Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

The short leash AI coding method for beating Fable

blog.okturtles.org

Post reply on HN
Print view View original

201–210 of 268 posts

Re: The short leash AI coding method for beating Fable

#201

Post by et1337 »

esperent wrote: post #174
chewbacha wrote: post #94

I did this for two weeks on a side project and still ended up in a situation where I did not have a mental model of the codebase. There’s no way build that model without building it yourself. I’m more convinced then ever of this.

If you were working as a manager on a large project, how would you build a model? Something where your position requires you to have an overview of the project but not necessarily to actually write or review much code.

I am not able to find it now, but there was an amazing story recently from the 60s or 70s where an engineer was in exactly this position. His team was building a new, complex, ambitious operating system, but it was late and over budget and didn’t work. It nearly wrecked the company. He talks about hitting rock bottom and asking himself what went wrong, and one of the fathers of computing (can’t remember which) shouts from the hallway in passing, “that’s easy, you didn’t understand what your people were doing.” So the guy turned it around by implementing a new rule: he had to understand every line of code his team wrote. They started over with the company’s existing OS in use by customers and implementing a few of the most requested features. Much less ambitious, but it actually shipped. Gradually they achieved all their goals by upgrading the existing system.

The “I must understand every line” constraint didn’t sound like a power trip that succeeded because the guy was such a brilliant code reviewer. I think it was a blunt instrument that enforced simplicity.

I guess what I’m saying is, I reject the premise of having technical oversight without writing or reading much code.

Re: The short leash AI coding method for beating Fable

#202

Post by densekernel »

visarga wrote: post #117
densekernel wrote: post #27

Earlier quoted context omitted.

I tend to agree, If you have invested significantly in the planning phase and there is momentum in the architecture and conventions that already exist in the project, the implementation phase might not need as much oversight as is suggested here. > You can discover that your initial idea was dumb and a better one exists The planning and architecture phase is usually where I make these types of discovery at a high lev…

I think the obvious solution here is to beef up the test side of the app, much more than when writing code by hand. Tests represent project knowledge in executable format. The LLM does not need to be careful to remember every detail of the tests. You don't need to vet every small interaction, it automates review work as well. Even better if the project was built from the start to be easier to test and observe. But my…

I agree, human-steered, AI-implemented test cases can at least capture the acceptance criteria.

It's then more efficient to inspect if existing test cases are being modified as part of the delivery of something new and inspect why.

Re: The short leash AI coding method for beating Fable

#204

Post by maccard »

solenoid0937 wrote: post #111
sixtram wrote: post #106

Earlier quoted context omitted.

You say you can have increasingly nuanced discussions with stronger models. What I say is, when I asked Claude why he applied a certain change I didn't understand, and boy, it was a small change, he said he "reasoned from first principles" based on the code paths. But it didn't work, and when I asked, "Okay, describe the steps of your reasoning from first principles," it literally answered that it had just made it up…

Posts like this are meaningless without more context - the model you're using, the harness, the initial prompt and context. Fable is better than most staff engineers at my FAANG.

> Fable is better than most staff engineers at my FAANG.

While this wouldn’t entirely surprise me, my experience is just not that. Using Claude and fable, it regularly (poorly) recreates features that exist inside our codebase. Sure, I could give way more initial context but at a certain point I’ve given so much context that I would have been faster writing the code myself, or I could have literally handed it to even a fresh graduate to write.

Re: The short leash AI coding method for beating Fable

#205

Post by sgarlatm »

jstrong wrote: post #50
steezeburger wrote: post #20

I find it hard to stay engaged doing this. I do get good results, but it's just hard to not get distracted when it's doing the work.

claude is so slow for interactive use like described, do people just run it in low effort mode or what?

I multi-task. While I’m waiting for Claude, I either check email or work with a different instance of Claude on a second problem

Re: The short leash AI coding method for beating Fable

#206

Post by pixl97 »

FeepingCreature wrote: post #200
spwa4 wrote: post #197

Earlier quoted context omitted.

Plus it's an open question if this is even a thing. Does consciousness consist of constructing actions beforehand, or of construction justifications afterward? Frankly, my opinion is that DNA is incredible at choose the most energy efficient/cheap option, and the cheaper option is definitely justifications afterward. I feel strengthened by psychological experiments where people are shown fake events involving them, w…

Sufficiently constrained post-hoc justifications are indistinguishable from explanations. Consciousness tries to make things up, it learns that people notice this, it then begins trying to construct justifications that won't be predictably called out as false. Eventually it learns how its unconscious operates, and how to interrogate it, and its post-hoc justifications, at least in the common cases, become reliable.

>Eventually it learns how its unconscious operates

I mean, no we don't, both in a personal way and in a global scientific understanding.

What you're saying happens is a set of socially consistent and acceptable responses based upon general human knowledge at the time. The common cases aren't exactly reliable, it's that they are repeatable in the sense they cover what we expect, and tend to explode when the world is less predictable.

This is why the scientific method changed the world, because we started writing shit down, comparing notes, and striving for repeatability.

Re: The short leash AI coding method for beating Fable

#207

Post by Marha01 »

esailija wrote: post #150
infinite_spin wrote: post #35

Earlier quoted context omitted.

> it doesn't mean it's intelligent I'm not sure how you're defining "intelligent", but I'd like to know how it is able to exclude a language model, while still including humans, without simply defining it with an axiom that predefines LLMs as lacking intelligence.

Intelligence is the complete opposite of an LLM. Usually the more you needed to memorize to do something the less intelligent you were considered. It was also not considered to be a different route to the same thing, but more like fraud. Also conceptually I could just write the weights on paper and do the billion multiplications on paper without any computer, does that mean I am the paper or the numbers or what??

> Intelligence is the complete opposite of an LLM. Usually the more you needed to memorize to do something the less intelligent you were considered.

Contrary to popular belief, training a LLM is not just about memorization (overfitting). There is some memorization happening, but well-trained LLMs also generalize.

Re: The short leash AI coding method for beating Fable

#208

Post by pixl97 »

sixtram wrote: post #154
doctoboggan wrote: post #122

Earlier quoted context omitted.

You can never ask why a model did a certain thing, or what it was "thinking" when it said something - just like you can't ask a human which neurons were firing when they had a certain thought. The information just isn't available at that level. You absolutely can have deep nuanced discussions with LLMs however, you just need to better understand their strengths and weaknesses.

So you're saying I can absolutely have a deep, nuanced discussion with an LLM, as long as I don't ask how he arrived at his conclusions?

>as long as I don't ask how he arrived at his conclusions?

So just the average US political discussion with a human then?

Re: The short leash AI coding method for beating Fable

#209

Post by atq2119 »

NitpickLawyer wrote: post #172
sn0n wrote: post #169

Earlier quoted context omitted.

Isn’t that part of what the think blocks are for? Yea, don’t inject them back into the context, but do log them for review of that train of thought… no?

You don't get access to the thinking traces. Might work with local models tho, but the current meta isn't particularly suited for this either, as it's a big blob of rambling surfaced by RL, with the "only" objective being that the thinking blob somehow leads to a better final answer. Something more detailed, using templates akin to oAI's harmony could work, provided there's also a step that teaches the models to refl…

That's true, but it does mean that the LLM itself actually does have access to those thinking traces and could therefore, at least in principle, answer what it was thinking. They're probably not trained to do that, though.

Re: The short leash AI coding method for beating Fable

#210

Post by [deleted] »

sixtram wrote: post #154
doctoboggan wrote: post #122

Earlier quoted context omitted.

You can never ask why a model did a certain thing, or what it was "thinking" when it said something - just like you can't ask a human which neurons were firing when they had a certain thought. The information just isn't available at that level. You absolutely can have deep nuanced discussions with LLMs however, you just need to better understand their strengths and weaknesses.

So you're saying I can absolutely have a deep, nuanced discussion with an LLM, as long as I don't ask how he arrived at his conclusions?

[deleted]
Post reply on HN