Training course · OpenAI Codex · Salesforce Development

OpenAI Codex for Salesforce Developers

Delegate development work with OpenAI Codex: CLI and cloud agent, AGENTS.md, sandboxing, approvals and team PR workflows.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects OpenAI Codex with the everyday processes of Salesforce Development. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

OpenAI Codex is a coding agent that runs both locally, as a command-line tool and IDE extension, and as a cloud agent. Locally, Codex reads your repository, proposes changes and runs commands inside a sandboxed environment. In the cloud, it works on delegated tasks in parallel inside isolated containers and returns results as traceable diffs or pull requests. Over two days you will learn how to combine both modes effectively and how to scope tasks so that the agent can complete them reliably and with minimal back-and-forth.

Control and security sit at the heart of the course. With AGENTS.md you hand Codex project knowledge, build and test commands, and conventions. You configure approval modes and sandboxing so that the agent only does what you permit, and you set up cloud environments with suitable setup scripts. You will also integrate Codex into your pull request workflows, use automated code review, and define team rules on which tasks are delegated and how results are checked before they are merged into the main branch.

Salesforce orgs grow over the years into complex platforms of Apex classes, triggers, flows, Lightning Web Components and integrations. AI coding assistants and agents help Salesforce developers write Apex and LWC faster, generate test classes with meaningful coverage, account for governor limits early and move sprawling trigger logic into clean frameworks. They support SOQL optimisation, metadata analysis and the migration from Process Builder and workflow rules to Flow. Because Salesforce code must be multi-tenant aware, bulkified and security-conscious, AI needs targeted context and clear rules. In this course you learn to combine AI tools with Salesforce CLI, scratch orgs and your DevOps pipeline while reliably respecting sharing rules, field-level security and platform limits.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Salesforce developers working with Apex and Lightning Web Components
  • Salesforce architects and technical leads
  • Salesforce administrators who also develop
  • Integration developers building Salesforce interfaces
  • Salesforce consultancies and partner teams

Typical challenges we address

  • Governor limits, bulkification and trigger recursion cause hard-to-reproduce errors
  • Mandatory test coverage consumes a lot of time writing test classes
  • Mature orgs with overlapping triggers, flows and processes and no documentation
  • Security requirements such as CRUD and FLS checks and sharing are often forgotten in code

What you will be able to do

  • You use Codex locally and in the cloud for the development tasks each mode suits best.
  • You write an AGENTS.md that guides the agent reliably through your project.
  • You configure approval modes and sandboxing to match your security requirements.
  • You delegate tasks to the cloud agent and review the results systematically.
  • Develop Apex and Lightning Web Components with AI support that are bulkified, secure and within limits.
  • Generate meaningful test classes and analyse org metadata systematically with AI agents.
  • Integrate AI tools with Salesforce CLI, scratch orgs and your deployment pipeline.

Course outline

Day 1

Module 1 Codex at a glance: CLI, IDE and cloud
  • Comparing how Codex works locally and in the cloud
  • Installing the Codex CLI, signing in and starting it in a repository
  • Interactive sessions, non-interactive execution and model choice
  • Distinguishing tasks that suit a coding agent from those that do not
Module 2 Project knowledge with AGENTS.md
  • Building an AGENTS.md with build, test and lint commands
  • Stating conventions, architectural notes and prohibitions precisely
  • Using nested AGENTS.md files for monorepos and sub-projects
  • Checking effectiveness and refining instructions iteratively
Module 3 Sandboxing, approvals and security
  • Choosing approval modes deliberately, from read-only to largely autonomous
  • Understanding sandbox boundaries for file system and network access
  • Handling secrets, dependencies from the internet and prompt injection
  • Configuration files for team standards and safe defaults
Module 4 Delegating tasks to the cloud agent
  • Configuring cloud environments with setup scripts and dependencies
  • Writing tasks with a clear goal, context and acceptance criteria
  • Launching several tasks in parallel and comparing the results
  • Using logs and test output to understand the proposed solutions

Day 2

Module 5 PR workflows and code review in the team
  • Turning results into pull requests and requesting follow-up changes
  • Using automated Codex code review on GitHub
  • Embedding Codex in scripts and CI pipelines
  • Setting team rules for delegation, review duties and accountability
Module 6 Practice lab: Salesforce Development
  • Writing bulkified Apex
  • Generating test classes
  • Building Lightning Web Components
  • Optimising SOQL and performance
  • Analysing org metadata
  • Preparing for security review
Module 7 Data protection, quality & transfer to daily work
  • Salesforce orgs hold customer and sales data: you learn to share only metadata and anonymised samples with AI services, protect credentials and connected app secrets, implement GDPR requirements for data retention and clarify licensing questions around generated code in AppExchange packages.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Writing bulkified Apex

Generate trigger handlers, service classes and batch or queueable jobs that keep SOQL and DML out of loops, respect governor limits and apply patterns such as trigger frameworks consistently.

Generating test classes

Create meaningful Apex tests with test data factories, positive and negative cases, bulk scenarios and assertions that verify real logic rather than just coverage, including mocks for callouts.

Building Lightning Web Components

Develop LWC components with wire adapters, Apex controllers, Lightning Data Service and Jest tests, and migrate existing Aura components step by step. Accessibility and loading states are covered too.

Optimising SOQL and performance

Write selective queries, interpret Query Plan results, spot large data volume issues and propose alternatives such as custom indexes, skinny tables or asynchronous processing. This prevents timeouts as data grows.

Analysing org metadata

Evaluate retrieved metadata to document automations per object, dependencies between fields, flows and Apex, and unused components, and plan clean-up work. The result is finally up-to-date documentation.

Preparing for security review

Examine Apex and LWC for missing CRUD and FLS checks, SOQL injection, unsafe sharing settings and cross-site scripting, and implement fixes using user mode and stripInaccessible.

Possible hands-on projects

Automation map

A script that reads an org’s metadata and shows every trigger, flow and validation rule per object, including execution order, in one overview.

Test data factory generator

A tool that produces a reusable Apex factory from object and field definitions, with required fields and valid picklist values.

LWC dashboard component

A Lightning Web Component that aggregates an account’s key figures from several objects and displays them with filters and drill-down.

Prerequisites

You have hands-on programming experience, are comfortable with Git and the command line, and know pull-request-based workflows. You already develop in Apex or Lightning Web Components and have a working knowledge of the Salesforce data model, governor limits and Salesforce CLI.

Technical requirements

Your own laptop with a terminal, Git and a Node.js runtime; a ChatGPT plan with Codex access or an OpenAI API key, plus a GitHub account for the cloud exercises.

Data protection & compliance

Salesforce orgs hold customer and sales data: you learn to share only metadata and anonymised samples with AI services, protect credentials and connected app secrets, implement GDPR requirements for data retention and clarify licensing questions around generated code in AppExchange packages.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Tue, 24 November 2026 – Wed, 25 November 2026 Online Request
  • Tue, 1 December 2026 – Wed, 2 December 2026 Munich Request
  • Thu, 10 December 2026 – Fri, 11 December 2026 Online Request
  • Thu, 17 December 2026 – Fri, 18 December 2026 Stuttgart Request
  • Tue, 19 January 2027 – Wed, 20 January 2027 Online Request
  • Thu, 28 January 2027 – Fri, 29 January 2027 Berlin Request

Frequently asked questions

When should I use Codex locally and when in the cloud?

Locally you work interactively and close to the code, for example when debugging or making exploratory changes where you want to follow every step. The cloud agent suits well-defined tasks that can run independently, such as adding tests or fixing smaller bugs. You can start several of these in parallel and review each one as a pull request.

What belongs in a good AGENTS.md?

A good AGENTS.md explains how the project is built, tested and checked, which conventions apply and which areas must not be touched. It is concise, concrete and kept up to date. Notes on architecture and common pitfalls also help. During the course you write an AGENTS.md for a project of your own and test how it changes the agent’s behaviour.

How safe is it to let Codex run commands?

By default Codex works inside a sandbox with restricted file and network access and asks for approval before risky steps. You decide how much autonomy to grant through approval modes and configuration. In the course you learn to choose these settings deliberately and to limit risks such as prompt injection or running unfamiliar dependencies.

How well do general-purpose AI assistants know Apex and Salesforce specifics?

Current models handle Apex syntax and common patterns well. Weaknesses show up around governor limits, bulkification and org-specific objects. With rule files covering your trigger framework, naming conventions and security standards, plus retrieved metadata as context, results become far more reliable. In the course you build exactly this context for your org.

Should an AI agent deploy straight into our Salesforce org?

We recommend letting agents work in scratch orgs or sandboxes and promoting changes to higher environments through version control and your deployment pipeline. That preserves reviews, test runs and approvals. Production orgs should be reachable by agents read-only at most, using a restricted user. You practise this way of working hands-on in the course.

How much does “OpenAI Codex for Salesforce Developers” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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