Voice of the DBA

Category: Editorial

  • Barely Reviewed Code

    Years ago I was giving a talk on software development and asked the audience how long it takes to review a PR that has 10 lines changed. Answers were in the minutes to tens of minutes range. I then asked how long it takes to review a PR that has 1,000 lines changed. Some people said hours, but a few people said seconds.

    I’ve often taken the latter, pessimistic view. Not because I don’t think engineers want to do a good job, but because I know human behavior. Most humans will get bored, lose focus, and end up skimming through a large amount of code. Many (most?) people don’t want to spend all that time, after all they have they their own code to write. They’ll just approve the PR and assume testing will catch any major issues.

    Even if a reviewer wants to do a great job, they likely will still miss things. It’s very hard to focus across that much code.

    This is a funny visual (from X) about code reviews. It’s titled “me reviewing code written by Claude before pushing it to production.” Plenty of people are probably laughing, or thinking this is a good reason to not use an AI to write code.

    However, I don’t think the problem is an AI writing code. If you trust the AI without reviewing things, that’s on you. You deserve blame if things fall apart.

    The bigger problem is that an AI can write code so quickly and can make so many changes that PRs will tend to be large. These changes will tend to not get human-reviewed with any level of focus or quality control. The problem is volume, not who wrote the code (or the quality). Certainly quality matters, but it’s easy to catch changes if you have a small volume of code. Harder if you have a lot.

    The more I use AI for spot work, to handle tedious things, to do something like subtly adjust spacing in a UI or focus on adjusting a few things in a data model, the easier it is to judge the focus and quality of the code. Is the change doing the job I need done, and is it doing it well?

    Code quality is a problem we’ve had ever since we started writing code. AI can make the problem worse, not because of poor coding, but because it will write so much code in a PR that you can’t review it appropriately.

    Steve Jones

    Listen to the podcast at Libsyn, Spotify, or iTunes.

    Note, podcasts are only available for a limited time online.

  • Republish: A Great Case for Powershell

    I’m still in Las Vegas coaching 13 year olds at the Red Rock Rave. Hopefully things are going well, though day 3 is often tough. It’s been a long weekend and players are tired (and coaches).

    I’ll be surviving today and then having a quiet night with my wife before returning tomorrow. I’ll see you Wednesday, but until then, you can read A Great Case for Powershell. Let me know how that has held up in the age of AI, 8 years later.

  • Republish: A Double Failure

    I’m off to Las Vegas for a volleyball tournament today. Fingers crossed we have a good weekend, and the team has a good experience. These tournaments can be stressful and tough with teams from all over the country.

    They can also be exciting when we win a few matches.

    While I’m gone, you get to re-read A Double Failure.

  • AI Database Central

    SQL Server Central has been a great success over the last 25 years. We’ve helped a lot of people improve their careers with the Microsoft Data Platform, primarily SQL Server, but we’ve published articles on other aspects of databases, including other platforms. I wrote a bit about the history of the site last month, with a few stories in various pieces. We even got Brian Knight to contribute a piece on what the site meant to him.

    Over the years, we experimented with trying to get an SSIS Central or a SSRS Central off the ground. However, we struggled to find other people who would have been willing to partner with us to provide content and answer questions. Eventually, we gave up, though I wish today we’d have pushed forward with a PostgreSQL Central site a few years back.

    However, we’re moving forward with AI Database Central next week. This is an experiment that will look to gather lots of articles and news on how AI technology can be used to work with databases. Our goal is to build a site that showcases some of the ways in which AI works well. To handle the load of producing articles, we’ve got a very modern take.

    We’re setting up a Clawdbot system that will read existing articles and questions and then produce its own articles based on the knowledge of what AIs have about database technology. For every article here on SQL Server, we’ll get a series of articles that cover the same topic on Oracle, MySQL, PostgreSQL, and MongoDB to start. We’ll turn the AI agents loose on more platforms over time, but our hope is that this will provide an exhaustive body of knowledge that other data professionals and AI agents can use. We’ll even have an MCP server available.

    Of course, we will take submissions, which AI agents will edit and provide feedback. We’re also looking to experiment with submissions of editorial topics and ideas, which the AI agent will then use to produce its own content for you to read.

    This will likely not work that well, mostly because it’s April 1 and this is an April Fools joke. It could be possible, couldn’t it? Not likely very good, but it could be fun.

    Steve Jones

    Listen to the podcast at Libsyn, Spotify, or iTunes.

    Note, podcasts are only available for a limited time online.