atomicnature's comments

What's the difference as you see it?

If you read the article carefully -- I've dealt with an alternative scenario as well -- where we may have smaller codebases with larger blast radius.

As to disposable software, it's harder to get traction/adaption when things constantly break or are slow or the experience is crappy in general.

To make it simpler - all else being equal - as a user would you prefer using highly reviewed/vetted/reliable software, or otherwise?

My bet is reliability is an invariant -- nobody wishes for software that crashes, leaks your private info, gives faulty output, is laggy to use and so on.

Try git-lrc, totally free since it uses gemini key. Triggers reviews automatically on git commit.

Specification languages need big investments essentially - both in technical and educational terms.

Consider something like TLA+. How can we make things such as that - be useful in an LLM orchestration framework, be human friendly - that'd be the question I ask.

So the developer will verify just the spec, and let the LLM match against it in a tougher way than it is possible to do now.

AI code review has genuinely helpful - especially when we generate code with copilot, etc.

Many times, these GenAI tools can delete/modify code mistakenly.

I use LiveReview's git precommit features - so the review happens right before I commit code automatically. And it has saved me many (100s of) times.

Give LiveReview's Precommit checks a try.

Go concrete. In FAANG engineering jobs now what % is this factory designer category vs what % is writing some mundane glue code, moving data around in CRUD calls, or putting in a monitoring metric etc?

Once you look at the present engineering org compositions see what's the error in thinking.

There are other analogy issues in your response which I won't nitpick

I don't agree with the limited point about fast fashion/enthittification, etc.

Quick check: Do you want to go back to pre-industrial era then - when according to you, you had better options for clothing?

Personally, I wouldn't want that - because I believe as a customer, I am better served now (cost/benefit wise) than then.

As to the point about recursive quality decline - I don't take it seriously, I believe in human ingenuity, and believe humans will overcome these obstacles and over time deliver higher quality results at bigger scale/lower costs/faster time cycles.

Where have I said engineers/architects aren't necessary? My point is that it is easier to get AI to get better than try to improve a million developers. Isn't that a straightforward point?

What the role of an engineer in the new context - I am not speculating on.

This is the "artisanal clothing argument".

I'd think there'll be a dip in code quality (compared to human) initially due to "AI machinery" due to its immaturity. But over-time on a mass-scale - we are going to see an improvement in the quality of software artifacts.

It is easier to 'discipline' the top 5 AI agents in the planet - rather than try to get a million distributed devs ("artisans") to produce high quality results.

It's like in the clothing or manufacturing industry I think. Artisans were able to produce better individual results than the average industry machinery, at least initially. But overtime - industry machinery could match the average artisan or even beat the average, while decisively beating in scale, speed, energy efficiency and so on.

It was available earlier. Here's the HN history:

https://hn.algolia.com/?query=Chomsky%20and%20the%20Two%20Cu...

The oldest submission is from 15 y.o ago - that is 2010.

I resubmitted it - thinking - with the success of LLMs - felt this was worth a revisit from "how real-world scientific progress works" point of view.

You can look into Judea Pearl's definitions of causality for more information.

Pearl defines a ladder of causation:

1. Seeing (association) 2. Doing (intervention) 3. Imagining (counterfactuals)

In his view - most ML algos are at level 1 - they look at data and draw associations, and "agents" have started some steps in level 2 - doing.

The smartest of humans operate mostly in level (3) of abstractions - where they see things, gain experience, and later build up a "strong causal model" of the world and become capable of answering "what if" questions.

Only one thing comes to mind:

The species as a whole will evolve inevitably; the individual animal may not.

Leslie Lamport built latex, most of distributed systems such as AWS services depend on formal verification. The job of Science here is to help Engineering with managing complexity and scale. The researchers are doing their jobs

Why do you think developer enjoyment is orthogonal to productivity and delivery?

Willful ignorance is a different process. Consider a food analogy.

Of the food we take - cells accept a % of it as nutrients and such, rest is discarded as waste. The cells know how to get this job done - it's a very complex process for sure.

I think it's the same with information content - a % actually is useful for making life happen - whereas the rest should ideally be discarded because it is meaningless from a life perspective. The mind just knows what's important most of the time.

In this case - willful ignorance would be something like intermittent fasting or regulating food intake carefully, since it is a conscious process.

The former process is unconscious and operates at the "cell level" whereas the latter is a conscious process that operates at the "whole-being" level.

1. The survey seems limited to UK or so. Not sure - it doesn't look like a global report.

2. Don't confuse "enjoyment" with "number of readers". The previous generation may have enjoyed it more - because there were no better options.

3. People over the globe are more educated now, and engaged in knowledge work. They must read to get work done.

4. Don't forget the "pirate book" scene - such as lib gen, Anna's archive, etc. - in developing countries.

Book sales in general (across all formats) are up I think - so there are still many, many readers around. We just have many new formats (EPUB, audiobooks, reader devices, etc.) and of course population is increasing over the globe. I'm pretty sure we have the highest number of readers on the planet right now than ever before in absolute terms.

Will this be open source?

You seem challenged with having a basic discussion without resorting to baseless personal attacks. HN discussions have nosedived in quality over the time. Feel like I'm on reddit.

On the topic - here were my original points (with some extensions):

1. I want a smalltalk-like environment but with modern languages (webassembly makes this technically possible)

2. Alan Kay himself agrees smalltalk is no longer relevant in a concrete manner anymore - it's too old and outdated. The library support is absymal, and LLMs etc won't be as helpful as modern langs, since the training data available is less in quantity and quality. And I am in line with Dr. Kay's view - Smalltalk is indeed too old. I feel the same way about using Lisp for my particular goals.

3. I am not complaining in any way - just stating my requirements in explicit terms. Also I dont consider myself a "user". I am a system builder. I am fully capable of doing things myself if there's no alternative available.

I've seen this already - but Lisp seems a bit limiting. I'd have loved to use Py/Go or JS in the least - something more upto date.