dvt

This website doesn't "teach" anything. It's a fun way to explore and get exposed to history. Kind of like Civilization 6 or something. Do you think CIV6 "teaches falsehoods" because you can build the Pyramids as the French?

This is such a weird nitpick, it's clear the website deals in averages and assumptions. It's meant to be an interesting window into possible lives intermixed with historical happenings at, or around, those times.

I get that some people just hate AI, but of all things, this is a pretty fun & educational use of it.

You are technically correct, but Verisign billed buying an x subdomain as if the y domain was part of a stable infrastructure. Which it kind of was until they decided to pull the rug.

I freaked out for a second because I've owned `dvt.name` for like 15 years. `.name` is not getting terminated, so it's important to be precise here. The third-level x.y.name (where you're the `x`) is getting terminated, and the respective `y.name` domains are going to be released.

Still a crappy thing for people, but it does not affect owned second-level domains.

Honestly, combat & movement feel pretty good and and it's very comparable to what a normal engineer would put together after 6 weeks. The hard part, when making games at least, is figuing out what makes things fun and (more specifically when it comes to RPGs) how to do the scaling. Both of these are pretty hard and require a ton of experimentation.

Since it's vibe-coded, I was really hoping to see some AI-generated storylines (turn `go to <x,y> and do z` into a fun quest) and more worldbuilding. AI is surprisingly good at generating passable prose, certainly comparable to a middle-of-the-road RPG.

I did the exact same thing[1] (minus the AI matching)—in fact, using the public HN firebase API, as you can see. So I fundamentally reject this premise. I had it running for years and no one complained and it scored me a few contracts because I also did a "Show HN:" and some folks liked it.

[1] https://github.com/dvx/hackjob/blob/master/assets/app/compon...

> this is creepy AF and feels like a giant invasion of privacy

People have been building HN job listing scrapers for years. Heck, I built one over a decade ago[1] (though it's offline now). This is a very common "Show HN:" project, and the argument that it's somehow bad faith and creepy is just absolutely nuts when posting on a public forum, specifically to get more exposure.

[1] https://github.com/dvx/hackjob

This is neat! What I would do is I would have a list of tags and make sure every post gets pigeonholed into those because otherwise it might be hard to match tags if extracted on a per-post basis (e.g. I see `large-scale data systems` for a job listing, which will rarely match a candidate because it's so wordy).

Cool product though.

Zitron is an AI doomer and a clear fact-distorter. I follow him because even a broken clock is right twice a day and I do think he's a pretty smart guy. I don't read his newsletter (it's basically word vomit these days), but his interviews are marginally interesting. One of the quotes in the linked article is totally correct:

> He found a niche in anti-tech grift, and is now exploiting the niche for all he can.

> hackers, for one

Got it, sooo.. SF tech bros. I think that humanoid robots are interesting but the real innovation and product-market fit will come figuring out how to do menial household chores (folding clothes is still very much unsolved, for example) as opposed to an ultra-generalized robot that can "do anything."

Skeuomorphism is back, baby! Apart from the wonky dragging on some of the knobs, I really like these. Kind of reminds me of teenage engineering.

Neat vision, but I can only imagine this thing literally fucking everything up. Like, knocking shit off my table, setting my kitchen on fire, bumping into things like an idiot.

Not sure who the market is here apart from SF tech bros with money to burn.

Location: Los Angeles

Remote: Yes

Relocation: Case-by-case

Hi HN, I'm an engineer and data professional interested in team-building, consulting and architecting data pipelines. At Edmunds.com, I worked on a fairly successful ad-tech product and my team bootstrapped a data pipeline using Spark, Databricks, and microservices built with Java, Python, and Scala.

At ATTN:, I re-built an ETL Kubernetes stack, including data loaders and extractors that handle >10,000 API payload extractions daily. I created SOPs for managing data interoperability with Facebook Marketing, Facebook Graph, Instagram Graph, Google DFP, Salesforce, etc.

More recently, I was the CTO and co-founder of a crypto gaming startup. We raised over $6M and I was in charge of building out a team of over a dozen remote engineers and designers, with a breadth of experience ranging from Citibank, to Goldman Sachs, to Microsoft. I moved on, but retain significant equity and a board seat.

I am also a minority owner of a coffee shop in northern Spain. That I'm a top-tier developer goes without saying. I'm interested in flexing my consulting muscle and can help with best practices, architecture, and hiring.

Would love to connect even if it's just for networking!

Website: https://dvt.name/ (under construction)

GitHub: https://github.com/dvx

Email: [d]@[dvt].[name]

You could make the converse argument, too: why don't you borrow and leverage and bet and short these AI companies, if you so vehemently think it's a bubble?

The bottom line is that markets are complicated, useful technologies are often accompanied by bubbles, investors are not always rational, and people generally try to make the best decision with the information they have available. The answer is likely somewhere in the middle, but that's a lot more boring and a lot less inflammatory.

You don't, that's why you review it (just how you would handle a real human submitting a paper). The main issue with LLM papers is that they tend to be very dense/circuitous or—because LLMs don't truly understand what they're doing—have the wrong focus. An LLM might spend pages on a trivial result, but quickly gloss over a truly remarkable finding.

Terry Tao talks about this challenge in some of his blog posts and interviews, it's pretty interesting.

What? Not at all. I'm referring to things like discussing distributions of certain things or probabilities of things as we go towards infinity, etc. These are proper papers, not surveys.

Not sure how much frontier math you follow, but probabilistic arguments are extremely popular (particularly in, weirdly enough, number theory), especially for fiddling with the bounds on things, or getting closer to full coverage of various theorems.

So this idea that doing math is some kind of fully deterministic & mechanistic process is a bit misleading.

Have mathematicians become "less savvy" since the invention of the abacus or calculator? The invention of logarithms or analysis? In some ways, the answer is trivially positive. In fact, number crunching was, for most of human history, a key element of being a maths researcher.

However, when we look at the claim with a more critical eye, it becomes obvious that this view is myopic. In fact, current progress is in fact indebted to the invention various tools, which has led us to grand theories and hypotheses: things the Ancient Greeks could only dream about.

Is coding about writing assembly? Is it about writing boilerplate? About writing endless if-then statements? I would argue that it is not: it's about coming up with ideas, building products, finding customers, iterating, producing code that's easy to read, easy to understand, easy to extend.

Coding (at least the kind LLMs do) was never really the hard part, and I'd like to know specific examples of savvyness the author is losing. They've made me more critical of code and able to create better patterns, simply because I can iterate so quickly.

One of my engineering highlights was Russ reviewing a few of my contributions to Golang (to the core http library). He's a super cool and nice guy. I don't really write that much Go anymore, but it was a fun & cute language when it first came out.

> It's not being shipped.

What are you talking about? I'm running 1.4 canary (the Rust rewrite) right now.

    λ bun --version
    1.4.0

Hope that helps.

First of all, I'd need to see a diff on that. It's insane to make that kind of claim without backing it up. Second of all, dead code (as in truly dead code: like an if statement that is guaranteed to never be true), is optimized away by the compiler. So even if we had all this dead code, it is not an issue that would ever impact the final product. Third of all, the Bun runtime consists of over a million lines of code, so that figure (again, even if true) is insignificant.

> The last three months have not looked good for Bun.

Apart from pro-AI or anti-AI posturing how have the last few months not looked good for Bun, exactly? I use it daily and I've seen basically zero regressions. I get it, you don't like AI or you like Zig over Rust, or whatever. I just haven't seen any serious argument that Bun has somehow become worse software.

> The project has over 5k open pull requests, which is the largest number of pull requests I’ve seen.

Terrible argument, and not really an argument at all.

> The biggest worry is, of course, the code itself.

I agree, so look at the code and point out what's wrong with it.

Insofar as Andrew Kelley is concerned, it's obvious he has an axe to grind and is salty about Bun embarassing Zig (which he freely admits). Not sure why you'd invoke an unreliable narrator as some sort of final nail in the coffin.

> There are also, of course, trade secrets, but if you didn't surreptitiously gain access to the information and didn't sign any NDA, that's not something you have to worry about.

But this is precisely the context of the original webpage: someone writing code at your company and your company not having copyright of that code. Almost everyone that works for any tech company signs an NDA, and code in private repos is just that: private. So even if said intellectual property (AI-written code) is not copyrightable, it's still a trade secret.

This is doubly stupid because I've worked at plenty of companies where we would routinely generate code (using macros or transpilers, or what-have-you), and that code is also not technically copyrightable.

Intellectual property does not necessarily have to be copyrightable but, as always, nuanced discussion will get lost in clickbaity headlines.

It's not hard to sell a dollar for 50 cents. Imo, these businesses are pretty clearly not doing well financially (the revolving door of unvested C-levels is a good hint, the constant postponing of S-1s is another).

> This sure looks like a race to the bottom

Always has been. My prediction is that both OpenAI and Claude will go bust unless they deliver a killer product. And unlike scrappy startups, they have a pretty serious deadline because creditors will come a-knockin'.

There's little to no functional difference between Kimi, Qwen, Sol, Opus, etc. All flagship models are within like 1-5% of each other and the real moat will be what's always been the hard part: making a good product.

> Boilerplate is a sign of a bad language

This is true, but I was mostly referring to framework boilerplate (Spring, React, etc.) or plumbing boilerplate. If you've ever written code professionally, you know that most code that you write is just making your thing fit with someone else's thing.

If your consumer or your provider made bad engineering decisions, you have to absorb them. If your company mandates the use of a framework, you have to absorb that, and so on. So I think it's great that AI can write all the dumb shit I didn't come up with anyway.

> Are software engineers really so full of hubris that they thought coding is all that there is to making a product?

Frankly, this barely scratches the surface of the hubris of engineers. I personally think AI has been one of the best things to happen to software engineering. Writing boilerplate or my millionth auth implementation was never why I fell in love with the craft in the first place.

Location:Los Angeles

Remote: Yes

Relocation: Case-by-case

I'm an engineer and data professional interested in team-building, consulting and architecting data pipelines. At Edmunds.com, I worked on a fairly successful ad-tech product and my team bootstrapped a data pipeline using Spark, Databricks, and microservices built with Java, Python, and Scala.

At ATTN:, I re-built an ETL Kubernetes stack, including data loaders and extractors that handle >10,000 API payload extractions daily. I created SOPs for managing data interoperability with Facebook Marketing, Facebook Graph, Instagram Graph, Google DFP, Salesforce, etc.

More recently, I was the CTO and co-founder of a crypto gaming startup. We raised over $6M and I was in charge of building out a team of over a dozen remote engineers and designers, with a breadth of experience ranging from Citibank, to Goldman Sachs, to Microsoft. I moved on, but retain significant equity and a board seat.

I am also a minority owner of a coffee shop in northern Spain. That I'm a top-tier developer goes without saying. I'm interested in flexing my consulting muscle and can help with best practices, architecture, and hiring.

Would love to connect even if it's just for networking!

Blog: https://ai.dvt.name/whos-david/ (under construction)

GitHub: https://github.com/dvx

Email: [d]@[dvt].[name]

I am so happy I haven't written a line of C++ in like 15 years. Absolutely disgusting language. Every time I look up one of their new standards, I'm like how does anyone keep all of this in their head (usually on top of stuff like boost, etc.)? No wonder LLMs are a thing.