Voice of the DBA

Tag: career

  • The End of Summer

    Growing up, this was the last week of summer for me every year. When I was a child in Virginia Beach, school started the day after Labor Day every year, which is next Monday in the US. This was our last chance to sleep in, enjoy the ocean, and stay out late without commitments. Starting next week we’d be back in school, up early, with homework to do every night.

    As an adult, the end of summer doesn’t really stand out anymore. Corporate changes are usually at the beginning of the year or in July, so it’s the end of June or December that are slower times. September is often the beginning of conference season for me, and I’ve usually been preparing for travel in September, as I am this year. I’ll be in San Diego in a little over a week for VS Live (if you want to join me, use the code Jones).

    I hope that most people have busy times and slow times at work. If you’re constantly busy and fighting fires, life is not good. That leads to stress, unhealthy living, and burnout. It’s not sustainable over time, at least not if you want to keep producing high quality work. I’ve lived in those situations and they’re neither enjoyable, nor the times when I’ve been at my most effective.

    When work is slower, I naturally slow down a little and appreciate that I can take more time to write, answer emails and messages with more detail, and think more carefully about situations. I also use the time to get ahead administrative tasks that I sometimes put off. For me, this is producing and scheduling things I’ll need later. This is often a time when I’ll write questions or editorials for the future.

    These are often the pieces I’m more pleased or proud of. I have time to work through details and spend more time reviewing my work. These are often the best questions I write.

    As a developer, this was the time I might refactor code I’m not pleased with, or tackle some niggling piece of work that I know is needed, but never has priority. As a DBA, this is when I refactor scripts and alerts, do more maintenance, maybe add some automation for tasks that I’ve just been doing manually because I don’t have time to do anything else. If I were  still a dev or DBA, this is when I’d be experimenting and practicing using AI as a lever to make myself more effective.

    When you have slower times, what tasks do you tackle? Documentation? Improvements? What else might not get done when the pace is a little more hectic? Let me know today.

    Steve Jones

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  • A Challenge of Our Knowledge

    AI is here to stay. It will evolve, it will get better at some things, and we might decide that it’s not good for certain tasks. It’s a weird, new, different technology that somehow seems magic, extremely intelligent, and at times as dumb as a box of rocks. It can do things that I could never do, or would never do, for myself. Heck, I’m not sure I could or would pay someone to do this by hand. Yet this was less than a minute for a computer system to take this image and transform it into something fun.

    Christian Buckley wrote an interesting post about AI challenging our identity, which sums up nicely one of the struggles many of us have with AI. Many of us identify with our work. We spend most of our lives for decades toiling away at a craft that we (hopefully) enjoy and in which we have success. We build skills, and we’re proud of our accomplishments.

    Some of us are more proud of our scars.

    Either is OK, but AI challenges that. AI can do work in seconds that we used to take minutes, often tens of minutes. Sometimes hours. It can remember things that we spend time googling or looking up in SQL Server Central forums. Our ability to search and navigate docs for an obscure setting, like that strange exit code you found in your CI/CD pipeline. We’re proud of where we’ve been and what we’ve done.

    I wrote recently about experts wanting to still solve problems themselves, without AI assistance. Some people don’t embrace AI because they think it devalues their knowledge. Others are afraid of the technology and potentially making mistakes with code an AI wrote that they don’t understand. They see this as a risk (and they should).

    However, choosing not to use the technology at all, or not trying to learn how and when to use it, is a mistake. We need to embrace the tools in our world, learning to take advantage of them.

    And more importantly, show our current and future employers we can do so.

    AI does challenge us. It challenges the way we used to work and some of the skills we used to rely on. We have to learn to flow with this challenge and make it a part of our future career.

    Steve Jones

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  • The Quiet Part

    Apparently, Meta did what a lot of employees suspect their management will do: use AI to lay off people. In this case, there is a report (and lawsuit) that Meta used it’s AI-integrated HR platform to make decisions about who to let go in a layoff. The rumor is that the AI used productivity metrics to choose who was the target of the layoff. As with a lot of AI failures, this appears to be another case of poor communication guiding the AI, or the AI not actually taking individual situations into account.

    A number of the people terminated were on maternity/paternity leave, which is a protected activity. Others may have been on other medical leave, though for privacy reasons, the article doesn’t have firm data to prove this. The lawsuit will likely bring more of this out, but this appears to be a case not just of AI making decisions, but of poor behavior from management. Plaintiffs were discouraged from taking leave off, which is something sh****y humans have said to people for decades. We need you; your baby or family isn’t important, so don’t use your leave. It’s one aspect of working in the US that is way worse than overseas, where there are more employee protections.

    Meta disputes the case, saying the AI didn’t make decisions. However, that brings out an interesting point. If the AI recommends things, who’s responsible? The humans, right? They still have to sign off on the decision. If they don’t perform due diligence, they’re still responsible, correct? I think so; after all, I’m responsible for code the AI writes if I commit it. Even if an agent does the work, I have to oversee it and approve (or grant permissions for) the actions.

    I. Am. Responsible.

    Trusting an AI to do a lot of work is like trusting a lot of smart, but very inexperienced staffers to work in your environment. There are always inconsistencies and reasons why we might code something, configure something, or deploy something a certain way. What seems like a good way to tackle the situation from the outside doesn’t always make sense when you have experience. Humans often have experience that AI agents lack.

    LLMs are relatively stateless, and while we can provide context, give them guidance, and provide comprehensive codebases, they still sometimes do silly things. This can be problematic, especially with database changes, which are stateful and disruptive to rollback.

    AI agents can make mistakes much like humans, only faster. Much, much faster.

    Labor is one of the most expensive parts of many organizations’ budgets. Plenty of management would like to replace relatively expensive humans with cheaper tokens. That isn’t working out as well in practice, despite lots of experiments. Hopefully, other organizations realize that AI is a tool, not a replacement for humans, and we can’t trust it or even believe it’s outputs without some human judgment.

    Steve Jones

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  • Are You Working More Hours?

    Recently, I noticed my son was coming home later and going to work earlier. He typically works a 9/80 schedule as a software engineer, but at times he might work extra hours on a deadline. His company tries hard to keep employees working a set schedule without overtime. Unless there is a need, after all, this is software. However, when they are on a deadline, management warns people, and they try to manage overtime to reasonable levels to avoid burning out employees.

    I asked him if he was extra busy or if AI was encouraging extra hours. He told me this was a short-term project with a few more hours, but mostly the team was decompressing a bit after work. I completely understood that as I’ve spent my share of time with co-workers at theend ofday, sometimes sharing a drink or meal nearby, sometimes just chatting in the office or the parking lot.

    There have been a number of studies and reports that AI is making people work more, not less. The time spent on a variety of tasks, especially those where we are reading or interacting with text, has grown. I suspect there is additional pressure from management as well to get more done since everyone has an AI assistant around. There is also the excitement of tackling new projects, which can lead people to spend more time at work. While I appreciate that AI can be exciting, and you might love it, don’t lose yourself in it at work. It’s still just a tool.

    And, of course, there’s the token spend. Some managers are measuring people on the amount of work their AI assistants do, rather than by what gets done. I’ve certainly seen plenty of people using AI to perform busy work just to be seen as using AI tools.

    At times, it seems people are using AI to process more information, which they then use AI to summarize. They post these summaries, which grow in number because the AI can produce more of them. Others use their AIs to read these summaries and produce their own summary of what they should be reading. It certainly seems like AI is producing more copies of information, summarized over and over, giving all of us more things to keep an eye on.

    That seems silly. While I like AI, I fall into that group that uses it lightly for targeted tasks. I certainly try not to create more reports, summaries, or even emails to send to others, especially large groups of people. We have enough to review without AI creating even more tasks to deal with every week.

    Steve Jones

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

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