Learning to Grind

When I was younger, I had a variety of jobs, but in most of the positions I had to work hard for stretches. Really hard, as in more than 8 hours a day or 40 hours a week. Often as I was starting a new position, it took some time for me to develop some understanding, some skill, and some muscle memory. In some jobs, especially in restaurants, I also had to build the physical skills to be on my feet for many hours.

In technology, I’ve often found myself unsure of how to approach a new position, aware I had knowledge gaps about how things worked, and often, I was naïve or ignorant of some piece of technology my employer used. Even at jobs where I started as a developer or DBA on a known platform (ASP or SQL Server), I sometimes encountered some aspects of the technology that I hadn’t used in the past (like clustering).

In those situations, something I learned from my parents and a few youth coaches came to mind. I needed to bust my butt to be successful. The lessons I learned weren’t expressed so politely, but they boiled down to putting in extra time and focus, and continuing on that path until I was competent in the eyes of someone else, usually my boss.

I’ve encountered many people in the last decade that have much to learn. I’ve met far too many that didn’t understand their environments as well as I’d expect them to as a manager. I have encountered far too many people who wish they could be more skilled in some way, but they haven’t made a commitment do the work to further that wish. I’ve met far too few people who are working to improve themselves on a regular basis.

How do we teach people to grind away at something to improve themselves?

I don’t know. I’ve tried to motivate people, I try to give them examples, I’ve tried to provide suggestions. It seems that many people have lost the drive to invest in themselves to prepare for the future. Too many want their boss to train them and then re-train them when they don’t use a skill and forget it. Or they want their time in a position to count as experience. Or they want their boss to give them time out of their 40 hours, without having to make their own investment of time at night or on weekends.

Skill and experience don’t magically appear. They take work. They take grinding away, making mistakes, achieving small successes, taking a step backward, then driving forward in new ways. It’s effort, and it’s time. Read any story about a person who’s achieved success and you’ll find tales of study, work, practice on their own time.

If you want something different in your career, or in life, you have to work at that thing. Make a plan, but then work at it. Give up some leisure time. Not all, but some. Give up something fun to achieve something else later. Learn to sharpen your saw, polish your craft, grow your marketability, whatever you want to call it.

Just start doing it.

If you want to read a few examples, I have a short series of posts on grinding away at life.

Steve Jones

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

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

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Playing with the Data API Builder

I published an article today on the Data API Builder, which is a way of presenting your database tables as a REST or GraphQL API for developers. You can read the article to learn how to get started, but I’m adding a small thing in this post.

This is part of my posts on the Data API Builder.

Setting the Page

The default page for data is 100 elements (and the next URL). That’s a lot for display, and I might not want developers to get that much data by default. Perhaps I only want 5 rows.

In the JSON file, I’ll add an item below the development mode element (but a level above. I’ve shown this below:

2024-12_0164

The JSON is a bit fiddly, so you need to make sure you know where you’re adding this. The options are below the “runtime” at the same level as “rest” and other items.

Once I do this, if I query from Postman, I see this, only 5 elements (and the next)

2024-12_0165

A quick add, which will be in the next (or next after that) DAB article.

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The AI/Human Spectrum

I was asked this question recently: is it more likely that AI will replace humans or assist them in their work?

It’s a good question. If you think about the way AI is being hyped in 2024, many people think AI is, or will soon be, replacing people and we need less of them in work. I guess the simplified view is that AI can do the jobs of many people, but I’m not sure the world is that simple. What I think is more likely is that AI becomes a lever that assists a few people in getting more work done and potentially replacing other, less knowledgable humans.

Maybe it’s the ultimate, do-more-with-less pressure that the management in many organizations places on workers that has people looking to AI to help. Get more done this year, but we’re not adding staff, and potentially we’re removing a few staffers. Maybe AI can do your job?

AI can be a lever, and I do think that there are tedious tasks that we might have AI take on for us. We’ll need more of an agent/proxy approach to AI systems, as now I can ask AI to do some things that relate to text/images, but not actually do work for me. I want an AI to actually set my Out-of-Office for me, not give me instructions on how to do it or write the message for respondents.

The current Generative AI/LLM systems aren’t really smart or intelligent, but they do process vast amounts of data and mimic the responses that other humans might give. If you work in an area that can benefit from that type of interaction, maybe an AI works well as a lever and lets you get more done on any given day. For some jobs.

However, getting more done might not be enough. If I pair program with someone else and they write a bunch of poorly performing code, it takes me time to judge the quality of what they’ve written and then additional time to fix it. Getting more done in that situation can be a burden because the additional code produced requires additional rework. I might get less work done in some cases if the code is low-quality and I use a lot of time to rewrite or improve the code.

However, if I am tackling simple tedious tasks, perhaps basic CRUD work in an application, maybe an AI can generate enough SQL, web, C#, etc. code that the job is done quicker. Maybe not at the most efficient level, but how many of you think the code for your internal applications is amazing? Is it good enough? Can an AI do “good-enough” work?

As with a lot of dramatic changes to technology, I find myself going back and forth on the value produced. Some days I think the tech is amazing and some days I think it’s akin to the stuff I shovel out of horse stalls. AI is in the same boat with me, and while I think there is potential, I know that there are also downfalls and potential detractions from its widespread use.

Certainly, the need to evaluate and judge quality is a challenge with AI, which leans me towards the lever that assists talented humans and replaces less talented ones. The other issue is cost. The LLMs are expensive, and use a lot of compute power. I’ve seen some smaller models, perhaps tailored with RAG or other methods of refining (and limiting) their use will overcome that, but who knows. The current models, however, cost something to run and someone is going to have to pay for that. Is there enough ROI to do that?

Lastly, trust. Can we really trust an AI to give us accurate responses, or even perform work on our behalf? We have that problem with other humans now, but they work slowly compared to a computer. Can you imagine the problems that a rogue computer system could create with access to change things in the real world?

Answer my question today. Are AIs more likely to assist or replace people?

Steve Jones

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

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

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A New Word: Dolonia

dolonia – n. a state of unease prompted by people who seem to like you too much, which makes you wonder if they must have you confused with someone else – someone flawless, selfless, or easy to understand from a distance – feeling vaguely disappointed that they’re unwilling to spend the time it takes getting to know the real you.

I have a bit of dolonia when I meet some people at events who seem extra excited to meet me. I wonder sometimes if they think I’m someone I’m not. Not a different person, but their impression of what I’ve done with SQL Server Central seems outsized compared to what I think I’ve done.

Perhaps I have the opposite of dolonia, not realizing my own impact.

In either case, it’s a certainly a strange life I lead some days.

From the Dictionary of Obscure Sorrows

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