Recently I was working in VS Code and I saw a walkthrough for the new Copilot chat features. I decided to give those a try in trying to get some information from my SQL Server instance.
This post walks through a few things I did with this GenAI agent. There is a video walkthrough at the end.
Note: I have copilot access set on VS Code as a part of my employer’s benefit.
This is part of a series of experiments with AI systems.
First Steps
When I start VS Code, I see something like this.
One of the Walkthroughts recently mentioned copilot. If I click the “More” at the bottom right, I’ll get this image. You might see something different, but Id’ expect you have a Copilot walkthrough if you can use Copilot. I choose the 4th one down (where the mouse pointer is).
This opened a Copilot pane. There were a few items, and you can see on the left in the image below, some have checkmarks. I’d explored these before.
If I scroll up, I see the one I wanted to get, which was “chat about your code”. I picked this one. This opened a blade to the left when I clicked the blue “Chat with Copilot” button.
I had read there are these @ agents (look up at the right side) and decided to type “@”. I saw a list of things.
Lots of places to work, but I choose the @mssql agent, since this is the place I tend to work. In the lower pane, I typed a question.
Above this (still in the left blade), I got a response.
Below this, I got some text and code explaining how to access a list of databases on various platforms. Not sure why MySQL is first, but I’m assuming this is alphabetical. For SQL Server, I saw this. This is a reasonable answer, with some help on how to execute it.
I then decided to connect to my local instance. I have the MSSQL extension, so I clicked that and got a connection.
Rerunning that query produced the same response. However, when I opened a query window, I got different results. Note the little database icon on the left, below my prompt, with “Untitled-1” next to it. This is the context, which I also saw added to the lower prompt box, just above where I would enter a prompt.
However, this didn’t work. After a few minutes, I got this.
and this. The LLM is trying, but can’t seem to get a query to run. It did try.
I then decide to move on.
Getting Results Back from Questions
This isn’t really the type of thing I’d do, but I decided to try and get some info from a database. The one above isn’t that interesting, so I switched to asking the model some questions. Here’s the first one, where I don’t remember the exact table name, but I ask.
It’s queried the database, and there isn’t a player table. However, it continues to look and finds dbo.players.
Even better, once it has the answer, it also provides a little more info. Maybe good, maybe bad. This reminds me of talking with a person that gives me more information than I asked for.
I try something else. Let’s get some metadata, since I clearly don’t remember what’s in this database.
I get a nice response, with some guesses about what information is contained inside these tables.
OK, can I query for information. I’ve always been a bit more of a hitter than a pitcher, so I’ll ask a question. This isn’t asking to join specific tables, but get me an answer.
It worked, though to be fair, I tabbed over to SSMS and wrote this query in the same time (with SQL Prompt) as the Copilot agent. Cool to see as I’d forgotten Thome and Vlad were up there.
While I got the answer, I didn’t get the query. I asked for it and got it, with an apology.
I’ll do something else. Who played the longest. Might be a somewhat funny query to write for a quick answer. I’d have to join a few tables and look for a sum.
It likely remembered I wanted the query, so that was included, with an explanation. However, it only looked at the batting table.
I asked other questions about fielding and pitching and got those answers (Nolan Ryan, 27 years with fielding stats and pitching stats. So I asked that:
Below this, I see the two players who tied, which Copilot noted.
The code provided only returned one player. I checked, which is something that you should always do. I asked if I could get better code. I got a few options, and I liked the RANK one, so I tried it and it worked.
Slightly annoying, but when I think about this type of conversation with someone else, especially a junior dev, I might have the same results and iterate this way.
At this point I also asked about databases, and I got a result. Maybe I needed a query to run first? Not sure why this works now.
Summary
This was an interesting set of things I could get done with this agent in VS Code. It’s not amazing, but it was helpful. I could tackle some light query tasks or db query ones while also handling some other work. In this case I wasn’t in the zone, trying to code or decode a database schema. Instead, I had a few things to try, and I let the agent work while I tabbed over to close some emails and chats.
In a job where I might need to find info from an unfamiliar database, this could be helpful in getting things done, though it’s hard to know if it’s slower for me if I were focused on ths all the time. The agent can find some info without me, but it also failed in a few cases. I started to try and get other things done when I noticed delays in responding and some hung queries.
Learning to use an AI agent to help you is a skill, and it’s one that takes time to develop.
I’ll look at some more practical tasks in the next post.
Video Walkthrough
Here’s a video walkthrough of most of the stuff in this post. It differs slightly as working with LLMs is not deterministic.