Indeed, that's what I kind of hinted at in https://news.ycombinator.com/item?id=46442195 and coincidentally https://news.ycombinator.com/item?id=46437688 briefly after, namely that OK, one can "generate" a "solution", that's much easier than before... but until we can verify somehow that it actually does what it say it does (and we know of hallucinations and have no reason to believe this changed) then testing itself, especially of well know "problems" is more and more important.
That being said, it doesn't answer the "why" in the first place, an even more important question. At least though it does help somehow to compare with existing alternatives.
Folks think, they write code, they do their own localized evaluation and testing, then they commit and then the rest of the (down|up)stream process begins.
LLM's skip over the "actually verify that the code I just wrote does what I intended it to" step. Granted, most humans don't do this step as thoroughly and carefully as would be desirable (sometimes through laziness, sometimes because of a belief in (down|up)stream testing processes). But LLM's don't do it at all.
They absolutely can do that if you give them the tools. Seeing Claude (I use it with opencode agents) run curl and playwright to verify and then fix it's implementation was a real 'wow' moment for me.
We have different experiences. Often I’ll see Claude, et. al. find creative ways to fulfill the task without satisfying my intent, e.g., changing the implementation plan I specifically asked for, changing tolerances or even tests, and frequently disabling tests.
I see these “you had a different experience than me” comments around AI coding agents a lot and can concur; I’ll have a different experience with Copilot from day-to-day even, sometimes it’s great and other days I give up on using it at all it’s being so bad.
Makes me honestly wonder — will AGI just give us agents that get into bad moods and not want to work for the day because they’re tired or just don’t feel like it!
Don’t downvote because you don’t like the question.
It obviously adds to the discussion: paid and non paid accounts are being conflated daily in threads like these!
They’re not the same tier account!
Free users, especially ones deemed less interesting to learn from for the future, are given table-scraps when they feel it’s necessary for load reasons.
> LLM's skip over the "actually verify that the code I just wrote does what I intended it to" step.
I'm not sure where this idea comes from. Just instruct it to write and run unit tests and document as it goes. All of the ones I've used will happily do so.
You still have to verify that the unit tests are valid, but that's still far less work than skipping them or writing the code/tests yourself.
I disagree it's less work. It just carte blanche rewrites tests. I've seen it rewrite and rewrite tests to the point of undermining the original test intention. So now instead of intentionally writing code and a new unit test, I need to intentionally go and review EVERY unit test it touched. Every. Time.
It also doesn't necessarily rewrite documentation as implementation changes. I've seen documentation code rot happen within the same coding session.
One commercial equivalent to the project I work on, called ProTools (a DAW), has a test "harness" that took 6 people more than a year to write and takes more than a week to execute.
Last month, I made a minor change to our own code and verified that it worked (it did!). Earlier this week, I was notified of an entirely different workflow that had been broken by the change I had made. The only sort of automated testing that would have detected this would have been similar in scope and scale to the ProTools test harness, and neither an individual human nor an LLM is going to run that.
Moreover, that workflow was entirely graphically based, so unless Claude Opus 4.5 or whatever today's flavor of vibe coding LLM agent is has access to a testing system that allows it to inject mouse events into a running instance of our application (hint: it does not), there's no way it could run an effective test for this sort of code change.
I have no doubt that Claude et al. can verify that their carefully defined module does the very limited task it is supposed to do, for cases where "carefully defined" and "very limited" are appropriate. If that's the only sort of coding you do, I am sorry for your loss.
> access to a testing system that allows it to inject mouse events into a running instance of our application
FWIW that's precisely what https://pptr.dev is all about. To your broader point though designing a good harness itself remains very challenging and requires to actually understand what value for user, software architecture (to e.g. bypass user interaction and test the API first), etc.
It’s a shame that the source code isn’t commented and documented more. At the very least, I would see it being helpful to add some documentation for every CPU op code being emulated.
Forbidding LLM to write comments and docstrings (preferrably enforced by build and commit hook) is one of the best "hacks" for using that thing. LLM cannot help itself but emit poisonous comments.
And since it's vibe coded, no one knows what the opcodes are. LLM won't remember. Human has no comments. Human can't trust post-hoc LLM-generated comments because they're poisonous.
Meh. No human has written the horrors llm produces. At least I am yet to see codebase like that. Let me attempt a theatrical reenactment:
// Use buffer that is large enough to hold any possible value. Avoid using JSON configuration, this optimizes codebase and prevents possible security exploits!
size_t len = 32;
// this function does not call "sort" utility using shell anymore, but instead uses optimized library function "sort" for extreme perfomance improvement!!!
void get_permutations() {
... and so on. It basically uses comments as a wall to scribble grandiose graffiti about it's valiant conquests in following explicit instruction after fifth repeat and not commiting egregious violence agains common sense.
I used to worry that using LLMs to code would let them use my code and train on my hard work. Then I realised how bad my code is, so I'm probably singlehandedly holding off an agi catastrophe.
Even if you try to get them to not, they will still overcomment the code. Or at least overcomment it from the perspective of a human. From the perspective of the LLM, I suspect the comments are necessary for it to be able to get the code output correct.
It's also a discoverability tool. If the code has good docstrings and decent naming for functions/variables it's a lot easier for the LLM to find the correct places to edit.
Heck, when Satya Nadella wanted to demonstrate Copilot coding, he had it emit an Altair emulator. I guess there's little room for creativity in 8-bit emulator design so LLMs can handle them well. https://thenewstack.io/from-basic-to-vibes-microsofts-50-yea...
This is a good point. I wonder how much NES emulator code is in Claude's training set? Not to knock what the author has done here, but I wonder if this is more of a softball challenge than it looks.
Give it copy paste / translate tasks and it’s a no brainer (quite literally)
But same can be said of humans.
The question here is, did it implement it because it read the available online documentation about the NES architecture OR did it just see one too many of such implementations.
Indeed, the 'cleanroom' standard always was one team does the RE and writes a spec, another team that has never seen the original (and has written statements with penalty clauses to prove it) then does the re-implementation. If you were to read the implementation, write the spec and then write the re-implementation that would be definitely violating the standard for claiming an original work.
WASM and the performance seems catastrophically bad (45ms to render a frame on an M4 laptop)? It would be much more impressive if Claude could optimize it into something that someone would actually want to play? Compare this to a random hit from Google, https://jsnes.org/ which has sound, much smaller payload, and runs really fast (<1ms to render a frame).
The cost of slop is >40X drop in performance? Pick any metric that you care about for your domain perhaps that's what you're going to lose and is the effort to recover that practical with current vibe-coding strategies?
It demonstrated the capabilities of an AI to a potentially on-the-fence audience while giving the author experience using the new tools/environment. That's solid value. I also just find it really cool to see that an AI did this.
Yeah, it shows the AI is not capable of writing maintainable projects. I'm off the fence. And its cool you find it cool, but reducing the problem space to that of a toy project makes it so much less impressive as to be trivially ignorable.
The new LLM (pattern recognizer/matcher) is not a good tool
That being said, it doesn't answer the "why" in the first place, an even more important question. At least though it does help somehow to compare with existing alternatives.
Why would this be any different?
Folks think, they write code, they do their own localized evaluation and testing, then they commit and then the rest of the (down|up)stream process begins.
LLM's skip over the "actually verify that the code I just wrote does what I intended it to" step. Granted, most humans don't do this step as thoroughly and carefully as would be desirable (sometimes through laziness, sometimes because of a belief in (down|up)stream testing processes). But LLM's don't do it at all.
Makes me honestly wonder — will AGI just give us agents that get into bad moods and not want to work for the day because they’re tired or just don’t feel like it!
It obviously adds to the discussion: paid and non paid accounts are being conflated daily in threads like these!
They’re not the same tier account!
Free users, especially ones deemed less interesting to learn from for the future, are given table-scraps when they feel it’s necessary for load reasons.
I'm not sure where this idea comes from. Just instruct it to write and run unit tests and document as it goes. All of the ones I've used will happily do so.
You still have to verify that the unit tests are valid, but that's still far less work than skipping them or writing the code/tests yourself.
It also doesn't necessarily rewrite documentation as implementation changes. I've seen documentation code rot happen within the same coding session.
That's what the author did when they ran it.
Last month, I made a minor change to our own code and verified that it worked (it did!). Earlier this week, I was notified of an entirely different workflow that had been broken by the change I had made. The only sort of automated testing that would have detected this would have been similar in scope and scale to the ProTools test harness, and neither an individual human nor an LLM is going to run that.
Moreover, that workflow was entirely graphically based, so unless Claude Opus 4.5 or whatever today's flavor of vibe coding LLM agent is has access to a testing system that allows it to inject mouse events into a running instance of our application (hint: it does not), there's no way it could run an effective test for this sort of code change.
I have no doubt that Claude et al. can verify that their carefully defined module does the very limited task it is supposed to do, for cases where "carefully defined" and "very limited" are appropriate. If that's the only sort of coding you do, I am sorry for your loss.
FWIW that's precisely what https://pptr.dev is all about. To your broader point though designing a good harness itself remains very challenging and requires to actually understand what value for user, software architecture (to e.g. bypass user interaction and test the API first), etc.
And it, like, "You are absolutely right! This is an excellent observation! Let me implement this optimization right away!"
And you, like, facetable and crycryUntil it's so, it's just hearsay to me by someone having a multi-billion horse in the race.
Give it copy paste / translate tasks and it’s a no brainer (quite literally)
But same can be said of humans.
The question here is, did it implement it because it read the available online documentation about the NES architecture OR did it just see one too many of such implementations.
Indeed, the 'cleanroom' standard always was one team does the RE and writes a spec, another team that has never seen the original (and has written statements with penalty clauses to prove it) then does the re-implementation. If you were to read the implementation, write the spec and then write the re-implementation that would be definitely violating the standard for claiming an original work.
The cost of slop is >40X drop in performance? Pick any metric that you care about for your domain perhaps that's what you're going to lose and is the effort to recover that practical with current vibe-coding strategies?
This endeavor had negative net value.
The new LLM (pattern recognizer/matcher) is not a good tool
Github alone has +4k NES emulator projects: https://github.com/search?q=nes%20emulator&type=repositories
This is more like "wow, it can quote training data".