it's not like this. You need a very good product that solves a real pain much better than competitors and word of mouth will work wonders with a little marketing push.
Since I was 17 I built projects and sold some kind of digital product, from desktop apps to services and finally a 8 figure exit of a web app.
In my first 20 years of trials i made enough to support myself, i had multiple projects + consulting work that got me some money. I tried everything, but I got better and better on spotting what works.
I didn't chase unicorns, I chase things that I needed personally in my projects and also had an established market. I found out that building simpler, improved and niched versions of bigger products gives me a higher chance of making higher revenue faster. This was before the indie hacker movement started.
Eventually one of my many projects grew faster than previous trials and I knew something is there. 7 years later I had a 8 figure exit with a team of 20 people, 100% owned and fully bootstrapped.
Was luck involved? Maybe, but after 20 years of grinding was it more luck or persistence and continuous learning? How many opportunities for finding "luck" would someone that tried methodically for 20 years to launch a successful business will get?
The only reason that's on top of HN is that people really want Mythos to be bad. This "study" is a cheap gimmick, they pointed to the actual location with the vulnerability and said "something is bad here, find it".
The hardest part is locating the issue, if you point directly to it, you're not comparing the same thing by far, and they know it. This was just a stunt by them to get publicity, they knew what they were doing and many fell for it, including here.
Why this was such a big deal? Haven't people reach the moon so many years ago? By this time we should have lunar bases, not cheer so much that we got past the moon at a few thousands miles away.
People mostly lose their jobs and suffer through no failure they were positioned to avoid, and often through no fault of their own at all. Spending your career chasing fads out of fear of being abandoned to penury is at least as limiting as mere conservatism towards new technologies. The risk is real and the fear is valid but that isn't the solution, no individual action you can take is the solution.
you are overestimating the skill of code review. Some people have very specific ways of writing code and solving problems which are not aligned what LLMs wrote, but doesn't mean it's wrong.
I know senior developers that are very radical on some nonsense patterns they think are much better than others. If they see code that don't follow them, they say it's trash.
Even so, you can guide the LLM to write the code as you like.
And you are wrong, it's a lot on how people write the prompt.
> you are overestimating the skill of code review.
“You are overestimating the skill of [reading, comprehending, and critically assessing code of a non-guaranteed quality]” is an absurd statement if you properly expand out what “code review” means.
I don’t care if you code review the CSS file for the Bojangles online menu web page, but you better be code reviewing the firmware for my dad’s pacemaker.
This whole back and forth with LLM-generated code makes me think that the marginal utility of a lot of code the strong proponents write is <1¢. If I fuck up my code, it costs our partners $200/hr per false alert, which obliterates the profit margin of using our software in the first place.
By far most of the code LLMs write is for crappy crud apps and webapps not pacemakers and rockets
We can capture enough reliability on what LLMs produce there by guided integration tests and UX tests along with code review and using other LLMs to review along with other strategies to prvent semantic and code drift
Do you know how much crap wordpress
,drupal and Joomla sites I have seen?
Just that work can be automated away
But Ive also worked in high end and mission critical delivery and more formal verification etc - that’s just moving the goalposts on what AI can do- it will get there eventually
Last year you all here were arguing AI Couldn’t code - now everyone has moved the goalposts to formal high end and mission critical ops- yes when money matters we humans are still needed of course - no one denying that- its the utility of the sole human developer against the onslaught of machine aided coding
This profession is changing rapidly- people are stuck in denial
> that’s just moving the goalposts on what AI can do- it will get there eventually
This is the nutshell of your argument. I’m not convinced. Technologies often hit a ceiling of utility.
Imagine a “progress curve” for every technology, x-axis time and y-axis utility. Not every progress curve is limitlessly exponential, or even linear - in fact, very few are. I would venture to guess that most technological progress actually mimics population growth curves, where a ceiling is hit based on fundamental restrictions like resource availability, and then either stabilizes or crashes.
I don’t think LLMs are the AI endgame. They definitely have utility, but I think your argument boils down to a bold prediction of limitless progress of a specific technology (LLMs), even though that’s quite rare historically.
I agree that LLM architecture might hit a ceiling (although the trajectory is still upward at present) but I meant Deep Learning in general
I do think there is a great deal of VC baiting hype in statements by Dario and Altman about ai coding but at the same time the progress has indeed been positive
We've finally proven or unlocked the secret to learning in machines - the only question is how fast that progress curve is - yes it might get stuck for a few years but I think this is really an inflection point that we’ve reached with these technologies
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