An Honest Review of AI Programming • Hacker News Board

Re: An Honest Review of AI Programming

#61

Post by [deleted] » Tue, Aug 04, 2026, 2:13 PM UTC

cronin101 wrote: post #58

ryanackley wrote: post #56

Earlier quoted context omitted.

LLMs work perfectly fine for me but I’m building web app equivalents of binder keepers, like most people. Essentially store data, display data. The novelty is in what/how we’re displaying. LLMs are owning this market. Unless you yourself are doing commercial game development, calling the author disingenuous puts your own pro-AI bias on display. It’s based on speculation. I prefer to take his very specific examples an…

I’ve specifically used Opus to diagnose and fix performance bottlenecks in parallel Rust code on multiple occasions (e.g improving NPS for a chess engine) and it works well. I’ve done plenty of performance architecting in my day-job and rule #1 is generally “you can’t fix what you can’t see/measure”. I have a suspicion that many folks aren’t investing in letting AI actually introspect iterative execution via the appr…

[deleted]

Re: An Honest Review of AI Programming

#62

Post by grumbel » Tue, Aug 04, 2026, 2:31 PM UTC

Sharlin wrote: post #8

daishi55 wrote: 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.

Whenever an AI hallucinates an API call, you run the compiler, give it the error messages and it fixes it. A proper agentic workflow might do it all automatically. These are arguments form 2023 ChatGPT3.5 days when it didn't have tool access or Web search.

The modern problem with AI is more the opposite, you give the AI a task that is impossible with the tools at hand and instead of saying "That doesn't work", it starts elaborate workarounds to make it happen anyway.

Re: An Honest Review of AI Programming

#63

Post by psd1 » Tue, Aug 04, 2026, 2:43 PM UTC

cronin101 wrote: post #49

ryanackley wrote: post #34

Earlier quoted context omitted.

His experience is completely plausible. He’s in a niche that requires highly performant code and most complex, highly performant games do nit have source available for models to train on. It’s a very common observation that the farther you stray from mainstream, the less effective the LLM models become.

Have you actually tried performance optimisation using an agent? With any programming language/framework that has quality profiling tooling (which is a prerequisite for most projects) I have had huge success with automated hotspot profiling where the LLM can propose theories, test the impact of fixes, convince you of which to pursue, etc. High performance algorithms are quite well documented so it isn't unreasonable…

TFA's author's experience is the opposite of your claims. Your claims may be right in _your_ circumstances, but not theirs.

> High performance algorithms are quite well documented

That may be true for bloom filters or what have you. But the author states the obvious: all recent games are closed-source. So any algorithms or techniques for real-time 3D that an LLM was trained on are going to be a long way behind the state of the art. The author makes that point extremely clearly, and they have credibility.

> this reads a lot like someone who decided how they feel about LLM-driven engineering ~5 months ago

TFA? No. Your comments here? Yep. Try to imagine a world where different kinds of work have different applicability of tools.

Re: An Honest Review of AI Programming

#64

Post by kwertyoowiyop » Tue, Aug 04, 2026, 2:53 PM UTC

> It's interesting how AI is constantly providing false information and incorrect statements about my area of expertise. Fortunately, it's very useful and always right about topics I know very little about.— pikuma.com (@pikuma) June 19, 2026

Also true for TV commentators, bloviating C-suiters, frequent posters on social media, politicians, etc.

Re: An Honest Review of AI Programming

#65

Post by cindyllm » Tue, Aug 04, 2026, 3:12 PM UTC

righthand wrote: post #36

lnenad wrote: 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…

Not providing a source is how Llms get caught in sycophancy and hallucinations. The “tool” needs improvement, especially one that claims it’s intelligence. How would you react if you found out after schooling everything you learned has half-hallucinated because your teacher made it up and there is no text book or historical log of facts? You had assumed this whole time you were learning facts…now what?

[dead]

Re: An Honest Review of AI Programming

#66

Post by spprashant » Tue, Aug 04, 2026, 4:06 PM UTC

> While I have found LLMs useful for researching and planning code changes, my attempts at actually making them write code have been quite lackluster. I found them to be slow and expensive to generate, for a mediocre result.

I think this observation is generally true for the kind of problems the author is working on.

But I would not make the leap to avoid using LLMs for any kind of code writing. LLMs do fantastically well in the 95%+ of the code that engineers spend time on. And for those we should leverage the technology.

It is upto us as engineers to figure out when to stop using LLMs. We are smarter than just dumping logs and half dozen specialized markdown files to a LLM and have it figure out solutions.

Re: An Honest Review of AI Programming

#67

Post by abirch » Tue, Aug 04, 2026, 5:23 PM UTC

joshribakoff wrote: post #19

abirch wrote: post #12

Earlier quoted context omitted.

If you're using an LLM and not an agentic workflow then you're doing things wrong in 2026. My agents have to pass tests meaning that if their LLM hallucinates, the agent tools capture it and not me.

Some people have the agent hallucinating its own meaningless tests

If people misuse or don't understand a tool, that doesn't invalidate the usefulness of the tool.

Re: An Honest Review of AI Programming

#68

Post by munksbeer » Tue, Aug 04, 2026, 5:48 PM UTC

grumbel wrote: post #62

Sharlin wrote: post #8

Earlier quoted context omitted.

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

Whenever an AI hallucinates an API call, you run the compiler, give it the error messages and it fixes it. A proper agentic workflow might do it all automatically. These are arguments form 2023 ChatGPT3.5 days when it didn't have tool access or Web search. The modern problem with AI is more the opposite, you give the AI a task that is impossible with the tools at hand and instead of saying "That doesn't work", it sta…

> A proper agentic workflow might do it all automatically.

Might?!

Every agentic workflow should be doing this automatically for nearly a year now.

And yes, I agree with the latter. The lengths AI will go to, to get you a working solution is sometimes scary.

Re: An Honest Review of AI Programming

#69

Post by munksbeer » Tue, Aug 04, 2026, 5:49 PM UTC

kamranjon wrote: post #41

hahahaa wrote: post #25

Earlier quoted context omitted.

> Hallucinations are an inherent property of how LLMs work. While technically true the hallucination rates on modern models is low and other checks can ensure that by the time a human sees it it is most likely solid. For research there is more danger as there is less feedback loop other than other LLM scrutinising the first. For research I get it to come to a conclusion but provide me with links so I can judge. More…

“While technically true the hallucination rates on modern models is low…” Isn’t this entirely context dependent? Where did you get the information that modern models have low hallucination rates? I’d love to see the benchmark if there is one, it seems like it would be useful to track.

Put it this way, the agent may well be hallucinating behind the scenes when it is coding for me, but I never see that, because it obviously verifies by compiling and testing the solution and won't show me something that is broken.

Re: An Honest Review of AI Programming

#70

Post by munksbeer » Tue, Aug 04, 2026, 6:18 PM UTC

psd1 wrote: post #63

cronin101 wrote: post #49

Earlier quoted context omitted.

Have you actually tried performance optimisation using an agent? With any programming language/framework that has quality profiling tooling (which is a prerequisite for most projects) I have had huge success with automated hotspot profiling where the LLM can propose theories, test the impact of fixes, convince you of which to pursue, etc. High performance algorithms are quite well documented so it isn't unreasonable…

TFA's author's experience is the opposite of your claims. Your claims may be right in _your_ circumstances, but not theirs. > High performance algorithms are quite well documented That may be true for bloom filters or what have you. But the author states the obvious: all recent games are closed-source. So any algorithms or techniques for real-time 3D that an LLM was trained on are going to be a long way behind the st…

> That may be true for bloom filters or what have you. But the author states the obvious: all recent games are closed-source. So any algorithms or techniques for real-time 3D that an LLM was trained on are going to be a long way behind the state of the art.

Neither you, nor the author of the article has to use LLMs for coding. But if you want to, there are some practices you should follow to get best results, and that includes setting up your environment to give the agent the best chance for success. If you have various rules that are non-obvious, you add them to your AGENTS.md file (as we have at my corp and in my little niche). The agent will then follow those rules, and learn from the surrounding code.

I'll just be blunt here - I don't believe the author would have done anything more than the bare minimum to test his pre-existing bias that coding agents are bad. I don't believe he would have put the effort into getting it writing good quality code to suit the project he was working in.

We write high performance, low latency java for trading systems. Our codebase is highly structured around this and the READMEs and AGENTs file contain the information for how to successfully write code like this, originally for human consumption, and now agents.

And it works. So, I don't trust the article.