 12-react/
├── 13-nextjs/
├── 14-shadcn-ui/
├── 15-fastapi/
├── 16-swagger-openapi/
├── 17-authentication/
├── 18-docker/
├── 19-docker-compose/
├── 20-prompt-engineering/
├── 21-llm/
├── 22-streaming-response/
├── 23-rag/
├── 24-vector-database/
├── 25-langchain/
├── 26-llm-observability/
├── 27-langgraph/
├── 28-ai-agent/
├── 29-mcp/
├── 30-testing/
├── 31-ci-cd/
├── 32-automation/
├── 33-background-jobs/
├── 34-deployment/
├── 35-payment-integration/
├── 36-ai-saas/
├── projects/
└── README.md
Written by someone learning in public — from a Software Engineering vocational background, with hands-on backend (Java) experience — with one clear target: becoming a remote-ready, internationally-employable Fullstack AI Engineer, and building AI-powered products along the way.
This repo is both a learning log and a portfolio, built to demonstrate real, shippable skills to future employers and clients.
Muhamad Badru Kamal (Dude) Software Engineer → Fullstack AI Engineer
⭐ If you find this journey interesting, consider starring this repo to follow the progress!