Build, Test, Review, and Ship Real-World AI Code with 10 Hands-On AI Projects & Workflows
By the end of this bootcamp, participants will know how to use OpenAI Codex as a practical coding collaborator across the software development lifecycle.
Participants will learn how to inspect an unfamiliar codebase, plan safe changes, write tests before implementation, build focused feature slices, debug failures, review generated work, refactor safely, and prepare code for team handoff.
This is not a passive introduction to AI coding. Participants will work inside a prepared real-world starter project and complete 10 hands-on Codex workflows that mirror everyday engineering work.
The focus is on using Codex responsibly: guiding it clearly, constraining its scope, verifying its output, and staying in control as the developer.
Overview
Participants will learn:
- Practical use of OpenAI Codex for day-to-day development tasks
- Agentic coding workflows that keep the developer in control
- Lightweight TDD (Test Driven-Development) practices for designing behavior before implementation
- Human-in-the-loop review habits for quality, safety, and maintainability
- Repository exploration, feature implementation, debugging, refactoring, and handoff workflows
- Guided hands-on exercises using a prepared starter project and sample data
- A complete end-to-end Codex workflow through a final capstone exercise
- Practical assessment and certification to validate learning outcomes
Who It’s For
This bootcamp is designed for:
- Builders who are comfortable reading code and want a structured path into agentic development
- Developers who want to use Codex effectively in everyday coding work
- Technical leads introducing Codex or AI-assisted coding practices to a team
- Teams moving from casual AI experimentation to repeatable Codex workflows
- Engineers who want practical guardrails for reviewing and accepting AI-generated changes
This workshop is best suited for people who can read and lightly modify code. Advanced attendees will benefit from the workflow, review, and adoption patterns; newer attendees will benefit from the guided project, checkpoints, and instructor-led walkthroughs.
Before You Start
Participants should have:
- Basic comfort using a code editor and terminal
- Familiarity with Python programming language
- Access to OpenAI Codex
- Basic familiarity with Git workflows
Participants do not need AI, machine learning, or model-training experience.
What You’ll Learn
By the end of this workshop, participants will be able to:
- Use Codex to inspect a codebase and identify safe places to make changes.
- Turn a user story into architecture choices, testable design, and an implementation plan.
- Guide Codex to draft unit tests that specify classes, methods, and expected behavior.
- Use Codex for focused code changes instead of broad, risky edits.
- Review, test, debug, and refine Codex-generated work.
- Use prompts, constraints, checkpoints, and reset points to manage uncertainty.
- Apply practical guardrails for team use, documentation, and handoff.
- Use Codex to support refactoring, review, and maintainability improvements.
- Complete a guided end-to-end Codex capstone workflow.
- Pass the final assessment and earn a certificate of completion.
Lineup
Chuck McCullough
Good to know
Highlights
- 7 hours
- Online
Refund Policy
Location
Online event
Agenda
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Hour 1: Codex Foundations and Workflow
In this opening session, you'll learn what Codex is, where it fits in the modern development workflow, and why developers remain responsible for design, testing, and final decisions. We’ll explore agentic development as a guided loop, ask, inspect, decide, test, implement, verify, and review and discuss how tests and small design choices help steer AI-assisted coding. You'll also examine the risks of non-deterministic AI output and practical strategies for managing them. Through a hands-on exercise, you'll set up your Codex environment, complete your first guided coding task, learn how to evaluate and refine Codex-generated work, and create a personal checklist for responsible AI-assisted development.
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Hour 2: Environment, Repo Orientation, and First Prompts
Participants will begin by confirming the prepared development environment and starter project, then use Codex to inspect the repository before making any changes. Through guided prompt patterns, they will practice context gathering, constraint identification, architecture discovery, and effective clarification techniques. Using Codex, participants will identify key files, understand data flows, locate likely change points, and document potential risk areas, while learning how to avoid vague prompts that lead to broad or unsafe edits. By the end of the session, each participant will produce a concise repository map, identify file responsibilities and risks, and create a reusable repository-orientation prompt for future projects.
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Hour 3: User Story, Architecture Choices, and Test Design
In these hands-on projects, participants will learn how to translate a realistic user story into a scoped technical implementation plan. Using Codex, they will break down requirements, identify assumptions and constraints, map data flow, propose simple classes and methods, make lightweight architecture decisions, and determine which files are likely to change. Participants will then take a test-first approach by designing and refining unit tests that define expected behavior before implementation, documenting edge cases, creating a clear implementation checklist, and using lightweight prototypes where needed to validate workflows and clarify requirements.