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lol. wish it was. fwiw i was pretty much bearish on AI for years because I did go deep into this shit since i got access to GPT 3. but since astra i have been q

lol. wish it was. fwiw i was pretty much bearish on AI for years because I did go deep into this shit since i got access to GPT 3. but since astra i have been quite bullish. 98% of people think AI means what gemini tells them when they do a google search. of that 2% who go beyond... maybe 20% of those are using AI to code. most SWE still think "using AI" to code means the copilot pane they open on the side in VSC. they get sloppy code output and think "ai sucks!" so of that 20%, maybe 5% have actually explored what an "agentic" workflow even means. they might use skills, set up their code base so AI almost NEVER makes a mistake. maybe 1-5% of that 5% actually went deeper, and those are the people who built tools like Cursor or Harvey or whatever other "agentic" companies. you are still thinking about the old world where you obsess and define data models and bike shed over data integrity, all the while you have a "temporary" table with 3 attributes that gets 2 million queries per second that's now holding up a bunch of other shit that's also glued together. > I could not think of a worse technology to use for an ETL pipeline than throwing LLMs at it and asking it to vibe out the correctness of the data every time it runs. like i said, if you are still having quality issues in 2026, that's a skill gap. also, agents now continually improve the process. for a business, the only thing that matters is transaction log. for 99% of businesses, swe are a cost. again this is like baby steps on the journey. we are still only 3 years into this technology being opened up to masses. i'm sure people thought computers were dumb, or that cars are stupid because the first cars were moving slow af. "we have horses, why do we need to build out roads to get anywhere" but you're free to feel smart doing 20/20 hindsight on things 100+ years from the future

lolakutty 10d ago
>like i said, if you are still having quality issues in 2026, that's a skill gap. So what ever shit the "AI" gets wrong, it is the user's fault, right?
- moomoo11 10d ago
  yes, if you use a tool improperly that's on you. i am specifically talking about people who don't use skills (the most basic shit) and then get sloppy code.
  - lolakutty 10d ago
    But what if I use the skills, and still can't model to follow it? Does the AI company say anywhere that they will refund the tokens if the model does not follow what is written in the Skills file? If there is no such guarantee, why should I spend time writing an elaborate skill file? There is no telling when the model chose to ignore stuff in it. I don't understand how people can work with something like that!
    - moomoo11 10d ago
      i think you miss the part about the loop. you're still building software for the past/current world. when you have chains of agents working seamlessly, where agents are managed by themselves (like spawning a new chain to do some scope of work), and it just sort of works on a infinite game loop, your system continually keeps improving as it works. at least, that is the goal with the systems i like to build. you have to do your due diligence, obviously, as you would with any TOOL you use. in that case it means having specific goals, methodologies, etc. that each model has to follow. (if one is a "hey grok explain this" type of person when it comes to using ai, ngmi) we have one agentic workflow where there are 4 different models that can be spawned (to handle tasks of various complexity), that work against an API (the source of truth). their goal is to work any time a specific file is uploaded, and handle it. it is a complicated file, with 1000s of line items, with varying amounts of uncertainty involved. it happens in the real world today, where it costs $xxx,xxx per year to do. because it involves many people and companies... it is done totally manually today.. how it works in order to get to that resolution is different based on the complexity of the task... sometimes there's bad data in the mix because people make mistakes when they create stuff (we're not special). in this case it requires finding out whether it is indeed bad data or actually correct. that requires setting up a scheduled job, and handling it when there is a resolution. i don't code this part. how this gets accomplished... the agents are able to work autonomously to handle any edge case, in order to complete the goal. the goal in this case is to ultimately record transactions (a goal of a business is to make money, believe it or not). does this not make sense? jeez hacker news used to be an imaginative place. the model that we pay $10-20 per 1M tokens will be $1 per 1M token next year. And the model next year that we can pay $10-20 per 1M token will be even better than Astra and Terra/Sol/Luna. It is an exciting time.
Capricorn2481 10d ago
> 98% of people think AI means what gemini tells them when they do a google search. > of that 2% who go beyond... maybe 20% of those are using AI to code. > so of that 20%, maybe 5% have... maybe 1-5% of that 5% actually went deeper How can you write any of this when you said you just started liking LLMs with Astra, a model that released two weeks ago. You're whipping out a bunch of made up stats trying to describe large swaths of programmers while admittedly being unfamiliar with the capabilities until two weeks ago? Why are you so antagonistic towards people's skepticism if you used them for years and found no value in them? This sounds more like a comment trying to generate massive amounts of FOMO. "If you REALLY put a lot of your money into them, that's when they shine! Don't believe the haters!" > like i said, if you are still having quality issues in 2026, that's a skill gap. > also, agents now continually improve the process. > for a business, the only thing that matters is transaction log. for 99% of businesses, swe are a cost. Maybe you should try building something for more than two weeks before making such big declarations, because this really does read like someone who is excited about a novel they wrote last night at 3 am
- moomoo11 9d ago
  because astra was a big jump, and it is a new model. i didn't get these types of results with fable. been building agentic workflows since gpt 3 days, and using AI coding agents since 2023. been building stuff for years, so i'm not just some w2/1099 type guy who bike sheds for a living lol this stuff is new... obviously it is a fast moving space.
- lolakutty 9d ago
  I think he is someone who got burned by some bad software contractors in the past...
  - moomoo11 9d ago
    no i’m just a startup founder who enjoys solving problems. already been through one IPO where i was an early employee so i’ve never really had to work with morons.

lolakutty 10d ago

>like i said, if you are still having quality issues in 2026, that's a skill gap. So what ever shit the "AI" gets wrong, it is the user's fault, right?

moomoo11 10d ago
yes, if you use a tool improperly that's on you. i am specifically talking about people who don't use skills (the most basic shit) and then get sloppy code.
- lolakutty 10d ago
  But what if I use the skills, and still can't model to follow it? Does the AI company say anywhere that they will refund the tokens if the model does not follow what is written in the Skills file? If there is no such guarantee, why should I spend time writing an elaborate skill file? There is no telling when the model chose to ignore stuff in it. I don't understand how people can work with something like that!
  - moomoo11 10d ago
    i think you miss the part about the loop. you're still building software for the past/current world. when you have chains of agents working seamlessly, where agents are managed by themselves (like spawning a new chain to do some scope of work), and it just sort of works on a infinite game loop, your system continually keeps improving as it works. at least, that is the goal with the systems i like to build. you have to do your due diligence, obviously, as you would with any TOOL you use. in that case it means having specific goals, methodologies, etc. that each model has to follow. (if one is a "hey grok explain this" type of person when it comes to using ai, ngmi) we have one agentic workflow where there are 4 different models that can be spawned (to handle tasks of various complexity), that work against an API (the source of truth). their goal is to work any time a specific file is uploaded, and handle it. it is a complicated file, with 1000s of line items, with varying amounts of uncertainty involved. it happens in the real world today, where it costs $xxx,xxx per year to do. because it involves many people and companies... it is done totally manually today.. how it works in order to get to that resolution is different based on the complexity of the task... sometimes there's bad data in the mix because people make mistakes when they create stuff (we're not special). in this case it requires finding out whether it is indeed bad data or actually correct. that requires setting up a scheduled job, and handling it when there is a resolution. i don't code this part. how this gets accomplished... the agents are able to work autonomously to handle any edge case, in order to complete the goal. the goal in this case is to ultimately record transactions (a goal of a business is to make money, believe it or not). does this not make sense? jeez hacker news used to be an imaginative place. the model that we pay $10-20 per 1M tokens will be $1 per 1M token next year. And the model next year that we can pay $10-20 per 1M token will be even better than Astra and Terra/Sol/Luna. It is an exciting time.

Capricorn2481 10d ago

> 98% of people think AI means what gemini tells them when they do a google search. > of that 2% who go beyond... maybe 20% of those are using AI to code. > so of that 20%, maybe 5% have... maybe 1-5% of that 5% actually went deeper How can you write any of this when you said you just started liking LLMs with Astra, a model that released two weeks ago. You're whipping out a bunch of made up stats trying to describe large swaths of programmers while admittedly being unfamiliar with the capabilities until two weeks ago? Why are you so antagonistic towards people's skepticism if you used them for years and found no value in them? This sounds more like a comment trying to generate massive amounts of FOMO. "If you REALLY put a lot of your money into them, that's when they shine! Don't believe the haters!" > like i said, if you are still having quality issues in 2026, that's a skill gap. > also, agents now continually improve the process. > for a business, the only thing that matters is transaction log. for 99% of businesses, swe are a cost. Maybe you should try building something for more than two weeks before making such big declarations, because this really does read like someone who is excited about a novel they wrote last night at 3 am

moomoo11 9d ago
because astra was a big jump, and it is a new model. i didn't get these types of results with fable. been building agentic workflows since gpt 3 days, and using AI coding agents since 2023. been building stuff for years, so i'm not just some w2/1099 type guy who bike sheds for a living lol this stuff is new... obviously it is a fast moving space.
lolakutty 9d ago
I think he is someone who got burned by some bad software contractors in the past...
- moomoo11 9d ago
  no i’m just a startup founder who enjoys solving problems. already been through one IPO where i was an early employee so i’ve never really had to work with morons.