5 ms·

They are not getting worse, they are getting better. You just haven't figured out the scaffolding required to elicit good performance from this generation. Unit

by theptip 10mo ago

They are not getting worse, they are getting better. You just haven't figured out the scaffolding required to elicit good performance from this generation. Unit tests would be a good place to start for the failure mode discussed. As others have noted, the prompt/eval is also garbage. It’s measuring a non-representative sub-task with a weird prompt that isn’t how you’d use agents in, say, Claude Code. (See the METR evals if you want a solid eval giving evidence that they are getting better at longer-horizon dev tasks.) This is a recurring fallacy with AI that needs a name. “AI is dumber than humans on some sub-task, therefore it must be dumb”. The correct way of using these tools is to understand the contours of their jagged intelligence and carefully buttress the weak spots, to enable the super-human areas to shine.

ashleyn 10mo ago
Having to prime it with more context and more guardrails seems to imply they're getting worse. That's fewer context and guardrails it can infer/intuit.
- falloutx 10mo ago
  Why the downvotes, this comment makes sense. If you need to write more guardrails that does increase the work and at some point amount of guardrails needed to make these things work in every case would be just impractical. I personally dont want my codebase to be filled baby sitting instructions for code agents.
- theptip 10mo ago
  No, they are not getting worse. Again, look at METR task times. The peak capability is very obviously, and objectively, increasing. The scaffolding you need to elicit top performance changes each generation. I feel it’s less scaffolding now to get good results. (Lots of the “scaffolding” these days is less “contrived AI prompt engineering” and more “well understood software engineering best practices”.)
frizlab 10mo ago
So basically “you’re holding it wrong?”
- greggoB 10mo ago
  I found this a pretty apt - if terse - reply. I'd appreciate someone explaining why it deserves being downvoted?
  - deleted 10mo ago
    [deleted]
  - Leynos 10mo ago
    It's something of a thought terminating cliché in Hacker News discussions about large language models and agentic coding tools.
  - mostlysimilar 10mo ago
    There are two camps who have largely made up their minds just talking past each other, instinctively upvoting/downvoting their camp, etc. These threads are nearly useless, maybe a few people on the fringes change their minds but mostly it's just the same tired arguments back and forth.
  - hug 10mo ago
    Because in its brevity it loses all ability to defend itself from any kind of reasonable rebuttal. It's not an actual attempt to continue the conversation, it's just a semantic stop-sign. It's almost always used in this fashion, not just in the context of LLM discussions, but in this specific case it's particularly frustrating because "yes, you're holding it wrong" is a good answer. To go further into detail about the whole thing: "You're holding it wrong" is perfectly valid criticism in many, many different ways and fields. It's a strong criticism in some, and weak in others, but almost always the advice is still useful. Anyone complaining about getting hurt by holding a knife by the blade, for example, is the strongest example of the advice being perfect. The tool is working as designed, cutting the thing with pressure on the blade, which happens to be their hand. Left-handers using right-handed scissors provides a reasonable example: I know a bunch of left-handers who can cut properly with right-handed scissors and not with left-handed scissors. Me included, if I don't consciously adjust my behaviour. Why? Because they have been trained to hold scissors wrong (by positioning the hand to create opposite push/pull forces to natural), so that they can use the poor tool given to them. When you give them left-handed scissors and they try to use the same reversed push/pull, the scissors won't cut well because their blades are being separated. There is no good solution to this, and I sympathise with people stuck on either side of this gap. Still, learn to hold scissors differently. And, of course, the weakest, and the case where the snark is deserved: if you're holding your iPhone 4 with the pad of your palm bridging the antenna, holding it differently still resolves your immediate problem. The phone should have been designed such that it didn't have this problem, but it does, and that sucks, and Apple is at fault here. (Although I personally think it was blown out of proportion, which is neither here nor there.) In the case of LLMs, the language of the prompt is the primary interface -- if you want to learn to use the tool better, you need to learn to prompt it better. You need to learn how to hold it better. Someone who knows how to prompt it well, reading the kind of prompts the author used, is well within their rights to point out that the author is prompting it wrong, and anyone attempting to subvert that entire line of argument with a trite little four-sentence bit of snark in whatever the total opposite of intellectual curiosity is deserves the downvotes they get.
clownpenis_fart 10mo ago
[dead]
Garlef 10mo ago
I'm referring to these kind of articles as "Look Ma, I made the AI fail!"
- falloutx 10mo ago
  Still I would agree we need some of these articles when other parts of the internet is "AI can do everything, sign up for my coding agent for $200/month"
techblueberry 10mo ago
"They are not getting worse, they are getting better. You just haven't figured out the scaffolding required to elicit good performance from this generation. Unit tests would be a good place to start for the failure mode discussed." Isn't this the same thing? I mean this has to work with like regular people right?
data-ottawa 10mo ago
Needing the right scaffolding is the problem. Today I asked 3 versions of Gemini “what were sales in December” with access to a sql model of sales data. All three ran `WHERE EXTRACT(MONTH FROM date) = 12` with no year (except 2.5 flash did sometimes gave me sales for Dec 2023). No sane human would hear “sales from December” and sum up every December. But it got numbers that an uncritical eye would miss being wrong. That’s the type of logical error that these models produce that are bothering the author. They can be very poor at analysis in real world situations because they do these things.
khalic 10mo ago
I’ve seen some correlation between people who write clean and structured code, follow best practices and communicate well through naming and sparse comments, and how much they get out of LLM coding agents. Eloquence and depth of technical vocabulary seem to be a factor too. Make of that what you will…

by theptip 10mo ago

ashleyn 10mo ago

Having to prime it with more context and more guardrails seems to imply they're getting worse. That's fewer context and guardrails it can infer/intuit.

falloutx 10mo ago
Why the downvotes, this comment makes sense. If you need to write more guardrails that does increase the work and at some point amount of guardrails needed to make these things work in every case would be just impractical. I personally dont want my codebase to be filled baby sitting instructions for code agents.
theptip 10mo ago
No, they are not getting worse. Again, look at METR task times. The peak capability is very obviously, and objectively, increasing. The scaffolding you need to elicit top performance changes each generation. I feel it’s less scaffolding now to get good results. (Lots of the “scaffolding” these days is less “contrived AI prompt engineering” and more “well understood software engineering best practices”.)

frizlab 10mo ago

So basically “you’re holding it wrong?”

greggoB 10mo ago
I found this a pretty apt - if terse - reply. I'd appreciate someone explaining why it deserves being downvoted?
- deleted 10mo ago
  [deleted]
- Leynos 10mo ago
  It's something of a thought terminating cliché in Hacker News discussions about large language models and agentic coding tools.
- mostlysimilar 10mo ago
  There are two camps who have largely made up their minds just talking past each other, instinctively upvoting/downvoting their camp, etc. These threads are nearly useless, maybe a few people on the fringes change their minds but mostly it's just the same tired arguments back and forth.
- hug 10mo ago
  Because in its brevity it loses all ability to defend itself from any kind of reasonable rebuttal. It's not an actual attempt to continue the conversation, it's just a semantic stop-sign. It's almost always used in this fashion, not just in the context of LLM discussions, but in this specific case it's particularly frustrating because "yes, you're holding it wrong" is a good answer. To go further into detail about the whole thing: "You're holding it wrong" is perfectly valid criticism in many, many different ways and fields. It's a strong criticism in some, and weak in others, but almost always the advice is still useful. Anyone complaining about getting hurt by holding a knife by the blade, for example, is the strongest example of the advice being perfect. The tool is working as designed, cutting the thing with pressure on the blade, which happens to be their hand. Left-handers using right-handed scissors provides a reasonable example: I know a bunch of left-handers who can cut properly with right-handed scissors and not with left-handed scissors. Me included, if I don't consciously adjust my behaviour. Why? Because they have been trained to hold scissors wrong (by positioning the hand to create opposite push/pull forces to natural), so that they can use the poor tool given to them. When you give them left-handed scissors and they try to use the same reversed push/pull, the scissors won't cut well because their blades are being separated. There is no good solution to this, and I sympathise with people stuck on either side of this gap. Still, learn to hold scissors differently. And, of course, the weakest, and the case where the snark is deserved: if you're holding your iPhone 4 with the pad of your palm bridging the antenna, holding it differently still resolves your immediate problem. The phone should have been designed such that it didn't have this problem, but it does, and that sucks, and Apple is at fault here. (Although I personally think it was blown out of proportion, which is neither here nor there.) In the case of LLMs, the language of the prompt is the primary interface -- if you want to learn to use the tool better, you need to learn to prompt it better. You need to learn how to hold it better. Someone who knows how to prompt it well, reading the kind of prompts the author used, is well within their rights to point out that the author is prompting it wrong, and anyone attempting to subvert that entire line of argument with a trite little four-sentence bit of snark in whatever the total opposite of intellectual curiosity is deserves the downvotes they get.

clownpenis_fart 10mo ago

[dead]

Garlef 10mo ago

I'm referring to these kind of articles as "Look Ma, I made the AI fail!"

falloutx 10mo ago
Still I would agree we need some of these articles when other parts of the internet is "AI can do everything, sign up for my coding agent for $200/month"

techblueberry 10mo ago

"They are not getting worse, they are getting better. You just haven't figured out the scaffolding required to elicit good performance from this generation. Unit tests would be a good place to start for the failure mode discussed." Isn't this the same thing? I mean this has to work with like regular people right?

data-ottawa 10mo ago

Needing the right scaffolding is the problem. Today I asked 3 versions of Gemini “what were sales in December” with access to a sql model of sales data. All three ran `WHERE EXTRACT(MONTH FROM date) = 12` with no year (except 2.5 flash did sometimes gave me sales for Dec 2023). No sane human would hear “sales from December” and sum up every December. But it got numbers that an uncritical eye would miss being wrong. That’s the type of logical error that these models produce that are bothering the author. They can be very poor at analysis in real world situations because they do these things.

khalic 10mo ago

I’ve seen some correlation between people who write clean and structured code, follow best practices and communicate well through naming and sparse comments, and how much they get out of LLM coding agents. Eloquence and depth of technical vocabulary seem to be a factor too. Make of that what you will…