If someone had told me a few years ago that I would use Artificial Intelligence in my daily work to develop software, I would probably have thought of something distant — almost futuristic.
But today, to be very direct:
AI is already part of my development workflow — and it is no longer optional.
And I’m not talking about theory or hype.
I’m talking about real-world problems: OSB errors, complex Oracle queries, ADF validations… the kind of issues we deal with every day.
The turning point: when it stopped being just “autocomplete”
At first, I saw AI as something similar to a more advanced autocomplete.
But that changed quickly.
What really makes a difference today is not just code completion — it’s context understanding.
Modern tools are able to analyze broader scenarios and suggest structural improvements, not just isolated lines of code.
That’s when it clicked for me:
I was no longer just writing code.
I was working with a copilot.
A real example: an OSB error that used to take hours
Anyone who has worked with OSB knows how it goes…
You get a generic error like:
Then the usual process begins:
- Checking logs
- Reviewing pipelines
- Validating XQuery
- Fixing namespaces
- Testing endpoints
This can easily take hours.
Today, my workflow often looks like this:
- Copy the error
- Include the relevant pipeline snippet
- Ask the AI:“What could be causing this?”
And the answer usually comes with:
- Possible XQuery issues
- Namespace problems
- Integration or endpoint failures
It doesn’t solve everything automatically — but it dramatically shortens the investigation time.
No responses yet