531–540 of 544 posts
This is the most important part of the article. Key takeaway.
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This sounds like an absolute hellscape of an app architecture but you do you. It also doesn’t stop anything but the Module A imports C without you knowing about it. It doesn’t stop module A from just copy pasting the code from C and saying it’s using B. >almost always coming into new initiatives That says a lot about why you are so confident in this stuff.
Yes microservice based architecture is something no modern company does… Including the one that you were so confident doesn’t do it even though you never worked there… Yet I don’t suffer from spooky action at a distance and a fear of changes because my testing infrastructure is weak… Either I know what I’m doing or I’ve bullshitted my way into multiple companies into hiring me to lead architecture and/or teams from 6…
You may have 30 years experience architecting new applications, but when it comes to maintaining large applications, you’re a neophyte.
If you don’t have first hand experience with what long term maintenance looks like for your creations, you don’t have any reason to be telling anyone how to write maintainable software.
If I were you I’d be suffering from imposter syndrome big time. What if you’re just a really good salesman and bullshitter? If I were you I’d want to stick around at a few places to see first hand how my designs hold up.
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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 automate…
> 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 ac…
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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You should be critical. If you made something, you should proof that it works. Especially in todays world. This article contains no proof that their work actually works.
Except that all of it is open source and you can go try it. So this is basically me saying "I made a really nice cake, here, try some" and you're plugging your ears and going "lalalala can't prove this cake is good, lalalala it's shit".
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This is anecdotal but just a couple days ago, with some colleagues, we conducted a little experiment to gather that evidence. We used a hierarchy of agents to analyze a requirement, letting agents with different personas (architect, business analyst, security expert, developer, infra etc) discuss a request and distill a solution. They all had access to the source code of the project to work on. Then we provided the v…
I think the benefit may be task separation and cleaning the context between tasks. Asking a single session to do all three has a couple of downsides. 1. The context for each task gets longer, which we know degrades performance. 2. In that longer context, implicit decisions are made in the thinking steps, the model is probably more likely to go through with bad decisions that were made 20 steps back. The way Stavros d…
If you want specific, empirical, targeted advice or work from an LLM, you have to frame the conversation correctly. "You are a tenured Computer Science professor agent being consulted on a data structure problem" goes a very long way.
Similarly, context window length and prior progress exerts significant pressure on how an LLM frames its work. At some point (often around 200k-400k tokens in), they seem to reach a "we're in the conclusion of this narrative" point and will sometimes do crazy stuff to reach whatever real or perceived goal there is.
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It has not been formally verified which is essentially the only way to achieve code without defects with reasonable confidence. There are several studies that have found that there are roughly between one and twenty bugs per thousand lines of code in any software, this project has several thousand lines of code, so I would expect several bugs if written by humans and I have no reason to assume that large language mod…
But you said "it's not great code" and then said "i don't know", so your idea of it being "not great code" is purely speculative and totally unfounded.
[1] I would however argue the later thing is more rare as it requires competent developers, however this still does not preclude some misunderstanding of the requirements.
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This is anecdotal but just a couple days ago, with some colleagues, we conducted a little experiment to gather that evidence. We used a hierarchy of agents to analyze a requirement, letting agents with different personas (architect, business analyst, security expert, developer, infra etc) discuss a request and distill a solution. They all had access to the source code of the project to work on. Then we provided the v…
Probably the same reason it takes a team of developers and managers 6 months to write what one or two developers can do on their own in one week. The overhead caused by constant meetings and negotiations is massive.
> The overhead caused by constant meetings and negotiations is massive.
just the other day i was asked to prepare slides for a presentation about something everyone already knows (among many other useless side-work)... i feel like with "ai" in general we are applying bandages where my real problem is the big machine that gives me paper cuts all day...
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There's a lot of cargo culting, but it's inevitable in a situation like this where the truth is model dependent and changing the whole time and people have created companies on the premise they can teach you how to use ai well.
Its also inevitable given that we still don't even really know how these models work or what they do at inference time. We know input/output pairs, when using a reasoning model we can see a separate stream of text that is supposedly insight into what the model is "thinking" during inference, and when using multiple agents we see what text they send to each other. That's it.
> separate stream of text that is supposedly insight into what the model is "thinking" during inference
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> Its shocking some people don't give it any real instruction or way to check itself. It's not shocking. The tech world is telling them that "Claude will write all of their app easily" with zero instructions/guidelines so of course they're going to send prompts like that.
I think the implications of limited to no instructions are a little to way off depending on what you're doing... CRUD APIs, sure... especially if you have a well defined DB schema and API surface/approach. Anything that might get complex, less so. Two areas I've really appreciated LLMs so far... one is being able to make web components that do one thing well in encapsulation.. I can bring it into my project and just…
> this all takes work... lots of design work up front for how things should function... weather it's a ui component or an API backend library. From there, you have to add in testing, and some iteration to discover and ensure there aren't behavioral bugs in place.
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I read back through a few of your posts and you’re either schizophrenic, or a very elaborate troll. I know a few older people who started posting like this when they hit their 50s. I’ve only got a few years left. Hopefully I can avoid it, but maybe it’s inevitable.
Ageism: now that's a warrior's flex, amIRight? People like myself in their 50s to 60s who had the experience of banging the metal on imperfect buggy hardware late into the night to mine gems before Python made the entire software engineering community pivot to a core competency of syntax pedanting plus stringing library calls together are having a real party with AI agents effectively doing the same thing they did 30…
> There won't be 45% unemployment because the minute AI starts replacing current engineering skills for real is the minute the people it targets wake up and start learning how to work with AI coding agents that will be dramatically better than today.