Tag: career

As I’ve been working with some AI (Artificial Intelligence) technologies, what I’ve often found is that they produce junior-level code. The code I’d expect from someone early in their career or inexperienced in a particular area. That is code that likely works, but isn’t efficient or clean or perhaps incomplete in some way.

I’m sure AI technologies will improve, and we’ll be able to train them better for our environment. Just like we train junior developers to be better. However, what does that mean for junior people across the next decade? I ran across an interesting post on the death of the junior developer, which speculates we might have a problem as an industry.

The post references an article from Gene Kim, where a law firm sees a similar problem with their junior people, who are associates. That position might be equivalent to the junior developer in software. Someone with more experience and knowledge often reviews work and helps shape it, even though the junior person does the work. With AI, however, we might not need the junior person. Instead, the AI produces work the senior person has to review. Finding issues with associate work is a lot like finding hallucination problems in AI responses.

The same could be said of coding. There is plenty of poorly written code, but if senior people become good at writing prompts and getting the same code back that a junior developer would write, then how many junior people do we need? Arguably less, though you might still need a few. Or you might think that you need all the junior people and you’ll get 10x more work done, clearing your backlog. Certainly, I know most developers, DBAs, and other IT people have a large backlog of problems.

However, the problem with junior people using LLM (large language model) AIs and getting more done is that they might generate a lot more bad code, so much that your senior people can’t find the time to review the code and you end up with systems that contain even more technical debt than you have today. Perhaps we even find systems that don’t perform well enough for regular use or create constant issues that your developers try to fix with AI, which might not work. I can certainly see things deteriorating rapidly.

There’s a great quote in the Gene Kim piece: “I believe this furthers the case that AI helps the experienced people far more than inexperienced people — the seniors more than the juniors.”

I’m starting to think that might be the case. Senior people are going to become very productive, and very valuable. Junior people are going to struggle, and while they’ll get work done, the quality will vary. Maybe that’s good, or maybe we will start to see a rapid divergence of not only productivity but salaries. If you can hire a senior person to produce better code at the same rate as your 5 junior people, maybe you’ll want to pay that senior person $200k a year and reduce junior rates to $45k a year.

I don’t know that we’ll see rapid changes, as many organizations are slow to alter the way they hire, code, or structure their staff. However, as there is success by others, especially when it’s touted in places like the ETLS, I can see other managers being influenced. That will filter over time to those who hire to pick the productive, senior-level people who can showcase some code skills in an interview. Craft a prompt to solve a problem, get some code back, refine it, explain where and why you’d change your prompt or use parts of the code, and we might see the AI-capable people getting hired quickly, and for fantastic compensation.

I don’t know that I think this reduces a lot of junior staff, mostly because of organizational inertia, but I do think that learning to be better at your craft and learning to use AI is likely to increase your future earnings.

Steve Jones

I know a lot of people in this business do not have computer science degrees. While some do, I suspect it’s a minority. I’m certainly curious, so if you want to share your education experience in a comment, tell me if you have a degree and what the focus was, as well as answer a few other questions.

At DevOps Days in Minneapolis recently, professors Fox and Sen from Macalester College talked about their computer science curriculum for growing the next generation of professionals. Along the way, they also asked the audience these questions:

• what were you required to learn?
• what courses were key?
• what topics were the focus?
• what was the teaching style?
• what was missing?

While these are good questions for any curriculum, these are interesting points to reflect on for any sort of learning. If you learned about technology in the military, on the job, or by yourself, what did others (or you) think was important and required? What did you feel was left out of your learning?

Of my small group of 4 that chatted about this, only one of us had a CS degree. I started in CS, but I actually have an economics degree. I switched to business, sensing more opportunity in the 80s there. However, I’ve continued to learn, even taking some classes post-graduation, that helped me learn more about computing.

It was an interesting look at a modern CS major, with lots of comments from the audience. The professors left us with their questions about how to look to the future, address AI, and even if they should teach an operating systems course, something both feel is missing from Computer Science at their college.

I think computer science is important for the world to advance how we build systems, but a lot of the deep theory on topics isn’t something that many of us need to learn. I would like to see a software engineering major come about that emphasizes more of the knowledge we’ve learned about building software, with emphasis on version control techniques, software design architectures, and process flows. While DevOps has been amazing, a lot of that knowledge could be used to better teach people how to build software in different ways. Distributed systems, database theory, performance measurement, and even different ways of managing code are things that need deep treatment, not just a module in another course.

Let me know today what you think of your education in computers.

Steve Jones

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

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

One of the challenges many people have is focusing their learning efforts along some path. The best way to move forward is with steady effort that guides you through steps to build knowledge or skill. However, with so much information out there on the Internet, how do you decide where you focus your efforts?

Lots of people choose a random method, but the world is full of those people, many of whom never develop strong skills. That might be fine if you are an hobby guitarist or piano player, but it’s not the best way to approach your career.

Choosing what you want to learn is hard, but if you were to try and become a better Database Administrator, what do you think of this list: the ultimate checklist for Jr DBAs. This is a long list of topics in various areas, such as basic concepts, indexing, backups, security, objects, etc.

I think it’s not bad, but it leaves you a lot of work to do on your own. You have to find places that explain these items, which can be a chore. If you find a link, how do you know it’s good? You can’t judge because, well, you don’t know. You’re learning here.

I wish there were more guidance in posts like this. Not necessarily more information in this post, but with links that might help someone know where to look for good information. If you know these things, then what do you think is a good source of information? Maybe on your own blog or maybe an article that taught you something. I’m sure I don’t always provide background links, but I try to ensure I include links to help someone learn more.

Inside a company, I might include internal links to our policies or documentation. As an example, maybe we write down how often we think stats should be updated as a standard and why or what types of backup schedules are appropriate. This would be an easy way to help someone learn why we approach our jobs in certain ways, which is a very specific type of learning we need. Other more general learning is important and would drive these decisions.

Would you make a list like this one for yourself? If you’re a junior DBA, you might find this helpful, though I’d suggest you ask others for input on where you learn about these concepts. For people looking to learn something else, such as Fabric or Snowflake, is this the type of list that would be helpful, assuming there are some links on where to learn more? Let us know today.

Steve Jones

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

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