For final-year students & early-career engineers
AI-Tutor
Learn to ship software with AI as a skilled teammate — free Beginner and Intermediate courses, Advanced modules at ₹999.
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Practical modules for capstones, internships, and your first years on the job.
Foundations: Modern SDLC + the AI-Augmented Engineer
Foundations: Modern SDLC + the AI-Augmented Engineer
Built for final-year students and early-career engineers. A grounding module: we define the modern SDLC (Plan → Design → Develop → Test → Release → Operate → Learn), show where AI augmentation slots in, and reset expectations about what an engineer's day looks like when an AI assistant is part of the workflow. By the end, every learner has a one-page diagram of an SDLC for a real product and a written list of…
Amit Ranjan
AI-Assisted Development & Vibe Coding
AI-Assisted Development & Vibe Coding
The signature module of the program. Learners spend most of the session doing, not listening. We tour the major AI coding tools (Cursor, GitHub Copilot, Claude Code, Aider), introduce four prompt patterns, then run a debug lab where each learner fixes a broken FastAPI endpoint using AI as a pair-programmer and documents every prompt. The point is to make AI a habit, not a curiosity.
Amit Ranjan
AI-Augmented Workflows end-to-end
AI-Augmented Workflows end-to-end
The capstone of the AI-augmented track. We take a small feature from request → branch → code → tests → PR → review → deploy → observe, with AI involved at every phase and a single prompt log as the spine. Then we triage a production incident with AI as a triage partner, while protecting secrets and avoiding fabrication risks. The deliverable is an evidence pack that future reviewers (or hiring managers) can… Built for final-year students and early-career engineers. Includes a structured lesson plan and hands-on exercises you can complete with an AI coding assistant.
Amit Ranjan
Visual AI Builders: Idea to MVP
Visual AI Builders: Idea to MVP
This module teaches the “vibe MVP” loop: start with a clear problem, get to a working demo fast using a visual AI builder, and keep quality by adding constraints, checks, and a small evidence log. The aim is not perfect architecture — it is a usable prototype with a credible story for how it works and what it doesn’t do yet.
Amit Ranjan
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From foundations to platform, AI practice, and career readiness.
Built for your next role
Self-paced modules
Learn AI-assisted engineering at your pace — from foundations through production habits.
Free to start
Beginner and Intermediate courses are free. Advanced deep-dives are ₹999.
Career-ready certificates
Finish modules with verifiable certificates you can show on your resume or LinkedIn.
How it works
A public catalog of AI-assisted engineering modules
- Problem
- Early-career engineers need a structured way to practise shipping with AI as a teammate — not a pile of unrelated tutorials.
- Stack (this demo)
- Next.js (App Router) · PostgreSQL via Prisma · NextAuth · Markdown lesson bodies stored in git and seeded on boot. No vector database, no LangGraph, no Temporal.
- Engineering choice
- Curriculum lives in the repo as UTF-8 Markdown/JSON and is upserted into Postgres at process start. The catalog is public; login is only for enrollment and progress. That keeps the demo inspectable without an account, and keeps lesson text in version control rather than only in the database.