Tag: AI

It likely isn’t a surprise to many of you that executives like AI. A survey shows that 74% of executives surveyed have greater confidence in AI-generated insights than advice from colleagues or friends. At the board level, even more (85%) favor AI-driven advice.

That’s amazing to me, and while I might think this is a bit too much trust being placed in these GenAI LLMs, perhaps it’s also partially because they work with too many people who aren’t great at their jobs. Plenty of people skim through data or focus on certain things and might miss the details. While an AI can read and summarize a lot, it might not have the context we expect. I tend to be a bit skeptical of AI summaries, often because they don’t necessarily weigh the different parts of an article the same way that I do. However, they can be helpful.

Even more interesting, 44% of executives say they would trust a GenAI to override their decisions based on insights, and 38% would trust AI to make decisions on their behalf. Business decisions based on data, or conclusions from a lot of inputs are different than producing working code, so I don’t know how accurate these models might be in this context. I do know that I want experienced people reviewing and judging GenAI outputs, and I would not allow an AI to override me without my input.

However, I wouldn’t just discount a GenAI recommendation. I tend to have strong opinions, but loosely held. I’ll change if there is evidence or a good argument to do so. It’s possible a GenAI might see things I miss and produce an insight that gets me to change a decision.

What’s a bit scary about the stats from this survey is that many executives see a skills gap in their staff, and their trust in GenAI might lead them to replace or augment existing staff with more GenAI tools. They might expect hiring can be delayed or slowed (or eliminated) with GenAI filling gaps. This might be especially true as many tech companies talk about how GenAI tools are making them more efficient.

That means that tech professionals should consider a few things. First, learn to work with GenAI tools and use them to prove your value to an organization. This includes learning when not to use them. Second, continue to improve your skills to ensure you can judge Gen AI results and emphasize that you are still the expert. Lastly, as the technology improves, consider adding some skills in how to train an AI to be a better assistant for you. The more efficient you are, especially with a GenAI helper, the more likely you are to impress executives and managers that are choosing which staff to keep.

Steve Jones

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I’m sure many of you have tried a GenAI LLM to do something. Maybe write some code, maybe get some sort of recommendation or suggestion, maybe to rewrite something or summarize text. I’m sure you have had some feelings about whether the tool made you more or less productive.

There was a trial conducted by the Australia Department of the Treasury on Microsoft’s 365 Copilot, asking for volunteers to participate and use the tool in their daily work. They used it and then completed a survey, which are summarized in this piece. Only 218 people went through the trial, and the results are interesting.

The headline says that the staff rated the GenAI less useful than expected. Those last two words are interesting because your expectations shape a lot of how you view anything in the world. If you expect little and get a little more, you might be happy. If you expect a lot and don’t get it, you might be very disappointed.

The sub-headline and the first sentence note that there still is an ROI from the tool. It isn’t as helpful and isn’t as widely applicable as people expected, but they chalk some of this up to product limitations and some to limited use by people. It was useful in summarizing things and drafting content, which are what they call basic administrative tasks. That’s interesting and likely where GenAI tools can help quite a bit.

Maybe the most interesting thing to me is that if Copilot saves 13 minutes a week for mid-level workers, it pays for itself. I don’t know how much time it would have to save me, but an hour or two a week might make me use it more. It certainly would be use a small monthly cost. So far, I haven’t committed to regular work with the tools, and I think I still spend more time learning and typing with GenAI tools than I’d like. I’m not sure if I am saving time over just doing the task myself. Some of that is because I have habits that allow me to work quickly and to use a Copilot, my pace slows.

This also brings up something I wonder about with these GenAI services. With the cost of compute services, there might not be a lot of margin for vendors to raise prices if people are only lightly more productive. I can see lots of companies starting to use these tools, realizing there isn’t as much value as they expected from increased productivity, and then dropping the cost from their budget. That might be some of what we saw in this years State of the Database Landscape, with less people using AI for database management tasks. I suspect some of the hype has died down and people aren’t finding the tools as useful as they expected.

I do think GenAI is helpful, but just helpful. It can’t do the work, and it can’t be trusted more than a junior worker. At least not yet. Maybe that will change, but I haven’t seen it to date.

Steve Jones

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I saw an article recently that a quarter of the Y Combinator startups have 95% of the code in their repos being AI generated. The article notes that if no other startups had any AI generated code (no idea the likelihood here, then about 24% of their code for startups is GenAI written.

24%

Is that high or low? If you think about all the code you’ve written in the last year, how much of it could be reasonably generated by AI? All the queries, schema changes, test code, dummy data insertions, refactoring to add a column to a table or result set. Could it be AI written?

Let’s assume you practice a bit and you could quickly get some table, view, and sproc code. If I were to ask an AI to add a date column to a table and adjust the view and sproc code, is that useful? If I can move on to another task, or start setting up a prompt to add some test queries (or tsqlt tests) for me, that might make me more efficient. Certainly I’d still have to think of how to model this, but could the AI save time?

There is a lot of code that AIs might not write well. Certainly any dynamic SQL stuff that might be susceptible to SQL Injection worries me. An AI might write this, but so can a human. If the human doesn’t understand this issue, then it doesn’t matter if the AI writes it or the human does.

Except the human can make more mistakes in a period of time with an AI helper than by themselves. At least, I think they will unless they just can copy/paste/search/replace the code themselves. Then maybe they can do the same level of damage to a codebase.

The article has this great quote: “… even if product builders rely heavily on AI, one skill they would have to be good at is reading the code and finding bugs.” That is very true, and it needs to be said to every manager, project leader, and executive. You still need trained, skilled, experienced developers.

This might be even more true for DBAs and ops people using AI to help them write scripts to change infrastructure. Plenty of people do this poorly now, but how many more quick scripts written by an AI will include unintended, insecure, or otherwise problematic code? People need to use the AI as a tool and review the output before using it.

So how much help could you get from an AI in your coding? 24%? 95% 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.