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Taste in the age of AI and LLMs

rajnandan.com

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Re: Taste in the age of AI and LLMs

#131

Post by CharlieDigital »

switchbak wrote: post #123
aaaronic wrote: post #70

Earlier quoted context omitted.

It does amaze me when colleagues refuse to read what I (personally, deliberately) wrote (they ask AI to summarize), but then tell AI to write their response and it's absolutely bloated and full of misconceptions around my original document. If they aren't willing to read what I put effort into, why should I be expected to read the ill-conceived and verbose response? I really don't want to get into a match of my AI ar…

I've been having ongoing issues with a manager who responds in the form of Claude guided PRs. Undoubtedly driven from confused prompts. Always full of issues, never actually solving the problem, always adding HEAPS of additional nonsense in the process. There's an asymmetry of effort in the above, and when combined with the power asymmetry - that's a really bad combo, and I don't think I'm alone. I'm glad to see the…

    > ...a manager who responds in the form of Claude guided PRs
I think the job of a dev in this coming era is to produce the systems by which non-engineers can build competently and not break prod or produce unmaintainable code.

In my current role, I have shifted from lead IC to building the system that is used by other IC's and non-IC's.

From my perspective, if I can provide the right guardrails to the agent, then anyone using any agent will produce code that is going to coalesce around a higher baseline of quality. Most of my IC work now is aligned on this directionality.

Re: Taste in the age of AI and LLMs

#133

Post by CharlieDigital »

subhobroto wrote: post #122
CharlieDigital wrote: post #11

> One of the most useful things about AI is also one of the most humbling: it reveals how clear your own judgment actually is. If your critique stays vague, your taste is still underdeveloped. If your critique becomes precise, your judgment is stronger than the model output. You can then use the model well instead of being led by it. Something I find that teams get wrong with agentic coding: they start by reverse eng…

> Instead, the right train of thought is: "what would perfect code look like?" and then meticulously describe to the LLM what "perfect" is to shape every line that gets generated. I don't think there's perfect code. Code is automation - it automates human effort and humans themselves have error, hence not perfect. So as long as code meets or exceeds the human output, it's "good enough" and meets expectations. That's…

    > I don't think there's perfect code
Note I used "perfect" in my text. In this context, meaning it passes human PR reviews following our standard guidelines with minimal feedback/correction required.

    > So as long as code meets or exceeds the human output, it's "good enough" and meets expectations. That's what a typical customer cares about.
Why settle for this when "perfect" is "free"? I understand this dichotomy when writing "perfect" code requires more expensive, more experienced human resources or more time so you settle for "good enough"; but this is no longer the case, is it? The cost of "perfect" is only perhaps a few fractions of a cent higher than shitty.

You only need to accurately describe what "perfect" is to the LLM instead of allowing it to regress to the mean of its training set. There really is no cost difference between writing shitty code and "perfect" code now; its just a matter of how good you are at describing "perfect" to the LLM.

For example, we very specifically want our agents to write code using C# tuple return types for private methods that return more than 1 value instead of creating a class. The tuple return type is a stack allocated value type and has a default deconstructor. We also always want to use named tuple fields every time because it removes ambiguity for humans and increases efficiency for agents when re-reading the code.

We want the code to make use of pattern matching and switch expressions (not `switch-case`) because they help enforce exhaustive checks at compile time and make the code more terse.

If we simply tell the agent these rules ahead of time, we get "perfect", consistent code each time. Being able to do so requires "taste" and understanding why writing code one way or using a specific language construct or a specific design pattern is the "right" way.

Re: Taste in the age of AI and LLMs

#134

Post by Jensson »

hellisothers wrote: post #117
arnorhs wrote: post #65

Earlier quoted context omitted.

The way I understood it, the original article is saying the _only_ remaining differentiator is taste and the comment you replied to is saying "wrong, there are also other things, such as effort". I don't necessarily interpret the comment you replied to as saying that "taste is not important", which seems like what you are replying to, just that it's not the only remaining thing. I agree that taste gets you far. And I…

Aren’t you just making their point stronger? Effort is what is being replaced here, with some taste and a pile of AI (formerly effort) you can go to the moon.

But you still need effort, its not only taste. "Only" means you can do it with no effort.

Re: Taste in the age of AI and LLMs

#135

Post by doctorpangloss »

adammarples wrote: post #120
lamasery wrote: post #98

Earlier quoted context omitted.

The joke is that the person "saying" this is wearing their "I'm a rational, independent thinker!" tech uniform (expensive Nordic outdoors wear, so practical, so smart, so active, Vimes' boot theory, et c, not like those clowns in business wear, I'm interested in practicality not signaling, that's why I'm spending so much money signaling so hard about how rational I am). They are visibly displaying a complete lack of…

Agree but arcteryx is from vancouver

The original article was written by an LLM.

Re: Taste in the age of AI and LLMs

#136

Post by skejeke »

lol the unfortunate truth is that hundreds of billions and trillions will be spent to learn a single truth: Taste cannot simply be bought nor can you bring products that add value into the world through sheer will of training machines.

Re: Taste in the age of AI and LLMs

#137

Post by ux266478 »

_2fnr wrote: post #48
DrewADesign wrote: post #35

Earlier quoted context omitted.

It’s not that straightforward. Art directors and designers get paid to visually communicate things the business wants to communicate— anything from brand vibes, to directing people to click on a “buy me” button, to the state of an interface. Most designers in tech companies aren’t even the ones that design things like branding — that’s done by specialists in extremely well-compensated studios, and corporate designers…

[flagged]

The job isn't about visual judgement, but composition. Judgement/taste is the responsibility of directors and executives.

Re: Taste in the age of AI and LLMs

#139

Post by skejeke »

monknomo wrote: post #79
andai wrote: post #52

Earlier quoted context omitted.

I think you're missing the point. Effort is a moat now because centaurs (human+AI) still beat AIs, but that gap gets smaller every year (and will ostensibly be closed). The goal is to replicate human labor, and they're closing that gap. Once they do (maybe decades, but probably will happen), then only that "special something" will remain. Taste, vision... We shall all become Rick Rubins. Until 2045, when they ship Ru…

do you need taste if you can massively parallel a/b test your way to something that is tasteful? say like you take your datacenter of geniuses and have a a rubin-loop supervising testing different directions. shouldn't that be close enough?

That approach leads you to products like instagram.

Re: Taste in the age of AI and LLMs

#140

Post by jdauriemma »

everybodyknows wrote: post #125
johnfn wrote: post #49

It is profoundly ironic that this article is AI generated.

Trying to bring my nose for AI up to standard -- care to share what you're smelling? For me it's: - Short, declarative sentences, stating grandiose yet vague claims, in a high school vocabulary: "Taste becomes useful when it moves from vibe to diagnosis." - Absence of references (let alone web links) to real-world examples. - Em-dashes, gone. No semicolons, but 23 full colons. As instructed by prompt?

To that I'd add:

* an abundance of ordered and unordered lists

* paragraphs are * _it's not X, it's Y_: "The goal is not to let AI choose for you. The goal is to build a sharper rejection vocabulary." "The biggest decisions are not formatting decisions. They are directional decisions."

* a lot of breaking up the prose, if you can call it that

* setup statement, then a colon, then a punchline: "AI and LLMs have changed one thing very quickly: competent output is now cheap."

AI-generated essays are listicles at heart

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