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OpenAI Codex for Everyone

Published by O'Reilly Media, Inc.

Intermediate content levelIntermediate

Delegate knowledge work, build reusable workflows, and automate recurring tasks

What you’ll learn and how you can apply it

  • Understand what an agentic workflow is and how Codex differs from a chatbot so you delegate finished work instead of collecting suggestions
  • Delegate tasks with a four-part prompt structure and Plan mode so Codex asks the right questions before it touches anything
  • Choose between models and reasoning effort levels deliberately, matching the depth of thinking to the difficulty and stakes of each task
  • Write a sharp guidance file that teaches Codex your conventions once so every future session starts smarter
  • Connect Codex to the tools your work already uses through connectors and review its output with confidence using the built-in review workflow
  • Package a recurring task as a reusable skill and schedule it as an automation so the work runs while you do something else

Course description

We used to live in a world of chatbots. You typed, ChatGPT answered, and every result still depended on you doing the actual work. Codex changes the deal. It is an agentic workflow tool, an AI that plans a task, uses real tools, works in a loop until the job is done, and hands you a finished deliverable instead of a suggestion. If your company runs on the OpenAI ecosystem and you are being asked to use Codex on the job, this course will get you genuinely good at it, without writing a line of code.

We start with a finished, working automation and spend the session learning to build its core ourselves, entirely inside the ChatGPT desktop app. You’ll learn to delegate work the way power users do, with clear goals, the right context, and a defined finish line. You’ll teach Codex how your team works with guidance files, connect it to the tools your work already lives in, and choose the right model and reasoning effort for each task, the control panel that makes Codex unique. Then you’ll package your best workflow as a skill anyone can run and schedule it to run on its own. You will leave with a working automation built from a real task you do everyday.

This live event is for you because...

  • You work at an organization that runs on the OpenAI ecosystem and you’re being asked to use Codex on the job.
  • You use ChatGPT daily but every result still depends on you doing the work, and you want to hand off entire tasks instead.
  • You have repetitive weekly work, reports, summaries, formatting, and triage that you know an AI should be doing by now.
  • You’re a nontechnical professional who wants real capability with an agentic tool without becoming a developer.
  • You lead a team and want to standardize how everyone works with AI, so best practices do not live in one person’s head.

Prerequisites

  • The ChatGPT desktop app installed and signed in before class, with Codex access confirmed (ChatGPT Plus minimum recommended, or a work-provided Business or Enterprise account)
  • The sample project folder downloaded (link to come)

Recommended preparation:

  • Bring one real recurring task from your job that you wish would run itself

Recommended follow-up:

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

The Finished Workflow (8 minutes)

Cold open and live demo Open cold on a finished automation, a Monday morning brief that read a folder of project files, summarized what changed, and drafted a status update on its own The contract for the day, you will see exactly how this works and build its core yourself What task does your team repeat every week that nobody wants to do?

Part 1: From Chatbots to Agents (38 minutes)

What agentic workflows are, and the harness tour

  • The arc we all lived, ChatGPT as pure chat, then images, then tools and search, and now an AI that does the work itself, in loops, until the task is done
  • Chat gives you answers, agents give you finished work, the difference is the loop and the harness
  • One agent, three surfaces, the Codex App where we live today, the IDE, and the CLI, same brain and same settings everywhere
  • The tools at its disposal, reading and writing files, running commands, searching, and browsing your project
  • The agent loop, prompt, think, use tools, repeat until done, and context as the agent’s working memory

Models and effort—your control panel

  • The agent’s brain is swappable, Sol for deep reasoning, Terra as the balanced default, Luna for fast and cheap work
  • Reasoning effort from low to max, how hard it thinks before acting, and what that costs
  • A decision rule for normal humans, the balanced default for daily work, deep reasoning for ambiguous or high-stakes tasks, fast and cheap for quick mechanical work

Hands-on—your first delegation

  • Everyone opens the sample project folder in the Codex App
  • The four-part prompt, goal, context, constraints, and done when
  • Voice dictation as the unlock, talk to it like a colleague instead of composing essays
  • First task, summarize what is in this folder and flag what is out of date
  • The safety net in one breath, by default Codex only touches this workspace and asks before anything bigger

Plan mode—make it interview you

  • Without Plan mode Codex has a bias for action, with Plan mode it touches nothing until you approve
  • Watch Codex ask clarifying questions and turn a fuzzy request into a concrete plan
  • The plan is an artifact, iterate on it, save it, hand it to a teammate

Part 2: Teach It How You Work (32 minutes)

Guidance files—what makes a good one

  • The repeated-instructions problem, if you keep typing the same guidance, stop
  • A guidance file is a playbook the agent reads automatically at the start of every session
  • The anatomy of a good one, what the project is, how things run, conventions, do-not rules, and what done means
  • The retrospective loop, tell Codex to update its own guidance file so a mistake never happens again

Connectors—plug in to the tools you already use

  • Your context lives in your docs, tickets, and drives, not in local files, and connectors let Codex pull live data from those systems
  • Demo, connect one real service and watch Codex pull live information into a deliverable
  • The restraint rule, start with one or two connectors that remove a manual loop you already do often

Hands-on—review like a pro

  • Codex does the work, you do the judgment, reading the change view and sending feedback on specific rows
  • The built-in review workflow as your quality gate, even on documents
  • Run a real change through review on your own sample project
  • Q&A

Part 3: Multiply Yourself (28 minutes)

Skills—package what works

  • The handoff problem, good workflows die on a single laptop
  • A Skill in plain terms, a repeatable task packaged with instructions and templates so anyone, or any agent, can run it by name
  • Demo, turn the morning brief workflow from the cold open into a named Skill

Hands-on—build your own skill

  • Build one skill from your own recurring task, the one you named in the opening poll
  • Design rules, a sharp description with trigger phrases, clear inputs and outputs, one job per skill
  • Where skills live, personal versus shared with your team

Automations—work while you sleep

  • Scheduled tasks, pick the project, the prompt, and the cadence, results land in your inbox
  • Skills define the method, schedules define the rhythm, only automate what already works reliably by hand
  • The self-improving Skill, an automation that reviews its own recent runs and sharpens its own instructions

Audience Choice (8 minutes)

  • Audience choice—the class votes on a workflow to run live or an earlier topic to go deeper on
  • Overflow room for questions and hands-on catch-up

Your 30-day plan and resources (6 minutes)

  • Week 1: daily delegations with the four-part prompt, and try the same task at two effort levels to feel the difference
  • Week 2: write your guidance file and connect one tool
  • Week 3: package your best workflow as a Skill
  • Week 4: schedule it and share it with a teammate
  • Going further: parallel work with multiple threads and worktrees once the basics stick
  • Resources and community
  • Q&A

Your Instructor

Mark Kashef

Mark Kashef is the founder of Prompt Advisers, an AI consultancy that has helped hundreds of businesses seamlessly integrate generative AI into their workflows. With over a decade of experience in data science and machine learning, he has served in the roles of data scientist and data science manager at multiple startups. Through his popular YouTube channel, Mark helps professionals quickly understand and apply the latest AI innovations to solve real-world business challenges. He also has a background in finance, enabling him to combine technical depth with strategic business insight.

Mark regularly delivers keynote talks, moderates panels, and appears on podcasts, offering insight into how AI is transforming the way we work. He’s known for translating advanced AI concepts into accessible frameworks that decision makers can act on confidently. Mark holds a master’s of management degree in artificial intelligence from Queen’s University

Skills covered

  • OpenAI
  • Coding Practices