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The rise of judgement over technical skill

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Re: The rise of judgement over technical skill

#31
post #13

Human judgement is like a house built on sand, it is basically provably feeble [0]. I've literally never in practice seen a human update their beliefs using Bayes' formula. I suspect we'll find that at some point fairly soon AIs will just have better judgement than us because they can be programmed to incorporate formal statistical concepts while humans have to rely on evolving grey goop which we haven't quite master…

Humans may not update like Bayesians, but we read context, shift priorities, and act under pressure. Judgment isn't just math — it's lived experience, intuition, and meaning in motion. That’s still hard to replicate.

Re: The rise of judgement over technical skill

#33

I would argue that this is already true in roles where one supervises the work of another person with skill. Great leaders, for example, were once practitioners. Over time their skills may fade, but their judgment makes them effective and able to the scale their impact.

In software, we promote good engineers to management, effectively accelerating the Peter Principle.

It doesn't have to be that way. Management skills are not an outgrowth of the skills of the managed, but orthogonal to them. This is similar to the lesson many PhD candidates I've known learn: expertise in their field is not pedagogical expertise. Companies who promoted from within used to provide training for new managers.

Re: The rise of judgement over technical skill

#34

This blog post shows how not to use AI. The author would have been unlikely to write such a uselessly redundant conclusion if they had to type it themselves. Edit: I like the post, but it didn't need to be padded with fluff.

We shouldn't be too quick to jump to "AI did it." People write redundant paragraphs and sentences in articles all the time because they're led to believe that every article needs a conclusion that sums up what's already been said. Ironically, including one in this article showed a lack of good judgment, which isn't confined to AIs.

Re: The rise of judgement over technical skill

#35
post #6

This echoes my experience with Claude Code. The bottleneck isn't the code generation itself—it's two critical judgment tasks: 1. Problem decomposition: Taking a vague idea and breaking it down into well-defined, context-bounded issues that I can effectively communicate to the AI 2. Code review: Carefully evaluating the generated code to ensure it meets quality standards and integrates properly Both of these require d…

I want to add something to this which is rarely discussed.

I personally value focus and flow extremely highly when I'm programming. Code assistance often breaks and prevents that in subtle ways. Which is why I've been turning it off much more frequently.

In an ironic way, using assistance more regularly helped me realize little inefficiencies, distractions and bad habits and potential improvements while programming:

I mean that in a very broad sense, including mindset, tooling, taking notes, operationalizing, code navigation, recognizing when to switch from thinking/design to programming/prototyping, code organization... There are many little things that I could improve, practice and streamline.

So I disagree with this statement at a fundamental level:

> The technical skill of writing code has been largely commoditized (...)

In some cases, I find setting yourself up to get into a flow or just high focus state and then writing code very effective, because there's a stronger connection with the program, my inner mental model of how it works in a more intricate manner.

To me there are two important things to learn at the moment: Recognizing what type of approach I should be using when and setting myself up to use each of them more effectively.

Re: The rise of judgement over technical skill

#36

A similar debate has happened in education where people seem to think that having ability to critically analyse texts is more important than knowledge. and to some degree that’s true but personally I think that without building on some decent level of foundational level of knowledge and having a mental model of a subject, you can’t tackle thorny questions because you don’t have enough to draw upon as examples and cou…

Reminds me of that concept that I saw pop up in HEP in recent years between "users" and "experts".

This distinction in that case is so dumb I cannot wrap my head around it: You first encounter the code, are unfamiliar with it but very quickly you become expert in order to solve your problem and advance the thing forward.

It does not matter which codebase you start on, what matters is that you understand what the actual stack does and what is involved in there because people are supposed to understand deeply what they are doing.

But this comes from the "corporatisation" of every single entity, where random metrics are used in order to assess performance instead of asking the simple question of "does it work" or "does it need fixing" or "will this thing break".

There is a clear disconnect between the manager type people that are removed from the work and the managers still doing things practically, which understand what the stressors are and where some work of deep understanding and extra contextualisation of the systems, is required, in order to not mess the whole thing up.

This being said, this is coming from a very peculiar perspective and with a very specific tech stack which is and is not industry standard at many levels...

Re: The rise of judgement over technical skill

#37
AI works great for providing you a starting point, and giving a big picture view of how certain things work, and how you should structure them.

Sometimes, even if you're a really seasoned software engineer, you'll encounter something you haven't seen before. Maybe to the point that you don't really even know what to search for to get started. So instead of spending half a day scrounging various forums, e-books, etc. you can ask the model, in somewhat vague terms, what you're looking for - and some of the LLMs are quite good at just that.

Now, the implementation of such things, not quite there yet. My experience has been that the more obscure the problems you deal with, the more obsolete code the model will spit out - with dead and unsupported libraries etc.

Re: The rise of judgement over technical skill

#38
post #32

The problem is - you can't judge if you're not skilled. So still, get skilled. Learn everything first hand. Try to master it. That's how our species prevailed in the first place.

CERT advisories are evidence that skill is necessary but insufficient. There’s a lot of code. We get ping ponged between various sections of the code every few weeks. Other people are contributing. There’s a ton of ways code can look like it’s probably correct and not be. There are non obvious bugs everywhere, and there’s an element of luck to whether you’re in the right headspace to catch them all.

Re: The rise of judgement over technical skill

#39
AI enables me to gold plate _everything_ I do, which feels exhilarating, if a bit exhausting. Having decent taste and being able to continuously test and verify my work allows me to smooth over the occasional hallucinations and elicit towering, mind-bending solutions.

AI's no replacement for experience; garbage in-garbage out.

When AI gets too good, I figure people will cloister to stop feeding the beast. It can only lead to ignorance and misery, I fear.

Re: The rise of judgement over technical skill

#40
This reminds me of Asimov's Jokester story where the same themes are explored - there is an all-knowing computer but someone needs to ask the correct questions.

"Early in the history of Multivac, it had become apparent that the bottleneck was the questioning procedure. Multivac could answer the problem of humanity, all the problems, if it were asked meaningful questions. But as knowledge accumulated at an ever-faster rate, it became ever more difficult to locate those meaningful questions. Reason alone wouldn't do. What was needed was a rare type of intuition; the same faculty of mind (only much more intensified) that made a grand master at chess. A mind was needed of the sort that could see through the quadrillions of chess patterns to find the one best move, and do it in a matter of minutes."

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