Voice of the DBA

Category: Editorial

  • Using AI for the First Draft

    At the Redgate Summit in London, I ran a panel talking about Platform Engineering and how we can make developers more productive. One of the questions from our audience revolved around AI (Artificial Intelligence) technologies and how they might assist. As a note, AI tech includes a lot of different things, like machine learning (ML) among other things, but a lot of people seeing the media and hype around LLMs (large language models)  think those are AI. They see AI as what is implemented in ChatGPT and Copilot, which is correct, but incomplete.

    One of the panelists, Jeff Smith of Redgate, said that he views the output from AI as a first draft, something that bootstraps further work by a human. This can save time and can help someone be more productive, but it’s a starting point and a boost, not a final product.

    I had not thought of AI this way, even though I expect to have to test, refine, and edit the results I’ve gotten from various assistants. While it might be possible for me to keep refining my prompt and perhaps generate better results (code and/or text), I don’t know that it’s often worth the time to do much of this. I might do a little, but it’s much easier to take the result of AI as a first draft and then make it fit my requirements.

    In much the same way I use Stack Overflow or SQL Server Central for code snippets. They often give me a starting point and something I can then adapt to my needs without all of the time and effort spent on reading an API or SDK, experimenting with the syntax, and then actually using this in some code I’m writing. Similarly, I can get a head start on writing a summary or a pitch, though I’ll admit I’ve found it less useful there. In fact, for many of my editorials, I’ve tried to use it to summarize an article or web link, and it does a very poor job (IMHO).

    Some of you might be concerned or worried about this, and some might not. To me, the average-to-poor code produced isn’t any different than the legions of Stack Overflow developers or SQL Server Central DBAs who take code from an online forum and fail to test it. Anyone using any code (or prose) should test (proof) it and verify it works appropriately in their situation. We have a lot of people who don’t do that now and AI might exacerbate that with more code, but I don’t know if we are in a worse situation. We certainly seem to be able to produce lots of average tech professionals now who turn out plenty of average code.

    Ultimately AI is a tool that does exist in the world and will continue to exist. We have to learn to work with it and use it to our advantage. Good developers and DBAs will do that. I’d like to think that many organizations will look to hire and use those people as their staff and use fewer of the people who don’t bother to test and improve the results from their tools.

    Steve Jones

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

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  • DBCC CLONEDATABASE is Semi-Discontinued

    I saw a tweet that DBCC CLONEDATABASE was being discontinued for production databases, which both scared me and didn’t make sense. I’ve used this a few times for a quick copy of a database and like how it works. Discontinuing it seemed strange to me.

    Then I read the blog post, which notes that it’s not being supported for production deployments. The post doesn’t explain why, but I’m guessing this is because all the stats and other metadata moves, and this might mess up the optimizer if different data is added. I don’t know who deploys production databases like this, but I could see people who have federated or sharded databases using this to create a new blank copy and then uploading data into it. Or maybe people who need new databases that are distributed onto remote office/edge devices used it? If you use this to create production dbs, let me know.

    This command will still be used for generating schema-copies for diagnostic and troubleshooting purposes, which is what it’s there for. I assume this means Microsoft Support will support you using this to investigate strange query issues or if you create a database at their request. However, there isn’t a mention of this being used for development and test environments, which is where I use it.

    Specifically, I’ve used it quite a bit lately with Redgate’s subsetter utility. I need a target that’s shaped like the source, and dbcc clonedatabase gives me that. I don’t really care about stats or anything else, I just need schema set up to move data around. It’s useful there. It’s also useful for a quick test of a deployment, where I can ensure I get the latest production schema and then run a deployment against it (hopefully using Flyway), looking for errors.

    If you use this command, don’t worry. The tool isn’t going away, and the restriction against production copies doesn’t take place until March 1, 2025. That’s nearly a year from now to change your process. If you’ve never used it, well, I don’t have a good reason to start using it, but you ought to be aware of how it works. Learning about new features is handy, as you might discover a problem the knowledge can solve. However, if you don’t know it exists, it will never enter your mind as a solution.

    Be curious and try things. It’s easy, and it’s fun.

    Steve Jones

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

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

  • Life in a Startup

    I have worked for a few startup companies, including SQL Server Central. Each has been a different experience, and I learned a lot at each stop. However, I’m not sure I’d want to go through that process again at my age. I was thinking about the challenges and the excitement of being at a startup while reading about the founding of Reddit. The post doesn’t go a lot into the technical details or the working life, but it is an interesting read from a VC investor.

    I also found this post on Choosing Startup Life, which talks about what the author thinks about before trying to start a company. He compares this with life in a Big Tech company, which relates to lots of companies, in technology or not. The main differences are lower salaries, less infrastructure, lots of work, and upside in a startup. Big companies have higher salaries and more perks, less stress and responsibility, and not a lot of context-switching. In general, that’s been true in my experience, though in bigger companies that didn’t think they were software companies, I sometimes could end up with a lot of context-switching.

    When you work in a startup, I hope you have some passion or belief in what the company is building. I think that’s what drives a lot of Kickstarter/Indiegogo projects. Someone wants to start a business to do x and they believe in x. It’s important to do that since you are likely to need to work extra hours. Startups often are cash-strapped, so they don’t have a lot of services and infrastructure and depend on employees to work above and beyond their main job. They also are in a hurry to get cash, so they want to complete their work sooner, which means more hours per week. Not all are like this, and once there is some investment capital, hours can ease a bit, but investors want their return, so this isn’t a slow-paced, relaxed atmosphere.

    There isn’t a lot of security. I’ve had startups fail under me where we didn’t have enough money to make payroll. I’ve had them sold in an instant with the new owner deciding to drastically change the employment status for many people. At the same time, I’ve had some jobs that result in unexpected windfalls of money. I haven’t had a company go public yet, but perhaps that will happen at some point.

    I think about being in a startup like being in my first apartment in college. Nothing is provided, I don’t even know what I’m missing until I look for it, I keep long hours there, and everyone is responsible for everything. There are also a lot of arguments over who should/needs to/ought to do what.

    Is it worth it? I think that the chances of a startup becoming a success can vary. It is important to understand valuations if you are trading away hours of your life on a gamble you’ll make money. Keep an eye on the number of shares offered and the potential value they would have to reach to make a difference in your life. For that matter, make sure you know what a pile of money means for your life. USD$100,000 sounds like a lot if you got a check tomorrow, but how much would that change your life?

    If you decide to create a company and take outside investment, make sure you really understand finances.

    Startups are exciting, but make sure you like the people working around you. You’ll spend a lot of time with them, and if you don’t enjoy their company, you won’t enjoy your job. Startup life isn’t for everyone, but it can be an exciting chapter in your life.

    Steve Jones

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

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

  • Common Algorithm Concerns

    When we build software, many of us use the same algorithms to solve problems. We might choose a similar method for a quicksort or a lambda validation or a regular expression. For database work, your code for a running total (or other common challenge) is likely very similar to many other people. At least on the same platform. You might solve this differently in SQL Server and Oracle, but for the same type of database, many of us write very similar code.

    Actually, many developers might copy and paste an answer from SQL Server Central, Stack Overflow, or another site. I’m not sure if I think this is good or bad, as it’s a good idea to reuse code if it solves the same problem. If you copy it and don’t test it, that’s bad. After all, the code might not solve your slightly different problem if you don’t check it.

    In the modern world, if we build software for our business using an AI assistant, could our company be liable if we knew our competitors were using the same AI service? Is this any different than a human developer performing a copy/paste from SQL Server Central? I don’t think it is in many cases, though the same concerns about intellectual property might be present in either case.

    The concerns over AI seem murky in some sense, especially as the AI might “generate” code that isn’t directly available on some public resource. I do think that this is more of a collusion using a service than an algorithm. Still, in the hyper-connected world, where many of our applications might look to take advantage of some service instead of implementing it ourselves, this could be an issue.

    I ran across a piece that discusses a lawsuit about a common pricing algorithm being used by different hotels. In this case, it’s not that the developers at different hotels used the same code, but rather that the hotels used the same service from a company, which of course, used the same code for all their customers. Whether you think this is a valid lawsuit or not, this is the type of legal action that others might bring if two competitors ended up using the same AI service and developed very similar code that might behave the same way.

    I don’t think that AIs (at present) can actually develop new algorithms or solve problems in a new way. Instead, they predict the likely solution based on how they’ve been trained by similar scenarios. In that case, how concerned are we about how getting common solutions in disparate pieces of software? For most of us, I think we’ve be pleased that we have well-tested (hopefully) code that runs efficiently (again, hopefully) being re-used in many places. That would be better for most systems in the world.

    What isn’t better is if humans become more adept at specifying prompts and producing software without lots of specialized expertise. For many developers that might be average, or even slightly below average, this might cause them concern for the security of their position. With good reason, as labor is one of the most expensive parts of building software.

    Ultimately, just as with any other position, the best way to build a safe, secure career, is to continue to build your skills and produce value for your employer. That way it’s unlikely any AI will ever outperform you.

    Steve Jones

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

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