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Two kinds of AI users are emerging

martinalderson.com

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Re: Two kinds of AI users are emerging

#251

Post by Havoc »

Havoc wrote: post #5

The copilot button in excel at my work can’t access the excel file of the window it’s in. As in “what’s in cell A1” and it says I can’t read this file. Not even sure what the point is then frankly. I’m happily vibe coding at work but yeah article is right. MS has enterprise market share by default not by merit. Stunning contrast between what’s possible and what’s happening in big corp

Follow up on this - seems it’s connected to the type of excel files. It cant read xlsb ie binary excel

So it is connected…user just needs to somehow know/intuit (?!?!) that they need to convert the workbook

Re: Two kinds of AI users are emerging

#252

Post by notepad0x90 »

I suspect there are much more than two kinds. there is a varying degree of understanding what these tools are capable of, and that multiplied by what people need and how much they care about outcomes and consequences is the number of "kinds" of AI users.

Let's take the group of developers (to keep it simple) that have a deep understanding of LLMs and how they work. Even then, some don't care if it generates entire codebases for them, some know there will be bugs in it, they just don't care. Some care, but they know their job is to make their project managers happy. Others don't have apathy or pressure like that, but they'll still use it in the same way, because for one reason or the other it saves them time. I'm probably missing more examples, but it is the same usage, but different motivations, people, and environments.

Re: Two kinds of AI users are emerging

#253

Post by jihadjihad »

benjijay wrote: post #205
majormajor wrote: post #24

Earlier quoted context omitted.

One of the dirty secrets of a lot of these "code adjacent" areas is that they have very little testing. If a data science team modeled something incorrectly in their simulation, who's gonna catch it? Usually nobody. At least not until it's too late. Will you say "this doesn't look plausible" about the output? Or maybe you'll be too worried about getting chided for "not being data driven" enough. If an exec tells an i…

> If a data science team modeled something incorrectly in their simulation, who's gonna catch it? Usually nobody. At least not until it's too late. Will you say "this doesn't look plausible" about the output? I recently watched a demo from a data science guy about the impending proliferation of AI in just about all related fields, his position was highly sceptical but with a "let's make the most of it while we can" T…

Always a good idea to spot check the labels and make sure you've got JFMAMJ..JASON Derulo

Re: Two kinds of AI users are emerging

#254

Post by cheevly »

notarobot123 wrote: post #160
PunchyHamster wrote: post #142

I'd argue 2 types of users are * People using it as a tool, aware of its limitations and treating it basically as intern/boring task executor (whether its some code boilerplate, or pooping out/shortening some corporate email), or as tool to give themselves summary of topic they can then bite into deeper. * People outsourcing thinking and entire skillset to it - they usually have very little clue in the topic, are int…

> The second group is one that thinks talking to a chatbot will replace senior developer And the first group thinks that these tools will enable them to replace a whole team of developers.

A company with 5 developers could potentially downsize to 3 developers using AI, while improving overall velocity. Would you agree?

Re: Two kinds of AI users are emerging

#256

Post by mettamage »

cik wrote: post #223
PunchyHamster wrote: post #142

I'd argue 2 types of users are * People using it as a tool, aware of its limitations and treating it basically as intern/boring task executor (whether its some code boilerplate, or pooping out/shortening some corporate email), or as tool to give themselves summary of topic they can then bite into deeper. * People outsourcing thinking and entire skillset to it - they usually have very little clue in the topic, are int…

To me this misses a third group, those using these tools as a series of virtual teammates, a mock team member with which to ping pong possibilities. This is actually the greatest use case I see, and interact with.

Yea I am an ENFP. While I don’t think MBTI is scientific, it captures perfectly that I have the tendency to think out loud.

LLMs make me think out loud way better.

Best rubber duck ever.

Re: Two kinds of AI users are emerging

#257

Post by eitally »

ddsfsdf wrote: post #238
sevenzero wrote: post #151

Earlier quoted context omitted.

I started to outsource thinking at my job as my company made it very clear that they do not want/cant afford thinking engineers. Thinking requires time and they want to deliver quickly. So they cater towards the very realistic deadlines our PMs set for features (/s). Funnily enough the features have to be implemented ASAP according to the customers, but the customer feedback takes like 6 months due to them using the…

What do you really care? Its a job.

Historically (I'm 48), professionals have cared about their jobs, generally speaking, and often do make serious attempts to logically derive sociological benefits from their personal efforts. There's been a seismic shift over the past 5-6 years, though, and this sense of care has massively eroded.

Re: Two kinds of AI users are emerging

#258

Post by chrisjj »

Yossarrian22 wrote: post #237
chrisjj wrote: post #178

Earlier quoted context omitted.

To be fair, he said almost one-shot. It's like a CPU that's almost 100% reliable... in that it fails only once every 1 million clock cycles.

For a 4 GHz CPU that’s 4 failures a second..

My point entirely.

Re: Two kinds of AI users are emerging

#259

Post by Schiendelman »

sevenzero wrote: post #151
PunchyHamster wrote: post #142

I'd argue 2 types of users are * People using it as a tool, aware of its limitations and treating it basically as intern/boring task executor (whether its some code boilerplate, or pooping out/shortening some corporate email), or as tool to give themselves summary of topic they can then bite into deeper. * People outsourcing thinking and entire skillset to it - they usually have very little clue in the topic, are int…

I started to outsource thinking at my job as my company made it very clear that they do not want/cant afford thinking engineers. Thinking requires time and they want to deliver quickly. So they cater towards the very realistic deadlines our PMs set for features (/s). Funnily enough the features have to be implemented ASAP according to the customers, but the customer feedback takes like 6 months due to them using the…

As a product manager, this makes me think the features you're building are not the things your customers need or want most. I'm curious if you were to ask your product manager about that six-month timeframe, and just ask the open-ended question of is there anything on the backlog that we can build that the product manager thinks users would pick up within days instead of months?
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