Accelerate software product development with AI-first engineering practices and Codex-powered workflows.

This immersive 3-day training helps product and engineering teams combine product thinking, modern engineering practices, and AI-assisted development to move faster from ideas to production-ready solutions. Participants learn to use Codex for requirements exploration, implementation, testing, refactoring, and rapid product iteration while maintaining quality and engineering discipline.

  • Why get trained: Learn how to collaborate effectively with AI coding agents, translate ideas into engineering workflows, accelerate MVP development, and build reusable AI-assisted development practices.
  • Why it matters: Reduce development time, improve team collaboration, accelerate experimentation, and deliver quality software faster without compromising maintainability.
  • Who should attend: Software Engineers, Technical Product Managers, Technical Leads, Engineering Managers, Solution Architects, Innovation Teams, and Product Development Teams.

Participants gain hands-on experience through real-world simulations, practical workshops, and guided exercises to build and evolve software products using Codex. HRD Corp Claimable.

Overview

Software product development is evolving rapidly as AI coding agents become an integral part of modern engineering workflows. Organizations are increasingly adopting AI-first product engineering, where product thinking, engineering practices, and AI-assisted execution work together to accelerate innovation and delivery.

AI coding agents such as Codex help teams move more efficiently from idea to implementation by supporting activities such as requirements exploration, solution design, feature development, testing, code review, and workflow automation.

This immersive 3-day training helps product and engineering teams learn how to design, build, test, refine, and deliver software products using Codex as an AI-powered engineering partner. The program combines product engineering, AI-assisted development, rapid prototyping, testing practices, and modern software delivery approaches to help teams build software faster while maintaining quality, maintainability, and engineering discipline.

By the end of the training, participants will have hands-on experience applying AI-first product engineering practices to build and evolve real software solutions using Codex.

Skills Covered

  • Understand how AI coding agents change software delivery
  • Apply AI-first engineering responsibly
  • Establish effective human-AI collaboration practices
  • Convert business ideas into buildable software solutions
  • Break product concepts into engineering workflows
  • Translate requirements into implementation plans
  • Accelerate MVP development
  • Use Codex for implementation workflows
  • Structure context for better outcomes
  • Collaborate with AI agents on development tasks
  • Apply AI-assisted testing practices
  • Refactor safely with AI support
  • Support rapid experimentation
  • Deliver production-ready implementations faster
  • Establish reusable engineering workflows
  • Improve team collaboration
  • Standardize AI-assisted development approaches
  • Build sustainable engineering systems

Prerequisites

There are no prerequisites to attend this training.

Target Audience

  • Software Engineers
  • Technical Product Managers
  • Technical Leads
  • Engineering Managers
  • Solution Architects
  • Innovation Teams
  • Product Development Teams

Course Curriculum

Module 1: AI-First Product Engineering Foundations

This module introduces the emerging discipline of AI-first product engineering and explores how AI coding agents are transforming modern software delivery. Participants learn how product thinking, engineering workflows, and AI-assisted implementation combine to accelerate product development. Participants will understand how AI coding agents support product development and how AI-first engineering differs from traditional software delivery approaches.

Module 2: From Prompt to Product

Participants learn how ideas, business requirements, user needs, and product concepts can be transformed into structured engineering workflows using Codex. The focus is on creating effective prompt-driven development approaches that improve implementation quality and delivery speed. Participants will learn how to convert product concepts into actionable engineering workflows and AI-assisted implementation plans.

Module 3: Context Engineering & AI Collaboration

This module focuses on one of the most important factors in successful AI-assisted development: context. Participants learn how to provide effective project context, requirements, constraints, and engineering guidance to improve implementation quality and workflow reliability. Participants will understand how context quality directly impacts AI-assisted engineering outcomes and product delivery effectiveness.

Module 4: Building Features with Codex

Participants use Codex to design, implement, refine, and extend product features while maintaining engineering quality. The module focuses on practical implementation workflows where AI assists throughout the software development lifecycle. Participants will learn how to accelerate feature delivery while maintaining maintainability, quality, and engineering standards.

Module 5: Testing, Quality & Product Reliability

This module explores how AI-assisted engineering workflows support testing, validation, debugging, and software quality improvement. Participants learn how to combine AI-assisted implementation with disciplined testing and review practices. Participants will be able to improve software reliability and quality while accelerating development workflows.

Module 6: Refactoring, Product Evolution & Iteration

Participants learn how software products evolve through iterative refinement, continuous improvement, and maintainable engineering practices. The module explores how Codex supports refactoring, modernization, and long-term product sustainability. Participants will understand how to improve existing systems safely while reducing technical debt and increasing maintainability.

Module 7: AI-Assisted Product Delivery Workflows

This module examines how AI coding agents support product delivery activities, including code reviews, pull requests, implementation validation, workflow automation, and engineering collaboration. Participants learn how to establish repeatable AI-assisted delivery practices. Participants will learn how to integrate AI-assisted engineering into modern product delivery environments.

Module 8: Capstone — Build an MVP with Codex

Participants apply everything learned throughout the workshop to design, build, test, refine, and present a working software product using Codex as an AI engineering partner. The capstone focuses on the complete product engineering lifecycle:

  • Idea
  • Planning
  • Implementation
  • Testing
  • Refinement
  • Delivery

Participants leave with practical experience building a working product using AI-first engineering workflows.

Dates & Locations

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Exam & Certification

Complete the AI-First Product Engineering with OpenAI Codex Training and receive your AI-First Product Engineering with OpenAI Codex Training Certificate of Completion after successfully completing the 3-day program. This validates your skills in applying AI-first engineering practices, AI-assisted development, rapid prototyping, testing, refactoring, and modern software delivery workflows using OpenAI Codex.

Training & Certification Guide

Why train with Trainocate

AI-First Product Engineering is an approach where product thinking, engineering practices, and AI-assisted development work together to accelerate software delivery and innovation.

OpenAI Codex is an AI-powered coding agent that helps developers with implementation, testing, code generation, debugging, and engineering workflows.

Organizations increasingly seek professionals who can combine product thinking with AI-assisted engineering. These skills can help improve productivity, innovation, and career growth opportunities.

Yes. Participants learn how to move from idea to implementation and build working MVPs using AI-first engineering practices.

Yes. The training includes AI-assisted testing, validation, debugging, and quality improvement workflows.

Providing clear project context, requirements, and constraints helps AI agents generate more accurate, reliable, and maintainable outputs.

Participants design, build, test, refine, and present a working software product using OpenAI Codex as an AI engineering partner.

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All courses are HRD Claimable.
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