AI in
Software Engineering
An advanced practical program for senior developers, lead engineers, QA automation engineers, technical product leads, and engineering teams who want to move beyond basic AI-assisted coding and build structured, scalable, and production-aware engineering workflows with AI.
What is this course
A STRATEGIC UPGRADE
YOU ALREADY KNOW SOFTWARE ENGINEERING.
NOW LEARN HOW AI CHANGES IT.
In 8 sessions, you’ll learn how AI is changing software delivery, how to prepare repositories for AI, write better specifications, work with coding agents, review AI-generated code, improve testing workflows, and build scalable AI-native engineering systems.
- 01
Understand AI deeply
Learn how AI is changing software delivery, developer roles, team workflows, and engineering expectations - not as a shortcut, but as a new engineering capability.
- 02
Apply it strategically
Use AI to support planning, implementation, testing, review, documentation, debugging, and decision-making while keeping human technical ownership.
- 03
Build a system
Create AI-assisted workflows with clear specifications, context architecture, quality checks, security rules, governance, and human approval gates.
Who is this for
BUILT FOR MODERN ENGINEERING TEAMS
WHO WANT TO STAY RELEVANT
Senior Developers
Who want to move beyond basic AI-assisted coding and use AI to improve real production workflows without losing code quality, maintainability, or architectural control.
Lead Engineers
Who define engineering standards, review processes, technical direction, and need to introduce AI into development workflows in a structured way.
QA Automation Engineers
Who want to apply AI to test strategy, unit/integration/E2E coverage, edge-case discovery, flaky test analysis, stack trace interpretation, and QA automation.
Technical Product Leads
Who need to turn vague tickets, product requirements, and business needs into AI-readable technical specifications with clear constraints and acceptance criteria.
Engineering Teams
Who want to build a shared AI-assisted operating model instead of using AI randomly across individuals and tools.
Engineering Managers
Who want to introduce AI into teams responsibly, with governance, security rules, quality metrics, cost control, and long-term adoption strategy.
Curriculum
EIGHT SKILLS.
ONE MONTH.
- 01
The New Engineering Reality
- 02
Engineering Memory
- 03
Specification-Driven Engineering
- 04
The AI Engineering Stack
- 05
AI Review Systems
- 06
Engineering Reliability
- 07
Agentic Engineering
- 08
The AI Engineering Operating Model
Final Project
YOU DON’T GRADUATE WITH A TOOL LIST.
YOU GRADUATE WITH AN AI ENGINEERING OPERATING MODEL.
In the final session, you’ll present a practical AI-assisted engineering workflow designed for a real software development team or engineering use case.
Join the Bootcamp- 01
AI-Ready Repository Map
A structured repository setup showing documentation, architecture notes, coding standards, test rules, API contracts, decision records, and AI instruction files.
- 02
Context System
A reusable specification framework with acceptance criteria, constraints, non-goals, implementation boundaries, risk areas, validation rules, and architectural guardrails.
- 03
AI Engineering Tool Stack
A practical tool stack with coding assistants, repo-aware agents, IDE tools, cloud agents, review workflows, testing support, and documentation workflows.
- 04
Reliability Workflow
A structured workflow for pull request review, risk analysis, missing test detection, regression checks, QA automation, debugging, log reasoning, and incident analysis.
- 05
Team AI Governance Policy
A practical one-page AI use policy for engineering teams, including acceptable use, prohibited use, security rules, human approval gates, evaluation standards, cost control, and quality metrics.
Start your journey at ACA X
Master AI skills.
Build your future.
Lead the change.
Course Fee: 100,000 AMD
Get up to 100,000 AMD back if you submit your annual tax declaration and have income tax.
Secure your spot now
Add your details and proceed to payment.
About ACA
ACA X IS BACKED
BY 10 YEARS OF
TECH EDUCATION
ACAx is the professional AI direction of Armenian Code Academy - one of Armenia's most established tech education institutions, founded in 2015.
For a decade, ACA has trained engineers, designers, product managers, and data professionals who now work at global companies, local unicorns, and fast-growing startups. ACAx is the next evolution -professional AI skills for everyone, not just engineers.
- 10+YEARS IN TECH EDUCATION
- 17K+TOTAL GRADUATES
- 100+PARTNER COMPANIES
- 300+TUTORS