Debugging SQL with LLMS

Here’s the latest installment in the series on LLM-assisted coding over at The New Stack: Techniques for Using LLMs to Improve SQL Queries.

The join was failing because the two network_interfaces columns contained JSONB objects with differing shapes; Postgres’ JSONB containment operator, @>, couldn’t match them. Since the JSONB objects are arrays, and since the desired match was a key/value pair common to both arrays, it made sense to explode the array and iterate through its elements looking to match that key/value pair.

Initial solutions from ChatGPT, Copilot Chat, and newcomer Unblocked implemented that strategy using various flavors of cross joins involving Postgres’ jsonb_array_elements function.

The rest of the series:

1 When the rubber duck talks back

2 Radical just-in-time learning

3 Why LLM-assisted table transformation is a big deal

4 Using LLM-Assisted Coding to Write a Custom Template Function

5 Elevating the Conversation with LLM Assistants

6 How Large Language Models Assisted a Website Makeover

7 Should LLMs Write Marketing Copy?

8 Test-Driven Development with LLMs: Never Trust, Always Verify

9 Learning While Coding: How LLMs Teach You Implicitly

10 How LLMs Helped Me Build an ODBC Plugin for Steampipe

11 How to Use LLMs for Dynamic Documentation

12 Let’s talk: conversational software development

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