AI-NATIVE ENGINEERING CERTIFICATION · COHORT 01

The AI-Native
Full-Stack Engineer
Program

Build production MERN applications, work fluently with Claude, Cursor and the modern AI toolchain, and graduate with shipped, tested and defensible software—not just course completion.

Across 24 weeks, you complete 36 project builds, seven deeper portfolio milestones, 110+ DSA problems and a production-style capstone. Placement activity begins after the frontend capstone gate in Week 13.

Weekend live 10–15 hrs / week Placement from W13

No payment on this page Brochure unlocks instantly after the contact form

60-SECOND PROGRAMME FIT CHECK

See whether this path fits your current level.

Share four details. We’ll capture your interest and give you the complete programme plan to review.

Cohort 01

Project builds36Two per sprint

Portfolio gates7Deeper review

DSA checkpoints5Timed assessment

Mock interviews3Panel feedback

✓ build the product

✓ test the failure paths

✓ disclose AI-assisted work

✓ explain and defend decisions

24calendar weeks

36project builds

7portfolio milestones

110+DSA problems

48live sessions

W13placement begins

WHY THIS PROGRAM EXISTS

What AI has changed about full-stack readiness.

Before you look at the syllabus, understand the standard. AI can generate code; engineers are still accountable for what is correct, secure, testable and worth shipping.

AI fluency is now baseline

You work with Claude, Claude Code, Cursor, Copilot and the modern AI application stack from the beginning—not as a last-week add-on.

Reward: faster execution without outsourcing your thinking.

Judgment matters more than output

Every AI-Native Lab requires a documented rejection. You learn to inspect suggestions, find failure modes and defend what you keep.

Reward: a credible answer when an interviewer asks, “Why this approach?”

Production discipline separates candidates

Tests, accessibility, security, observability, backups, rollback paths and honest limitation notes turn a demo into engineering evidence.

Reward: work that can survive scrutiny—not just a screen recording.

WHAT YOU WILL HAVE TO SHOW

By Week 24, your progress should be visible—not assumed.

Not a list of tools you have “covered”. A sequence of artifacts you can open, run, test, explain and defend.

Portfolio proof01

A deployed frontend capstone and case study

React, TypeScript, forms, routing, deliberate state ownership, testing, accessibility and performance—presented as a coherent project story.

Live deployment
Repository and README
Architecture explanation

Backend proof02

A documented, tested API

Typed Node and Express services, clear layers, structured logs, a verified OpenAPI contract and appropriate test coverage.

Full-stack proof03

A secure MERN beta

A complete user journey across React, API, database, authentication, authorization, validation and failure-state UX.

AI proof04

An auditable AI engineering record

Structured-output validation, RAG, tool calling, evaluation, cost and latency thinking, rejected suggestions and a disclosure log.

Interview proof05

A measured DSA progression

110+ problems, five level checkpoints, complexity explanations and three mock interviews under panel conditions.

Final proof06

An industry capstone you defend live

Architecture, trade-offs, tests, operations, limitations and AI use—released, documented and presented before a panel.

THE 24-WEEK JOURNEY

Here is how the evidence compounds across 24 weeks.

Three phases build on one another. Your projects become more integrated, your decisions more consequential and your evidence more valuable.

FRONTEND ENGINEERING & PLACEMENT READINESS

Build a frontend portfolio before backend complexity arrives.

Start with web foundations, responsive UI and Git. Progress through JavaScript, TypeScript, React, forms, routing, state, testing, accessibility and performance.

Your phase rewardA deployed frontend capstone and case study—the gate that opens the placement track.

Representative builds

01 Reusable UI System & Marketing Site
02 Typed JavaScript API Application
03 React Product Browser
04 Tested Accessible Dashboard
05 Deployed Frontend Capstone & Case Study

HOW THE WEEK WORKS

A predictable weekly rhythm that keeps you building.

Weekdays build fluency. Weekends are protected for the decisions that are hard to learn alone: implementation, live debugging, architecture argument, interview practice and review.

“Syntax can be learned alone; judgment cannot.”

MON–FRI~4 hrs

Self-paced foundation

Concept micro-videos and reading notes
Interactive coding and guided labs
Weekly quiz and debugging challenge
DSA problem sets with complexity notes
Readiness check before the live studio

SATURDAY3 hrs live

Implementation Studio

0:00

Readiness & blockersClear the ground before building.

0:20

Live implementationBuild from empty, decision by decision.

1:50

Learner build sprintExtend the work with instructor support.

2:40

Debug clinicDiagnose deliberately introduced failures.

SUNDAY3 hrs live

Applied Engineering Studio

0:00

DSA Live ClinicPattern teaching and timed practice.

0:45

Sprint projectBuild the second integrated artifact.

1:55

AI-Native LabUse the sprint tool on your own codebase.

2:35

Sprint reviewDemo, PR review, evidence and retrospective.

CURRICULUM EXPLORER

Everything you learn connects to the product in front of you.

The curriculum does not teach isolated tools. Each technology arrives when a project needs it and is assessed at a stated depth.

FRONTEND ENGINEERING

Build interfaces that work beyond the happy path.

Move from semantic HTML and responsive design to strict TypeScript, React architecture, validated workflows, deliberate state ownership, accessibility, testing and measured performance.

HTMLModern CSSJavaScriptTypeScriptReactViteReact Hook FormTanStack QueryRedux ToolkitPlaywright

You will be able to showA deployed frontend capstone with tests, accessibility evidence and a written case study.

Want the sprint-by-sprint specification?The brochure maps all 18 sprints and 36 projects.

AI-NATIVE, NOT AI-DEPENDENT

AI accelerates the workflow. Judgment remains yours.

Generated code is treated as untrusted until it is reviewed, tested, understood and disclosed. The program rewards the quality of your judgment, not the volume of generated output.

18 AI-Native Labs—one inside every sprint.

One documented rejection per lab with written reasoning.

An AI Disclosure Log from first sprint to final capstone.

Bounded agents with schemas, permissions, retries, audit logs and human approval.

Model output

- const result: any = await model.generate(prompt);
+ const raw = await model.generate(prompt);
+ const result = OutputSchema.parse(raw);

Would you accept this change?

Choose an action to see the engineering rationale.

React + TypeScriptNode.js + ExpressMongoDBClaude CodeCursorMCPRAGDockerGitHub ActionsPromptfooReact + TypeScriptNode.js + ExpressMongoDBClaude CodeCursorMCPRAGDockerGitHub ActionsPromptfoo

INTERVIEW-READY DSA

Interview readiness is trained, timed and reviewed.

DSA runs in parallel from Week 3 to graduation. It is taught live, practised weekly and assessed five times—without an assistant during checkpoints and mock interviews.

110+problems

5checkpoints

3mock interviews

45live minutes / Sunday

FoundationsWeeks 3–5 · arrays, strings, hash maps

15 problems

Core patternsWeeks 6–9 · two pointers, window, search

20 problems

Recursion & treesWeeks 10–13 · BFS, DFS, heap

20 problems

Graphs & searchWeeks 14–18 · traversal, backtracking, greedy

25 problems

DP & interviewWeeks 19–24 · mixed timed problems and mocks

30 problems

checkpoint-mode

// AI assistance: disabled
function solve(input) {
  // explain the pattern
  // implement under time
  // justify complexity
}

status: "ready to reason aloud"

THE MILESTONE LADDER

Seven portfolio gates. Each one raises the standard.

Every sprint produces a project. These seven milestones receive deeper portfolio review and create the strongest checkpoints in your story.

Milestone 1 · Week 2

Reusable UI System and Marketing Site

Responsive design, accessibility, reusable styling and deployment—your first polished visual portfolio evidence.

Portfolio valueEarly visual proof

PLACEMENT TRACK

Placement support begins after your portfolio clears its first major gate.

The placement track opens in Calendar Week 13, immediately after the frontend capstone gate. It runs alongside backend and full-stack development rather than waiting until graduation.

Clear expectation: the program provides evidence, coaching, applications, mock interviews and employer access. It does not guarantee employment.

W13–14

Lead with frontend proof

Resume and profile alignment, frontend applications, JavaScript, React and DSA interview practice.

W15–17

Add backend credibility

Recruiter conversations, take-home practice, accessibility questions, data and security stories.

W18–20

Expand to full-stack roles

Node, API, MongoDB and security interviews supported by a demonstrable MERN beta.

W21–24

Defend the capstone

Employer events, capstone pitch, system-design fundamentals, final interview rehearsal and follow-up.

FIT CHECK

This programme is demanding by design. Is it a fit?

The programme works best when the commitment, current level and expected outcome are clear before you begin.

You are likely a strong fit if…

You are a graduate or early-career engineer pursuing junior frontend or full-stack opportunities.
You are a career changer with some programming exposure and need structure, live accountability and portfolio evidence.
You can protect Saturday and Sunday live sessions plus weekday self-study.
You already use AI assistants casually and want professional discipline around them.
You intend to sit technical interviews and want DSA assessed—not merely mentioned.

This is probably not the right fit if…

You are looking for guaranteed placement rather than a demanding evidence-building program.
You cannot commit roughly 10–15 hours per week, rising after placement activity begins.
You want to skip fundamentals because an assistant can generate code.
You want a passive video course with no camera-on live work or project defence.
You need deep foundation-model training or robotics hardware specialization.

70/100

6/10minimum capstone score

80%minimum live attendance

5/5DSA checkpoints attempted

7/7milestones submitted

EVIDENCE-BASED CERTIFICATION

Certification is earned through evidence, not attendance.

There is no single final exam that wipes away six months of evidence. Your score is assembled continuously from projects, milestone reviews, the capstone, DSA and studio participation.

25%

Implementation projects

25%

Major milestones

20%

Industry capstone & presentation

15%

DSA checkpoints & mocks

10%

Live studio participation

Self-paced completion

LEARNER VOICES

Short learner stories, kept in motion.

This launch build includes clearly marked placeholders. Replace them with verified names, designations, photographs and outcome-backed quotes before publishing learner claims.

Verified learner storyProgramme learner

Sample

Replace this placeholder with a concise, verified learner quote that explains the work they built and the capability they can now demonstrate.

Verified learner storyWorking professional

Sample

Use this card for an approved outcome-backed story, with enough context to be useful and without making an unverified placement promise.

Verified learner storyCareer-transition learner

Sample

Add an approved learner photograph, designation and short quote that connects the programme experience to visible portfolio evidence.

THE FULL PROGRAM PROSPECTUS

See the complete 24-week programme before you decide.

Download the 40-page brochure with all 18 sprints, 36 projects, tool depth codes, AI usage charter, five-level DSA track, placement journey and certification criteria.

Full curriculum map Project evidence Assessment rules

Complete the short contact form to unlock the PDF.

QUESTIONS, ANSWERED

Decide with the full picture.

A serious career program should make the commitment, outcome and limits clear before you apply.

Who is this program designed for?

It is a strong fit for graduates, early-career engineers and career changers with some programming exposure who want junior frontend or full-stack readiness, live accountability and a portfolio that can survive technical scrutiny.

How much time should I commit each week?

Plan for roughly 10–15 hours per week: about four hours of weekday self-paced learning, six live weekend hours and independent project work. From Week 13, placement activity can raise the commitment to roughly 13–18 hours.

Are the weekend sessions live?

Yes. Saturday is a three-hour Implementation Studio. Sunday is a three-hour Applied Engineering Studio with DSA, a sprint project, an AI-Native Lab and review. Sessions are recorded and published to the platform within 24 hours.

What does “AI-Native” mean here?

AI capability is threaded through the engineering program rather than replacing it. You use coding assistants, model APIs, RAG, MCP, agents and evaluation while following a strict review, testing, verification and disclosure discipline.

Is DSA genuinely included?

Yes. The track runs from Week 3 to graduation and includes 110+ problems, a 45-minute live clinic every Sunday, five checkpoints and three panel mock interviews. Checkpoints and mocks are completed without an assistant.

When does placement support begin?

The placement track opens in Week 13, after the deployed frontend capstone gate. It begins with frontend opportunities and expands toward junior full-stack roles as backend and MERN evidence is added.

Does the program guarantee a job?

No. The program provides technical evidence, portfolio reviews, coaching, application activity, mock interviews and employer access. Employment depends on demonstrated capability, interview performance and the market.

How is the certification awarded?

Assessment is continuous. Certification requires at least 70/100 overall, a minimum capstone score of 6/10, at least 80% live attendance, all five DSA checkpoints attempted and all seven major milestones submitted.

MAKE THE NEXT 24 WEEKS COUNT

Ready to see whether the programme fits your next move?

Review the full prospectus or complete the programme fit check. Both paths give you the information needed to make a deliberate decision.

The AI-NativeFull-Stack EngineerProgram

See whether this path fits your current level.

Your programme plan is ready to review.

What AI has changed about full-stack readiness.

AI fluency is now baseline

Judgment matters more than output

Production discipline separates candidates

By Week 24, your progress should be visible—not assumed.

A deployed frontend capstone and case study

A documented, tested API

A secure MERN beta

An auditable AI engineering record

A measured DSA progression

An industry capstone you defend live

Here is how the evidence compounds across 24 weeks.

Build a frontend portfolio before backend complexity arrives.

Representative builds

Turn a polished interface into a secure, persistent application.

Representative builds

Package, deploy, observe and defend what you built.

Representative builds

A predictable weekly rhythm that keeps you building.

Self-paced foundation

Implementation Studio

Applied Engineering Studio

Everything you learn connects to the product in front of you.

Build interfaces that work beyond the happy path.

Build the systems behind the interface.

Ship through a repeatable path, not a last-minute upload.

Build AI features with boundaries, evaluation and fallback.

Turn knowledge into interview behaviour.

AI accelerates the workflow. Judgment remains yours.

Interview readiness is trained, timed and reviewed.

Seven portfolio gates. Each one raises the standard.

Reusable UI System and Marketing Site

Placement support begins after your portfolio clears its first major gate.

Lead with frontend proof

Add backend credibility

Expand to full-stack roles

Defend the capstone

This programme is demanding by design. Is it a fit?

You are likely a strong fit if…

This is probably not the right fit if…

Certification is earned through evidence, not attendance.

Short learner stories, kept in motion.

See the complete 24-week programme before you decide.

Decide with the full picture.

Ready to see whether the programme fits your next move?

The AI-Native
Full-Stack Engineer
Program