FinnLobsien

It doesn’t invalidate other parts of your point, but Warp is open source now.

I guess you're right that food is historically speaking extremely safe. I guess with this specifically, the issue is about how connected one company can be to the whole food supply.

A farmers market stand may not have perfect food safety either, but their outbreak would be limited to the few people who bought something on the farmers market (or maybe a cafe/restaurant or two that they supply).

Most likely, any harm wouldn't even be traced back to any individual salad because the sample wouldn't be big enough to form a pattern people would notice.

But because they supply so many salads to everywhere, it's a major issue that affects the whole food system.

I guess it's similar to an AWS outage. Companies constantly have outages, but an AWS one takes down half the internet.

I agree with you, but I also think sadly most consumers don't really care about this. The reason the internet is in the state it's in is because most people tolerate it.

Most people simply don't care about using well-made software so long as it gets the job done because they don't even look at other options. I suppose this is how carpenters feel when they see ubiquitous IKEA furniture.

Not a surprise this is launching now. John Ternus is taking the reigns as CEO in a week and was previously SVP of hardware engineering.

I can't hate a direction where Apple becomes more about building great computers rather than trying to force more and more subscriptions. I do wish they would fix many of the long-standing OS and native app problems.

Not a surprise with John Ternus taking the reigns as CEO in a week, who was previously SVP of hardware engineering.

I can't hate a direction where Apple becomes more about building great computers rather than trying to force more and more subscriptions. I do wish they would fix many of the long-standing OS and native app problems.

I agree that a lot of entrepreneurship is misguided. And I totally agree that research, charity work, or other stuff can have many of the same benefits.

What I think is important (and why I think entrepreneurship is directionally good) is open-ended exploration and taking initiative to pursue one's own projects. I don't care about the specific direction, but about the idea of proactively trying to shape reality by following one's interests.

I think what you're describing with backpacking is true for most. If the point is to check off a list of Instagram picture spots, then it's more of an exercise in consumerism. If it's to deeply engage with other cultures, languages, and people, that's different.

I guess it's similar with entrepreneurship. If the point is to inhabit the founder personality archetype you see on social media, that's different than to be genuinely solving interesting problems.

I think that undermines a lot of benefits of entrepreneurship - the learning of many different skills, network, etc. and also just the adventure of starting a company.

It’s like saying most people will never be professional athletes so we should discourage sports.

Or most people live in their home country, so we should discourage young people from taking backpacking trips.

I guess this is a question of what you believe code and software engineering writ large is for.

If you believe that good engineering practice matters (in the sense that your software is maintainable, efficient, etc.), then this is horrific because the human has no idea what’s going on and any attempt to fix something by hand would probably uncover enough complications to make you consider rewriting from scratch.

But if your only qualifier is “does it do what I want it to do?” then this is perfectly fine. If you throw out the assumption that a human will ever maintain the code or need to understand it, then who cares if your main branch is full of unused code and it’s outrageously complex.

In a way, I guess this is a similar moment to abstract painting in the early 20th century.

If your assumption was that the point of a painting is to accurately capture a landscape or person, then abstract paintings are an abomination.

If you believe paintings should evoke a feeling and depicting people or landscapes are only one way to get there, you can throw out all the sketching and composing and painting technique.

I think there are two things at work here:

-An expectation that because a scientist is incredibly good at one thing, they must be good at another, entirely different type of thing. This seems to uniquely apply to scientists.

We don't judge a phenomenal football player for not being an incredible archer, but then we do judge a Nobel prize-winning physicist for believing in astrology.

-I think this can sometimes be two sides of the same coin: The same divergent thinking that helps you make revolutionary discoveries (you're unwilling to take the status quo for granted) also makes you explore "strange" ideas.

Yeah exactly, I think the massive volume increase in content requires more aggressively filtering what you pay attention to. My tolerance for bad content has gone to nothing because the second I realize I can prompt the same article into existence except more personalized, I’m out - and the next time I see that company/person’s blog, I’m ignoring it.

Not everything made with some kind of AI assistance is slop, but all slop is made by AI.

I think there's a difference here between low-effort AI slop and something made with the help of AI. I always wonder how many AI images and articles we consume without realizing they were made by AI just because a human actually spent the time on making the AI create a good output.

I think this is extremely true when it comes to prompting, but not only in this way. I would add that this also applies to an LLM's output on deep enough topics.

Anyone can point at a public GitHub repo and have an LLM write the documentation for it. Whether that documentation is good requires understanding that codebase.

There's no way around expertise unless we're talking about strictly mechanical tasks.

I do think LLMs are incredible at helping to build your expertise. You could point it at a codebase and say: "Explain how this API works" and interrogating the LLM until you get an explanation at exactly your level of understanding.

But then what's the point of the proof? I guess it's cool that it's possible, but given enough tokens, you could take someone who's never written a line of code and have them prompt AI to turn their vibe-coded meal prep app into a highly available distributed system with multi-region failover and immutable audit logs.

They would probably get something that checks those boxes in one way or another, but what does it do for them?

I don’t see a world in which this doesn’t just annihilate the current market for books.

If I can write a query into Amazon for a book on topic X, I can write that query into ChatGPT or whatever and cut out the middleman.

Some of this may work in the short term while some people still equate the format “book” with “went through a rigorous process”.

That erosion was underway before AI (e.g. on Amazon I instinctually ignore any self-published Kindle books), but I can’t imagine this will last.

I think/hope the market will somehow make human-written books easy to recognize.

I guess this is a general problem where things that show you take initiative get converted into “thing to put on your resume”, and if that’s the primary motivation, you’ll do the bare minimum to check the box to put it on your resume.

Same thing happens to school extracurriculars.

I think much of this comes down to wanting to be a type of person vs. wanting to do the actual thing.

It’s easy to be consumed by “I’m the wealthy San Francisco founder guy” and doing everything that lifestyle requires, including things that may not be good for you.

I think this is intuitively true, and I've noticed this even as someone who doesn’t have an engineering background.

In my LLM coding experience, I’ve had this happen numerous times, for instance when building a card game.

The LLM does a great job for a while, but adding special event cards becomes impossible because it imported a standard 52 card deck library instead of having a flexible data model with card objects.

I suppose this is knowable and you could tell an LLM to do this from the beginning. It's just that when you view making a game (or any piece of software) as just a throwaway thing and don't start with deep thought about the implementation as an experienced engineer might, you don't think about this.

I think part of the issue with AI-generated writing, code, or anything else, is that it robs us of the thinking that used to be baked into the process of making stuff.

For my game, if I had to build it from scratch, I surely would've sketched out the kind of data model it requires to not waste my time.

I do think some of this stuff is overblown though. It's true that LLMs don't create production-grade stuff, but not all software needs to be scalable, fast, and easily maintainable.

This might be required for infrastructure or apps designed to (hopefully eventually) be used by millions.

But it's not true for a minor utility, like if I want to build a meal-planning app for my family. I don't care if the app is the fastest it can be or if the data model could eventually support a feature to configure dietary preferences and allergies or to plan the meals for Google's tens of thousands of employees.

There was a viral article a few years ago around how software could be like a home-cooked meal. And AI enables exactly that. A home-cooked meal doesn't require culinary perfection, but to feed the family and, maybe more importantly, be a gift of labor to the other person.

I totally agree with this when it comes to skill acquisition and deep expertise, which I care about more with skills than whatever rewards I might get for that expertise.

It's just important not to conflate this deep expertise with the milestone you need to get a job or something. Especially when combined with expertise in other fields, even very little effort can let you advance a lot.

It's not if you use it correctly. If you say "Find me good brands for X", then yes you'll get bad stuff.

I said something like:

"Identify [category]-making cluster regions in Europe (where I am), research the manufacturers/companies you find and see if they have online stores."

Once I had that list and found stuff I liked, I sent what I liked back to the AI and asked it to find me items of comparable build quality from better-known brands."

I did this latest step so that I could have a benchmark and to see if I was actually getting a better deal or if I could just buy from the big brand.

The trick was to specify the exact process I'd like to have run, but wouldn't take the time to do.

I ended up buying stuff directly from an obscure manufacturer's Shopify store for 1/3 the price I would've paid at a big brand. I think this could work in any product category where quality markers are somewhat objective and standardized.

Yeah it's quite interesting how most of the decline of great brands came as a result of ownership changes, not complacency on part of the owner/founder.

I've actually found AI a great resource for finding brands that offer great value for money by buying from obscure factories/brands with the same quality attributes as major brands, but without all the marketing spend and brand margin to subsidize.

I wonder if there’s an inverse of this: brands that actually got better over time because they don’t have massive brand history to fall back on, or simply because they actually care.

Yes, and I even think this applies to generally valuable skills.

I can be really good at organizing projects, but I shouldn’t channel that into spending hours creating the perfect Jira template with 18 integrations just because I can do it well because that’s a lot of energy spent on something nobody may ever use.

Meanwhile that skill may very well be extremely valuable elsewhere.

Possibly, but I think it’s a bit more intuitive than that. It’s basically just like companies with terrible websites:

Most of them are terrible because they no longer exist, have no budget because they’re not making money, or because they’re bad at doing things generally.

But then there’s a set of companies that do fantastically well and are so busy serving customers (or are satisfied with their results) that their website doesn’t matter. In that case, the bad website is an indicator for a good product.

True! And the point isn't that you shouldn't base whether you do something on how much economic value it produces.

I think the judgment is more that if you're doing something to produce some kind of outcome (e.g. work), don't get stuck on things that don't impact that outcome.

The point isn't that you shouldn't do things well. It's that just because AI makes it effortless to ship some random new thing nobody asked for, that doesn't mean you should ship it.

I think that calculus changes completely when you do things for fun, where the only outcome you're trying to produce is doing more of the activity.

If you're doing something for fun, the doing is itself the reward.

> Technology was supposed to make room for life but instead for more and more people life is slowly being rearranged around AI. People fear being replaced by machines and respond by giving those machines more of their judgment, attention and time. And for what? Every “saved” hour is returned to a race with no finish line.

I think this is true. I've recently heard Tim Ferriss say: Just because you can do something well doesn't mean it's worth doing.

This is so true with AI. You can do a lot of things with AI, but that doesn't automatically make them worth doing. Anything multiplied by zero is zero. If the benefit of something is (effectively) zero, it doesn't matter how low the cost is.

AI isn't useless and there are beautiful, enriching use cases for it. But the idea that AI must consume our lives so we don't get left behind by those who brag on LinkedIn about operating 12 concurrent agents in self-perpetuating loops seems faulty to me.

I've come around to the other side of this in a way. I used to think "wow they don't care at all" the same way I previously looked at menus clearly made in MS Word: The place will probably be cheap and they don't care about having fancy menu design.

From there, it's two possibilities:

-They care about the food at the expensive of design and it's going to be cheap and great (good) -They care about the food as much as the design and it's going to suck (bad)

This switch happened after a new place opened in my neighborhood that had AI signage and is now my favorite lunch spot.

Yes! It has all the polish and flourish of something that has all the finishing touches, but none of the underlying structure your brain infers it to have due to its polish.

Sure this is true. And if an AI draft helps in creating quality writing, great!

I was thinking more when it comes to stuff other people send me (like a freelance writer) and “editing” is basically writing the first draft because no cognitive effort has yet been spent on the piece

Yes some parts of that are easier with AI, but I think comparatively to other activities, architecture is much harder.

And I also think what you describe is true in some contexts where you know exactly what you’re after.

You also don’t make architecture decisions in a vacuum, so the decision others make also affect you and you need to sell your decisions to others.

I think the bigger issue in defining this is that “programming” is too big a task to say whether it got easier or harder.

Some YAML formalities now take zero effort while architectural thinking became way more important and difficult.