AI-Tutor
Module 17DevelopmentModule 17 · AI Practice track

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…

Intermediate2 lessons1h 2m

Taught by Admin

Module 17

AI-Augmented Workflows end-to-end

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  • · Lifetime access to materials
  • · Certificate when you finish
  • · Lesson plan + hands-on exercises

Course content

1 sections · 2 lessons · 1h 2m

1.Module materials

2 lessons
  • Lesson plan30mPreview
  • Exercises32m

Instructor

A

Admin

Industry practitioners teaching AI-augmented software engineering.

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Module 01

Foundations: Modern SDLC + the AI-Augmented Engineer

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Foundations: Modern SDLC + the AI-Augmented Engineer

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 where AI would or would not help.

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Module 02

AI-Assisted Development & Vibe Coding

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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.

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Module 03

Prompt Engineering for Developers

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Prompt Engineering for Developers

Module 02 introduced four patterns. This module goes one layer deeper: few-shot, chaining, output evaluation, and the discipline of a prompt library. The lab is hands-on: each learner builds a small reusable library for one task they actually do.

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Module 04

Software Design: SOLID, clean architecture, DDD basics

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Software Design: SOLID, clean architecture, DDD basics

Most early-career engineers can recite SOLID but can't spot violations in their own code. This module teaches recognition — then practice — in two languages. We finish with a refactor lab where AI is the pair and the rule is "tests stay green".

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