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Build full “product skills” and you'll probably be fine

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Re: Build full “product skills” and you'll probably be fine

#321
Silly take honestly. I use this example a lot, but how exactly do self-checkout systems make cashiers more productive?

There are tools which increase human productivity, while still requiring it (barcode scanners, for example). And then there are another class of tools which make human labour obsolete (self-checkout systems).

LLM's (as they exist today) could be considered both. Github copilot would be an example of how GPT can be used as a productivity tool by human programmers, but as the technology progresses AI will become less of a "copilot", and will gradually replace humans as the main decision maker. Then eventually LLM will probably be used by people completely none technical to replace the need for coders entirely.

Now the argument becomes, well this will open up new opportunities. Instead of being a programmer you can be be a user researcher on a project, which could be the case, but this is a much more nuanced argument.

The most well paid jobs are typically those which require years of knowledge retention and require the human to basically serve as an advanced expert system in some domain.

Both "good" and "bad" programmers can write code into a text editor, the difference is that the "good" programmer will make decisions backed up by years of professional experience – same for a good doctor or good lawyer. This is why we pay more for these professions, because that depth of knowledge is hard accumulate.

This is the very thing that GPT attacks. What it can't replace is someone physically laying bricks or plumbing pipes. But there is less depth of knowledge required in jobs like this which limits salaries for these professions.

So sure. Perhaps in the future someone can say, "hey, GPT, build me [x]", but just remember you won't be the only one who can do that and there is no significant depth of knowledge in such a job. So while GPT won't replace all jobs and may even create some new ones, expect it to replace or devalue the majority of "good" jobs like doctors, programmers, lawyers, designers, etc.

So to Carmack's point, he's right you'll be able to build websites and apps faster using GPT as a tool, but you'll probably do so for a fraction of the salary.

We've ran similar experiences over the last several decades with outsourcing. If your labour can be easily out sourced then your ability to retain a good salary drops. It's not that a worker today can't make clothes in the US faster and better than at any point in the past, it's that it makes no economic sense to do so.

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Another thing I'd note here is that I'm autistic as are a lot of programmers in my experience. My brain is built to do technical things and I struggle intensely with human interaction. In my opinion it's not that programmers "don't understand" software solves problems for people, it's that a lot of us don't naturally excel in those areas. I think it's fair to say a lot of like to stick to what we're good at, and that's generally writing code and designing complex systems. The more time I have to talk with users about their needs instead of doing technical work, the less useful I am. And I'm guessing designers are also people who want to design rather than type prompts into a chatbox.

So another consequence here is that we might increasingly be forced to do jobs we don't really want to do as AI restricts the areas of labour where humans can still compete.

Re: Build full “product skills” and you'll probably be fine

#322
post #301
post #86

Earlier quoted context omitted.

My career predates relational/SQL databases so I can confirm what you wrote. When Oracle came out the buzz was that a whole bunch of programmers would go away because managers and executives could write queries in a “natural” English-like language. That never happened. SQL is hard to master, but it’s the easy part of understanding the relational model and any particular schema. Instead Oracle and the other RDBMSs tha…

As someone trying to learn SQL it feels that there are much more steps: * language syntax * the relational model (relatively easy? It is just "there"?) * database schema, where I have 3 000 tables, or 50 0000 tables (that's how ERPs are made) * actualy knowing how to use the language * building those queries that join columns from 15 different tables together to deliver the needed data -> it sounds easy, but Im strug…

Building the queries is the easy part. Making the queries run fast with large tables is difficult and there are trainings available, but very focused and a bit expensive compared with the ones on large training websites (ex. LinkedIn Learning). For example Brent Ozar (brentozar.com) has lots of blogs and 2 sets of trainings for MS SQL Server, some for beginners and some for experts, that are extremely useful for people with such needs. Problem is, expert tuning for MS SQL is totally different than expert tuning Oracle that is totally different than Postgres and others.

On a side note, if you have to join 15 tables for a report it is a sign you may go in the wrong direction. In 99% of the cases I never needed more than 5-6 tables if the data is well structured, but that takes years to learn.

Re: Build full “product skills” and you'll probably be fine

#323

Earlier quoted context omitted.

> So exact in fact that they will need to specify a program in a click and drag interface, or in human language. This. I started programming in Machine Code, where the "editor" was a pad of graph paper. I've watched management- and business-focused people sneer at us geeks for my entire career, and watched them drool over the thought of finally getting rid of us. Hasn't happened yet. > I'd be surprised if the next st…

re: idea people True. And once their product hits the market, if it ever gets there, they don't thrive. Prior to launch they are sooooo in love with their idea that they are meticulous about features all the while thinking they're smarter than the market. They don't understand and appreciate the value of execution. Ideas are easy. Execution - because it involves people as well as adapting to change - is 10x harder. Y…

It's the usual: "I have a great idea for a Startup, now I just need the money to hire some Developers to implement it...". The Winklevoss twins for example come to mind...

Re: Build full “product skills” and you'll probably be fine

#324

Earlier quoted context omitted.

re: idea people True. And once their product hits the market, if it ever gets there, they don't thrive. Prior to launch they are sooooo in love with their idea that they are meticulous about features all the while thinking they're smarter than the market. They don't understand and appreciate the value of execution. Ideas are easy. Execution - because it involves people as well as adapting to change - is 10x harder. Y…

One of the things that I'm fairly good at, is walking people from "Crazy Idea That Will Never Work," through to "Finished Product That People Want." It tends to be a very long process, and often involves a lot of "trial balloons." I just went through that, in the last couple of years. The project we're realizing, looks absolutely nothing at all like what the CEO originally dreamed up, but everyone that has seen it, l…

I love this approach. What is your current role that allows you to do that?

Re: Build full “product skills” and you'll probably be fine

#327

Earlier quoted context omitted.

That's a great analogy, and it makes me wonder just how closely did Carmack himself follow this advice early in his career. I suspect that he wouldn't have got where he is without an unusually deep interest in the nuts and bolts.

Well - I've read some about origin of Doom/Wolfenstein - it was definitely a mixed bag (as expected from young man), but there was definitely a focus on end result (smoother animation, better 3d), than coding just for the sake of coding.

I think in context "smoother animation" and "better 3d" might be the kind of things that in this hypothetical future would be driven by ai. I think we'd be talking more about understanding story and reward mechanisms.

Re: Build full “product skills” and you'll probably be fine

#328
post #301
post #86

Earlier quoted context omitted.

My career predates relational/SQL databases so I can confirm what you wrote. When Oracle came out the buzz was that a whole bunch of programmers would go away because managers and executives could write queries in a “natural” English-like language. That never happened. SQL is hard to master, but it’s the easy part of understanding the relational model and any particular schema. Instead Oracle and the other RDBMSs tha…

As someone trying to learn SQL it feels that there are much more steps: * language syntax * the relational model (relatively easy? It is just "there"?) * database schema, where I have 3 000 tables, or 50 0000 tables (that's how ERPs are made) * actualy knowing how to use the language * building those queries that join columns from 15 different tables together to deliver the needed data -> it sounds easy, but Im strug…

As someone who did a lot of SQL back in the day, and is now doing some again for a startup POC, I'd say you're basically right but there is also:

* Rewriting queries and also parts of the schema when it turns out the things that made sense in the design phase cause massive bottlenecks once you get more data, or just get it faster, than you tested with.

Of course the good news is now you can run the best RDBMS's on your laptop, or on a $5/mo VPS; or have a small managed one starting at <= $15/mo. Plus ChatGPT can help you remember how to do that inside join. ;-)

Re: Build full “product skills” and you'll probably be fine

#330

Earlier quoted context omitted.

Actually chat gpt is quite good at understanding some kinds of wiggliness. I built a restful api and documented it in a readme.md file in the wiggliest of ways. I then asked chatgpt to turn the readme into a swagger spec and then give me a page that read the spec and gave me a nice doc page with api exercise tool. Both tasks it performed really well and saved me a whole bunch of time.

I have some meticulous API docs I've written, which I tried to get ChatGPT to convert into swagger It failed spectacularly I wonder if it's because the API is quite large, and I had to paste in ~10 messages worth of API docs before I was finished. It kept repeating segments of the same routes/paths and wasn't able to provide anything cohesive or useful to me. Was your API pretty small? Or were your docs pretty concis…

Chatgpt has a token limit. If you exceeded it then it would have no way of delivering a good result because it would simply have dirtied what you said at first. My api was not huge, about 8 endpoints.
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