441–450 of 1001 posts
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Also, do it assuming different linguistic backgrounds. It could sound dramatically different by people that speak English but as second language, which are going to be a whole lot of your users, even if the application is in English.
It's pronounced wanderfull in Norwegian
> Engineers don't try because they think they can't. This article assumes that AI is the centre of the universe, failing to understand that that assumption is exactly what's causing the attitude they're pointing to. There's a dichotomy in the software world between real products (which have customers and use cases and make money by giving people things they need) and hype products (which exist to get investors excite…
One interesting take away from the article and the discussion is that there seem to be two kinds of engineers: those that buy into the hype and call it "AI," and those that see it for the fancy search engine it is and call it an "LLM." I'm pretty sure these days when someone mentions "AI" to me I roll my eyes. But if they say, "LLM," ok, let's have a discussion.
Ex-Google here; there are many people both current and past-Google that feel the same way as the composite coworker in the linked post. I haven't escaped this mindset myself. I'm convinced there are a small number of places where LLMs make truly effective tools (see: generation of "must be plausible, need not be accurate" data, e.g. concept art or crowd animations in movies), a large number of places where LLMs make…
Author here if anyone has thoughts
> Bring up AI in a Seattle coffee shop now and people react like you're advocating asbestos.
can you please share the methodology you used to reach this conclusion?
in other words - what is the sample size? how many Seattle coffee shops did you walk into and yell out "hey, what do people think about AI?" (or did you gather the data in a different way, such as by approaching individual people at the coffee shop?)
what is your control group? in other words, how many SF coffee shops did you visit and conduct the same experiment?
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>AI is certainly not reliable enough for me to jeopardize the quality of my work by using it heavily. I mean this in sincerity, and not at all snarky, but - have you considered that you haven't used the tools correctly or effectively? I find that I can get what I need from chatbots (and refuse to call them AI until we have general AI just to be contrary) if I spend a couple of minutes considering constraints and bein…
> have you considered that you haven't used the tools correctly or effectively? The problem is that this comes off just as tone-deaf as "you're holding it wrong." In my experience, when people promote AI, its sold as just having a regular conversation and then the AI does thing. And when that doesn't work, the promoter goes into system prompts, MCP, agent files, etc and entire workflows that are required to get it to…
Then there’s people like me, who you’d probably term as an old soul, who looks at all that and says, “I have to change my workflow, my environment, and babysit it? It is faster to simply just do the work.” My relationship with tech is I like using as little as possible, and what I use needs to be predictable and do something for me. AI doesn’t always work for me.
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>AI is certainly not reliable enough for me to jeopardize the quality of my work by using it heavily. I mean this in sincerity, and not at all snarky, but - have you considered that you haven't used the tools correctly or effectively? I find that I can get what I need from chatbots (and refuse to call them AI until we have general AI just to be contrary) if I spend a couple of minutes considering constraints and bein…
> have you considered that you haven't used the tools correctly or effectively? The problem is that this comes off just as tone-deaf as "you're holding it wrong." In my experience, when people promote AI, its sold as just having a regular conversation and then the AI does thing. And when that doesn't work, the promoter goes into system prompts, MCP, agent files, etc and entire workflows that are required to get it to…
This is almost the complete opposite of my experience. I hear expressions about improvements and optimism for the future, but almost all of the discussion from active people productivly using AI is about identifying the limits and seeing what benefits you can find within those limits.
They are not useless and they are also not a panacea. It feels like a lot of people consider those the only available options.
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Engineers at Google are much less likely to be doing green-field generation of large amounts of code . It's much more incremental, carefully measured changes to mature, complex software stacks, and done within the Google ecosystem, which is heavily divergent from the OSS-focused world of startups, where most training data comes from
There are plenty of good tasks left, but they're often one-off/internal tooling. Last one at work: "Hey, here are the symptoms for a bug, they appeared in - go figure out the CL range and which 10 CLs I should inspect first to see if they're the cause" (Well suited to AI, because worst case I've looked at 10 CLs in vain, and best case it saved me from manually scanning through several 1000 CLs - the EV is net positiv…
But unfortunately the nuances in the former require understanding strengths and weaknesses of current AI systems, which is a conversation the industry doesn't want to have while it's still riding the froth of a hype cycle.
Aka 'any current weaknesses in AI systems are just temporary growing pains before an AGI future'
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> No one HAS to use AI. Well… That's no longer true, is it? My partner (IT analyst) works for a company owned by a multinational big corporation, and she got told during a meeting with her manager that use of AI is going to become mandatory next year. That's going to be a thing across the board. And have you called a large company for any reason lately? Could be your telco provider, your bank, public transport compan…
> My partner (IT analyst) works for a company owned by a multinational big corporation, and she got told during a meeting with her manager that use of AI is going to become mandatory next year. That's going to be a thing across the board. My multinational big corporation employer has reporting about how much each employee uses AI, with a naughty list of employees who aren't meeting their quota of AI usage.
It's mostly a sign leadership has lost reasoning capability if it's mandatory.
But no, reporting isn't necessarily the problem. There are plenty of places that use reporting to drive a conversation on what's broken, and why it's broken for their workflow, and then use that to drive improvement.
It's only a problem if the leadership stance is "Haha! We found underpants gnome step 2! Make underpants number go up, and we are geniuses". Sadly not as rare as one would hope, but still stupid.
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I don't see it that way. Tabs, spaces, curly brace placement, Vim, Emacs, VSCode, etc are largely aesthetic choices with some marginal unproven cognitive implications. I find people mostly prefer what they are used to, and if your preference was so superior then how could so many people build fantastic software using the method you don't like? AI isn't like that. AI is a bunch of people telling me this product can do…
You can vibe-code a throwaway UI for investigating some complex data in less than 30 minutes. The code quality doesn't matter, and it will make your life much easier. Rinse and repeat for many "one-off" tasks. It's not going away, you need to learn how to use it. shrugs shoulders
I think the throwaway part is important here and people are missing it, particularly for non-programmers.
There's a lot of roles in the business world that would make great use of ephemeral little apps like this to do a specific task, then throw it away. Usually just running locally on someone's machine, or at most shared with a couple other folks in your department.
Code doesn't have to be good, hell it doesn't even have to be secure, and certainly doesn't need to look pretty. It just needs to work.
There's not enough engineering staff or time to turn every manager's pet excel sheet project into a temporary app, so LLMs make perfect sense here.
I'd go as far to say more effort should be put into ephemeral apps as a use case for LLMs over focusing on trying to use them in areas where a more permanent, high quality solution is needed.
Improve them for non-developers.