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Also, even though it called itself purely object-oriented, the earlier versions lacked inheritance.

Nowadays object oriented programming is almost entirely associated with inheritance hierarchies.

Perhaps inheritance isn't as central to object oriented programming as initially envisioned.

For a long time Guido wanted CPython to remain simple, as the reference implementation.

Probably also during the 2 to 3 migration, but that goal appears to have now been abandoned.

I wonder how the authors of other implementations like pypy will be able to keep up as the reference implementation becomes more and more complex.

How I've done it is to use some kind of observer pattern, where you register listeners to state changes.

Whenever state is updated, the listeners are all called with the updated state and can update the UI and what not based on the new state.

I haven't profiled this and compared it to frameworks, but feels adequate for the relatively simple UIs I've done.

On Margaret Hamilton from Chapter 5 of Hackers by Steven Levy

"She was well aware of the hackers’ playfulness around the ninth floor, and she was moderately friendly with some of them, even though they would eventually blend into one collective personality in her memory: one unkempt, though polite, young male whose love for the computer had made him lose all reason."

> I'd rather my language surface problems at compile time (via type errors) for all possible code paths rather than a particular codepath at runtime.

The kind of problems caught by compile time type checking are less fine grained than those that can be caught at run time. For more exploratory programming, one would prefer the latter.

At compile time, one checks that they are passing around correct types, at run time, the actual logic of the program is exercised.

Awesome! thanks for sharing these :)

Right, I get it.

People tend to underestimate to what extent pre-LLM programming experience contributes to their ability to steer LLMs in the right direction and produce decent results.

In 5 to 10 years, we'll see what kind of engineer is produced from pure LLM steering without years of hand coding experience. Even many of the more experienced ones would have some of this skill atrophied.

Presumably a DSL would allow you to do more heavy lifting in your specific domain with less tokens.

Let's way you wanted to do a web application using LLMs. Using a web framework would cost less tokens than using the vanilla underlying language (Python, PHP, whatever..), which is again way less tokens than building up from assembly (an LLM should be able to do this given enough time and compute).

Makes sense.

Why not let the shell do the expansion of `somedir/*` to refer to the content of the directory instead?

Running a company is hard work. If the current leadership in these companies cannot act responsibly, they need to make way for leadership that can.

There are many companies that compete but are careful not to break laws or cause obvious harm.

Why should a billion-dollar funded corporation still want to externalize the costs of its actions?

So perhaps the news here should be that OpenAI didn't take security seriously in their experiment, rather than the narrative that AI agents are a looming danger to the world.

As heavily funded as the top AI startups are, how is it that they cannot fill every single role with the best expertise available?

Is tech hiring so badly broken? Or do they have such broken processes / misaligned incentives that even people who could be doing a better job in these companies are unable to?

Also, was something lost in the transition from the traditional 'sysadmin' role to 'platform engineer' in the 'cloud native' environment?

If humans were directly making these attacks law enforcement would already be onto them. But because the humans routed these attacks through AI agents, it only makes news and contributes to AI hyperbole.

One thing that is common about middle democracies is that prioritize a bureaucratic elite structure over an entrepreneurship culture, while both the US and China embrace entreprenuership wholeheartedly.

If they changed that they'd perhaps become world powers themselves.

As more people start using AI for research, they'll probably adopt AI'isms in their writing too, even if they don't use AI itself to do the writing.

Subconsciously we all pick up patterns that we regularly encounter.

Yet as a programmer myself, I've been in situations where I'm artificially separated from the customer against my will.

I want to build something useful for them but if they let me be too close to the customer, I'll be making important decisions that are supposed to be someone else's job.

> Did you enjoy the crafts, or did you enjoy the compliments? Did you enjoy the difficult puzzles or the identity derived from a career that gives you the reputation and perceived value of someone who can do a thing most people can’t?

I think in the end everyone will be happy. Those who just want to ship, make money and attain status and do not care much for the process will embrace whatever capabilities AI affords them and move on.

Those who get satisfaction from the process and prioritize craftsmanship will also do so and form their own subcultures where this is appreciated.

If software is eating the world as some say, then surely, there can't be just one way of doing software.

Whole civilizations fell when people forgot how to do important things

> Even better, discovery was through human recommendations rather than algorithms designed to keep you hooked on the platform.

Yeah, that's one thing that is definitely noticeable. Online social services basically became data-driven psychology research companies, with the goal being to improve engagement. Every page refresh became an A/B test designed to keep you hooked.

Sometimes I wonder what the tech ecosystem would look like without the ZIRP era.

I look back over 15 years and with the exception of increased smart phone usage, everything else still looks mostly familiar. Maybe a bit more slick, but also slower and buggier despite having much better hardware.

There hasn't been a qualitative leap in software (as was in the 90s). Just larger SaaS companies. Without ZIRP would it have been any different?

I don't think this is a counterpoint.

An established codebase is already the best kind of context you could give an agent. It has all the patterns baked in so the agent simply follows established patterns. Such a codebase probably contains tens to hundreds of thousands of man-hours poured into it by humans refining it to do what it does - taking into account real world feedback and constraints.

When working on something from scratch, the best an agent can do is the average of whatever is in its training set and the clarity of the text prompts.

> they launched Brave Orion

I think you mean Brave Origin. It's the minimal version without the extra services. Free on Linux and purchaseable on other platforms.

I think that's a fair compromise, since the company needs to somehow make money.

It's been working great for me as the primary browser for a couple of years now.

Prior to that I was on Firefox (for the sake of browser engine diversity) but left as soon as they announced they were turning into an AI powered advertising company, and would use your data for training. However, I keep it around for cross-browser testing.

Perfectly fine for personal servers that matter. Its better IMO to risk having a rare breakage than to stay behind security upgrades.

Experts don't want to 'gatekeep'. Experts have been producing FOSS for the benefits of everyone, and liberally answering questions on mailing lists, stack overflow etc for free.

Experts have been badly bitten by poorly written and badly architected software, lost their hairs trying to figure out bugs and poor design.

They recognize the first version of a piece of software is only a miniscule percentage of the work and majority of effort goes into maintenaning it for its lifetime.

They are viscerally horrified at a thousands of LoC codebase generated at the speed of GPU inference they are to be responsible for.

Explain why you think it's a myth. Also I'm basing my argument on common sense. And I didn't speak about my 'world view' in the comment.

Exactly. Henry Ford made sure his own employees could afford the cars they were making.

These people making these kind of grand pronouncements either have an embarrassing blind spot, or are not making sincere, but carefully calculated statements.

Just via competition, Chinese researchers are doing much more than Bill Gates could ever hope to do through 'thought leadership' spread the benefits of generative AI.

US investors are desperate for the next hypergrowth opportunity. From what I can tell the US economic strategy is to outgrow its debt.