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An Honest Review of AI Programming

mropert.github.io

1–10 of 89 posts

Re: An Honest Review of AI Programming

#2
> An Honest Review

> I do admit that this approach immediately triggered my contrarian side and made me very defiant of any AI tool.

Makes sense.

> While this could be partially remedied by always asking for a primary source or citation, I dislike the idea that one has to add magical incantations to their queries to get the right results. It’s a good laugh to make fun of “make no mistake” memes, until you start having to consider similar things seriously.

Man I am genuinely stumped at the obvious lack of desire to use something in a way it's supposed to be used. LLMs are tools and like with any tool it's on us to use it properly, not hitting a screw with a hammer and saying that hammers are a very stupid tool.

Re: An Honest Review of AI Programming

#3
> “Agentic workflow” (or whatever they’re calling it at the time you’re reading this article)

> Unlike the silver bullets of the past (like microservices or NoSQL)

> Hallucinations are an inherent property of how LLMs work.

> It’s all marketing and buzzwords

Not a serious article or thinker. I can get this stuff on Reddit if I want to read thrice-regurgitated cliches about AI.

Re: An Honest Review of AI Programming

#5
post #2

> An Honest Review > I do admit that this approach immediately triggered my contrarian side and made me very defiant of any AI tool. Makes sense. > While this could be partially remedied by always asking for a primary source or citation, I dislike the idea that one has to add magical incantations to their queries to get the right results. It’s a good laugh to make fun of “make no mistake” memes, until you start havin…

It's more like a hammer that never drives nails straight unless you hold it in a specific uncomfortable manner.

You shouldn't be required to tell an information retrieval tool to actually retrieve information rather than making it up!

Re: An Honest Review of AI Programming

#6
I read through a bit of it, and it seems like the author assumes training was done only on open source data, but I doubt that's actually the case. There are plenty of paid, proprietary source codes being sold out there, hacked code, that is.

Aside from that, I don't agree with the author's view on agentic workflows. Modern AI native development runs like a massive state machine, starting from MCP, local file systems, and what's usually called a harness.

I also noticed what might be a mistake in the author's domain, games. Putting aside the fact that inheritance based OOP is an outdated pattern, the suggestion to remove update() and put it into a manager class's List, then iterate with a for loop, is meant to eliminate overhead like P/Invoke costs in C#. But if Foo is still a class, a reference type, then List is just an array of pointers scattered across heap memory. Pointer chasing can still happen. So I think that's actually bad advice.(Of course, the same issue exists in Mr. Claude's code as well.)

If the author truly wanted Data Oriented Programming(or DOD), they would have specified struct arrays or NativeArray.

This is a tricky area. The author's goal was likely to remove the per MonoBehaviour Update call cost in Unity, which is why they suggested using List. But the instruction seems ambiguous, and I think that's part of the difficulty with AI development.

The objective function is the same, but the implementation varies and subtly differs from what I actually want.

From a design perspective, for team maintenance, the GameUpdateable abstraction might actually be better. But it's difficult. In terms of extensibility, an update manager that handles registration and expansion of multiple update targets might be over abstracting.

Writing this down makes me realize how many things I actually consider when putting code into a program. Sometimes I model how my next teammate might read it, and sometimes my words might be interpreted differently. It's really difficult.

Re: An Honest Review of AI Programming

#7
post #2

> An Honest Review > I do admit that this approach immediately triggered my contrarian side and made me very defiant of any AI tool. Makes sense. > While this could be partially remedied by always asking for a primary source or citation, I dislike the idea that one has to add magical incantations to their queries to get the right results. It’s a good laugh to make fun of “make no mistake” memes, until you start havin…

To be fair, hammers are bad screwdrivers. They are faster at driving screws and require less finesse to do so, but are really bad at taking them out, often break the screw, and often result in a fastening that superficially looks correct but fails to perform well under stress.

Two new types of screw, the ring-shank nonhelical fastener and the rivet, however, are changing everything. Soon, using screwdrivers will be rare except in special circumstances.

Re: An Honest Review of AI Programming

#8
post #3

> “Agentic workflow” (or whatever they’re calling it at the time you’re reading this article) > Unlike the silver bullets of the past (like microservices or NoSQL) > Hallucinations are an inherent property of how LLMs work. > It’s all marketing and buzzwords Not a serious article or thinker. I can get this stuff on Reddit if I want to read thrice-regurgitated cliches about AI.

I'd like to hear actual rebuttals to those quotes.

Re: An Honest Review of AI Programming

#9
post #8
post #3

> “Agentic workflow” (or whatever they’re calling it at the time you’re reading this article) > Unlike the silver bullets of the past (like microservices or NoSQL) > Hallucinations are an inherent property of how LLMs work. > It’s all marketing and buzzwords Not a serious article or thinker. I can get this stuff on Reddit if I want to read thrice-regurgitated cliches about AI.

I'd like to hear actual rebuttals to those quotes.

If the author can’t put in the effort to think of something original to say that hasn’t been said 1000x, why should I put the effort into rebutting cliches that were last relevant in 2024?

Re: An Honest Review of AI Programming

#10
post #9
post #8

Earlier quoted context omitted.

I'd like to hear actual rebuttals to those quotes.

If the author can’t put in the effort to think of something original to say that hasn’t been said 1000x, why should I put the effort into rebutting cliches that were last relevant in 2024?

So you basically agree but complain there are no new arguments against AI programming in the article?
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