Oracle APEX & AI

Oracle APEX has been one of the most important tools in my work for building database-driven business applications.

What makes APEX especially powerful for me is not only the low-code development experience, but the fact that it sits directly on top of Oracle Database.

Today, AI is adding another layer to that model.

My main interest is not simply how AI can generate more code. I am interested in how AI can improve application development while keeping systems structured, maintainable and governable.

Oracle APEX

I use Oracle APEX to build data-intensive business applications on top of Oracle Database.

My work around APEX includes:

application planning and architecture
data modelling
SQL and PL/SQL
page and component design
REST integrations
security
performance
maintainability
enterprise application development

For me, APEX is strongest when it is treated as part of the Oracle Database ecosystem rather than as an isolated low-code tool.

Selected Oracle APEX articles

Planning Oracle APEX Applications Before You Build

A practical approach to application planning before opening Page Designer: navigation, master-detail structures, authorization, standardization and common design mistakes.

Connecting Oracle APEX Applications with REST Enabled SQL

A real-world case study showing how separate Oracle APEX applications can work together through REST Enabled SQL while keeping data and application responsibilities separated.

Calling PL/SQL from JavaScript in Oracle APEX with AJAX

A practical example of calling server-side PL/SQL from JavaScript without submitting the page, using modern Oracle APEX techniques.

Start with APEX

If you are new to Oracle APEX, start with my beginner series:

Oracle APEX for Beginners

A practical introduction to Oracle APEX for developers who want to understand the platform step by step.

The series covers application creation, data modelling, application structure, pages, navigation and reports.

The goal is not only to show where to click, but to explain how the pieces fit together.

AI-assisted development

Generative AI is changing how software is designed and built.

AI can already help with:

application design
SQL and PL/SQL development
documentation
testing
code generation
refactoring
data analysis
development workflows

But generating more software is not enough.

The important question is whether the resulting application remains understandable, reviewable, secure and maintainable.

APEXlang and the future of APEX development

One of the areas I find particularly interesting is APEXlang.

APEX has always been declarative. APEXlang takes that idea further by making the application definition easier for developers, source-control systems and AI tools to understand.

APEXlang and AI-Assisted Oracle APEX Development

Why I believe APEXlang is more than an export format, and how it can connect AI-assisted generation with source control, developer review, validation and enterprise governance.

The development model I find most interesting is not:

Prompt → generated application

but rather:

Business intent → AI → structured application specification → review → controlled application

AI provides speed.

APEXlang makes application intent visible.

The developer remains responsible for architecture, security and quality.

From early generative AI experiments to APEX 26.1

I started writing and speaking about generative AI in application development in 2023.

At that time, many of the ideas were still experimental.

Since then, the discussion has moved much closer to practical application development.

Generative AI in Oracle APEX: From a 2023 Vision to APEX 26.1

A look back at how my early ideas about natural-language-driven APEX development evolved toward AI-assisted development, APEX Assistant and APEXlang.

This evolution is one of the main themes I want to document on this site.

AI with enterprise data and documents

AI becomes significantly more valuable when it can work with trusted company information.

A general-purpose model may know a great deal about the world, but it does not automatically know:

your customers
your projects
your database
your contracts
your internal documentation
your business rules

That requires another layer of architecture.

Generative AI with Your Own Data and Documents

My practical experiments with Oracle Select AI, RAG, AI agents, SQL tools and company documents.

One of the main lessons was that an LLM alone is not enough.

Depending on the question, an enterprise AI assistant may need access to:

structured database data
company documents
APIs
specialized tools
business-specific instructions

The goal is not to give AI unrestricted access to everything.

The goal is to give it the right controlled tool for the right information.

Oracle AI and enterprise data

The areas I continue to explore include:

Oracle Select AI
generative AI with private business data
retrieval-augmented generation
vector search
AI agents
AI-assisted data analysis
application-level AI integration
enterprise data governance
AI-assisted software development

For business applications, the most interesting problem is not simply connecting an LLM.

It is combining AI with trusted enterprise data, application context and controlled access.

The question I keep coming back to

My work has gradually moved through several layers:

Database → APEX → Cloud → AI

Each layer has built on the previous one.

Oracle Database provides the data and business foundation.

Oracle APEX provides a structured application model.

Cloud provides infrastructure and AI services.

AI can now help developers and users work with all of those layers in new ways.

The question I keep coming back to is:

Can AI make enterprise application development significantly faster without sacrificing structure, security and maintainability?

This page — and the articles linked from it — document that journey.

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