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I had hardly written any code prior to ChatGPT other than teaching myself some VBA. Since then, using Gen AI tools to learn + write code, I have deployed a fun

I had hardly written any code prior to ChatGPT other than teaching myself some VBA. Since then, using Gen AI tools to learn + write code, I have deployed a functioning full stack application to the web. NextJS on Vercel, with a backend server also deployed running on Python, and a Supabase DB. Is it the best application ever making loads of money? Definitely not. Are there things wrong with it? Absolutely (although I promise I'm not exposing sensitive env vars and API keys to the web). Did the first versions look like absolute ass as I clumsily figured things out and made bad mistakes? You bet. But it's a functioning app that does some useful things and has real users. I would never have imagined doing this in a million years prior to Gen AI. Do some devs see mixed results depending on how they're using the tools? I'm sure. Is Gen AI overhyped broadly speaking? Probably so. But when I see people say it's a delusion, waste of resources, and everyone is wasting their time on it ... for me, it just doesn't line up.

DamnInteresting 1y ago
> I have deployed a functioning full stack application to the web Best hope ChatGPT plagiarized that code from people who properly sanitized user input, otherwise it might be vulnerable to SQL injection, XSS, etc. If such holes exist, it may be tough to resolve them without a professional. > But when I see people say it's a delusion, waste of resources, and everyone is wasting their time on it ... for me, it just doesn't line up. I don't think anyone would say LLMs are useless, but there are people out there comparing the birth of LLMs to the Industrial Revolution, and the advent of the Internet. Such claims are preposterous. I think the widespread use of LLMs will ultimately be undone by a few factors: 1) Due to the way LLMs function, they will never be totally cured of 'hallucinations'. They are accurate a lot of the time, and apparently useful in those times. But you can never really trust its output. That is an exhausting problem, and will burn people out. 2) Prices for LLMs are artificially very low right now, these companies are burning investor money to keep going. The 'cost' is going to have to go way up for these LLM providers to be sustainable. I put cost in quotes because it will be some cost in subscription prices, but also cost in terms of ads that will be inserted everywhere, and other degrading forms of monetization. 3) Models are running out of good training data. They'll either hit a wall, or continue training on content that was itself LLM generated, which will go the way of Habsburg Jaw in a jiffy. Ensloppification is real. I'm sure there will be niches for LLMs in the future, for those who can afford their true cost. But this cram-it-in-everything, available-everywhere frenzy will probably be looked back upon with deserved embarrassment.

DamnInteresting 1y ago

> I have deployed a functioning full stack application to the web Best hope ChatGPT plagiarized that code from people who properly sanitized user input, otherwise it might be vulnerable to SQL injection, XSS, etc. If such holes exist, it may be tough to resolve them without a professional. > But when I see people say it's a delusion, waste of resources, and everyone is wasting their time on it ... for me, it just doesn't line up. I don't think anyone would say LLMs are useless, but there are people out there comparing the birth of LLMs to the Industrial Revolution, and the advent of the Internet. Such claims are preposterous. I think the widespread use of LLMs will ultimately be undone by a few factors: 1) Due to the way LLMs function, they will never be totally cured of 'hallucinations'. They are accurate a lot of the time, and apparently useful in those times. But you can never really trust its output. That is an exhausting problem, and will burn people out. 2) Prices for LLMs are artificially very low right now, these companies are burning investor money to keep going. The 'cost' is going to have to go way up for these LLM providers to be sustainable. I put cost in quotes because it will be some cost in subscription prices, but also cost in terms of ads that will be inserted everywhere, and other degrading forms of monetization. 3) Models are running out of good training data. They'll either hit a wall, or continue training on content that was itself LLM generated, which will go the way of Habsburg Jaw in a jiffy. Ensloppification is real. I'm sure there will be niches for LLMs in the future, for those who can afford their true cost. But this cram-it-in-everything, available-everywhere frenzy will probably be looked back upon with deserved embarrassment.