In an era of increasing infrastructure complexity, VLDBs, and "massive SQL Server fleets," seasoned database engineers need ways to scale their impact. This session moves past the AI hype to show how a veteran practitioner integrates tools like Cursor, Claude, and Gemini into a real-world, mission-critical environment.

We will dive into a GitHub-centric development workflow, moving from manual scripting to an AI-assisted "Plan-Debug-Ask" model. We’ll explore practical use cases that go beyond basic chat:

Unit Testing & Regressions: How to generate a comprehensive battery of tests for T-SQL and PowerShell to ensure monitoring code remains stable across thousands of instances.

Log Diagnostics at Scale: Using AI to rapidly analyze and pattern-match SQL Error Logs, Windows Event Logs, and Cluster Logs to identify root causes faster than manual inspection.

Strategic Tooling: A look at the modern "AI Stack" for engineers—understanding how to navigate the strengths of different IDEs and models to determine when to use agentic workflows versus traditional documentation lookups.

Attendees will leave with a practical framework for using AI as a force multiplier—not to replace their 20 years of experience, but to automate the "bits and bytes" so they can focus on the big picture.

Speaker Context: I bring over 20 years of experience in the SQL Server ecosystem (currently a Senior Database Engineer at Salesforce). This isn't a theoretical session; these are the exact workflows I use to maintain code for a massive, high-consequence SQL Server fleet.

Session Style: This is a demo-heavy session. I will show real-world, GitHub-based workflows demonstrating how I use Cursor’s Agent mode and Claude Code to iterate on PowerShell scripts and T-SQL objects. I will share the "good, the bad, and the ugly"—including where these models excel and where they still require a veteran’s "sanity check" to avoid hallucinations.

Why This Session: This is my first conference presentation in several years, and I’ve chosen this topic because it represents the most transformative shift I’ve seen in my career since the transition to the cloud. My goal is to help other experienced DBAs and Engineers bridge the gap between their deep platform knowledge and the new era of AI-native development.

Level: Intermediate (200)