The AI Engineer Arc / Job-Ready Track

From AI-Assisted → AI-Native

For final year and pre-final year engineering students preparing for placements and interviews. 11 modules across three levels, built to make a student job-ready — with a real portfolio, not just a certificate. Every module is tool-agnostic: learn the skill, then apply it in whatever AI stack you have. Tap any module to see what it teaches.

"The future of AI is not about replacing humans, it's about augmenting human capabilities."— Sundar Pichai, CEO of Google

AI-Assisted AI-Connected AI-Native
00 Start here · Find your level

Before the course starts, every student takes a short, anonymous questionnaire. In about 5 minutes, 8 questions place you on the arc — AI-Assisted, AI-Connected, or AI-Native — so you begin exactly where you are and get the modules that move you forward, not the ones you already know.

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+ What you'll walk away with

The whole track builds one thing employers actually look at: a portfolio that proves you can ship with AI.

1

A working code habit

Prompt craft, debugging, and reading unfamiliar code fast — the daily skills of an AI-assisted engineer.

2

A connected workflow

Your first MCP integrations, plus AI that debugs, tests, and reviews with real project context.

3

A production-ready AI agent

One agent that does a real-world job — built, evaluated, observable, and deployed — the centerpiece of your portfolio.

4

Under the hood

You built your agent and a minimal harness yourself, so you can explain exactly how it works in an interview.

5

A feel for the frontier

Optional deep dives into voice agents and the Hermes agent — so the next tier isn’t a mystery.

6

The right vocabulary

You can talk about MCP, agents, and context like someone who has actually used them — because you have.

↘ The arc, end to end

Each AI-Assisted skill grows into a Connected workflow, then a Native build. The arc is the path from "I use AI" to "I ship with AI."

AI-AssistedAI-ConnectedAI-Native
B1 · Prompt craftsmanship→ I1 · MCP fundamentals→ E1 · Build a production-ready agent
B2 · Codebase Q&A→ I2 · Context-aware debugging & tests→ E2 · Harness engineering
B3 · Debugging & stack-trace triage→ I3 · AI code review→ E3 · Voice agent (optional)
B4 · Boilerplate & scaffolding → E4 · Hermes agent (optional)
✦ Who runs it

The single question a placement cell should ask of any AI workshop, answered up front.

SK Surya Kannapiran
Surya Kannapiran
Builds and deploys AI agents into production across industries
Founder and AI trainer, AI Arc · theaiarc.co
  • Ships AI agents into production for companies across several industries.
  • Works on the AI context layer that lets AI operate reliably on a large production codebase.
  • Leads engineering for a global tax and e-invoicing platform end to end.

Most AI training is run by professional trainers. This is run by an engineer who builds the thing he is teaching, every day. The field turns over monthly, so what students learn is what works right now, on production code.