AI

Yesterday I gave a talk for MSSQLTips called “Building a DBA Agent for Your SQL Server Estate”. I’ll drop the recording into this post once it’s published. What I want to do here is pull the whole thing together in writing: the demos, what I actually ran against a live SQL Server estate, and the argument I’m making when I say an AI agent can be trusted near production.

If you’ve been following along, this is the third post in what’s turned into a series. In Giving AI Agents Visibility Into SQL Server with MCP, I built sql-mcp-server, a custom MCP server that gives an agent real DMV access. I said at the end of that post that skill files were coming in a follow-up also in Using Claude Code as a Database SRE Agent, I showed a skill file catching a silently unprotected DR instance against the Everpure Fusion fleet API and how to build compliance and observability reports quickly. So here we are.

I’ve been running this blog on Hugo for a long time, and like most blogs with real history, it’s accumulated some tech debt. Some of it is my own fault. This blog started on WordPress, where it ran for seven years, and I migrated it to Hugo back in 2021. That migration exported those seven years of posts straight from WordPress’s database into raw Markdown, HTML tags, inline styles, and all. I am not a good HTML programmer, and it showed. Broken tags, stray   entities, image markup that only sort of worked, all of it scattered across dozens of WordPress migrated posts.

Here’s the scenario: one of my SQL Server instances migrated to the DR array. The VM moved, the old volumes were destroyed, and nobody created a Protection Group on the destination. There were no alerts. Nothing failed.

The DR environment just quietly had no data protection. No snapshots, no replication. We’d have had no idea until we needed to recover. Ok, well this was in my lab, but this could really happen in the real world.

I’ve been thinking a lot lately about what it actually takes to make an AI agent genuinely useful for database work, both for administration and for application access to the data tier. Writing the T-SQL code is the easy part. A coding assistant can do that out of the box. The hard part is giving it visibility into a running SQL Server: which sessions are blocked right now, where the wait stats are pointing, which indexes the optimizer is begging for. Without that, the agent is just guessing. With application access, an agent can propose how things should work, but what if we had tools that added context describing the agent database’s schema and what the entities actually mean to the application when interacting with the database agentically?

SQL Server 2025 is an upcoming release focused on AI, analytics, and modern database development, backed by innovations in mission-critical engine features for security, performance, and high availability.

Let’s dive into what this means for your AI and data-driven applications. We’ll walk through some of the new features announced by Azure Data Principal Architect Bob Ward in his post Announcing SQL Server 2025, and I’ll give some thoughts on these innovations and where they will fit in the enterprise.