dvt

Engineering has never been, nor will it ever be, about "repetition" or "memorization." This is a relatively new fable invented by those that have participated in ritualistic interview hazing. Imo, there are, broadly speaking, two types of engineers: computer scientists, and programmers.

Computer scientists do science. The end result is a new algorithm or theorem, and they work with lots of math, proof systems, formal languages, and so on. This is a profoundly creative and collaborative process.

Programmers build products for end-users. The end result is the user experience, the bottom line, stars on Github, or whatever. This is also a process that constantly needs feedback, from teammates and from clients.

These are broad categories and sometimes they overlap: an operating system or database engineer might do a bit of both, depending on the hardware targeted or on various constraints. Sometimes you need to be a bit clever to get to your product goal.

This cleverness has nothing to do with memorizing keywords or solving interview gotcha questions. This cleverness can't be augmented by AI, and it can't be rotted by AI: it's something that's innate to people. Their internal curiosity just happens to manifest in the context of engineering because they love the craft.

In many ways, it's like reading a book. You can't "make someone" enjoy reading, some people are just boring and uncurious. In many ways, I feel that people that are threatened by AI are like this. AI is an incredible tool, but it feels like an autistic junior engineer. Sure, it might have memorized more library names or more syntax or can reference some little-known fact, but it fails to understand basic data flow. It doesn't grasp ergonomics, ease of use, etc., etc.

A tool like fata is great if you want to be an AI, but it won't turn you into a good engineer.

In the last decade, the software engineering industry has turned into a grift that has pushed out hundreds of thousand of low-quality "engineers" through coding bootcamps or online courses. Many of these people have no passion for the craft or interest in building products.

Then, when money was cheap during COVID, companies over-hired unscrupulously. Now, given that markets are cooling off and there's some political, geopolitical, and economic uncertainty, companies are hedging their bets, and laying off is usually the right move, especially as interest rates are going back up.

There are perfectly viable explanations for the situation the industry finds itself in without invoking the AI boogeyman, especially considering that just about every study out there shows that AI use correlates with a fairly modest increase in productivity, and that it won't turn anyone into a "10x engineer" overnight.

Both the Leiden Declaration[1] as well as Commelin et al.'s announcement (Shaping the Future of Mathematics in the Age of AI)[2] are completely common-sense pieces, neither overstating the power of AI nor understating the capability of these tools to be misused (most acutely when it comes to attribution).

I do think that ethically, OpenAI and Anthropic, by training their models on the entire corpus of human knowledge, have certainly broken some rules, but these rules were already broken decades ago by Google—unless we really want to start splitting hairs about if indexing + processing is different than training, which is imo a distinction without a difference—, so it's hard to see who to exactly blame. In any case, that cat is out of the bag. (And for the record, I'm technically a stakeholder: I'm part of like two class actions because of a few books I wrote.) But that's neither here nor there.

[1] https://leidendeclaration.ai/#declaration

[2] https://arxiv.org/pdf/2603.24914

We've been flooded with "AGI is 6 months away!" for a few years now, mostly by Anthropic/OAI/XAI, which is clearly nonsensical hype. Also, almost everyone has been walking back their previous claims that "AI will replace ~80% of white-collar jobs."

Calling my position stoic is kind of goofy imo (and fwiw, I personally find AI to be a pretty useful tool), but I'm not going to reply to some drive-by account literally made just to troll me.

> pushed for by the same fucking people who caused our societies smartphone addiction

Not sure where you live, but I would guess the West (where we have the luxury to be worried about "smartphone addiction"). I assure you that the net positive of smartphones, especially cheap Androids, have had a significantly more positive effect on society than negative, particularly in the developing world.

I think Terry Tao is a great litmus test for AI zealotry (both pro- and anti-). Just in this thread, we have people twisting themselves into knots about how he "sold out" or "not doing math the right way" or whatever. To him, AI is a tool, like any other.

From the interviews I've seen with Tao, he's not some AGI maniac, he says things like here's where we can use this tool, here's where it's less likely to be useful. There's a lot of hallucinations, so we need to double check stuff. Most of the stuff the AI produces is nonsense, but there's occasionally a diamond in the rough.

A very tempered attitude, and likely what most sane people are experiencing when using AI.

Even if it was just prompting, not sure how that takes away from the final, fairly polished, product. How do you define "actual engineering"?

For me, rendering was just a nice-to-have.

Using lopdf[1] for PDF parsing, rtf-parser[2] for RTF, calamine[3] for XLSX, and I'm sure you know that DOCX/PPTX/etc. is basically just a zip file of XML + text. The LLM cares about textual data (which just gets moderately cleaned up post-extraction), so I (thankfully) didn't have to deal with rendering. But showing a preview or end-result to a user would be a huge plus, so I can see myself using your library.

[1] https://github.com/J-F-Liu/lopdf

[2] https://github.com/d0rianb/rtf-parser

[3] https://github.com/tafia/calamine

Super cool. Working on a local AI tool specifically for document workflow automation (where context = screen/web/folders/files), and this could come in super useful. I do most of the PDF/DOCX/etc. parsing natively in Rust, but having a nice way to see the output without spinning up Word or Powerpoint is a huge leap.

Thanks for releasing publicly.

I do have a 3090 Ti on my gaming PC, but even my old M1 MBP (with a mere 32gb of RAM) is quite competent and can run a quantized `Gemma4-26B-A4B` in the background while I do other stuff.

> Even at non VC subsidized $/token prices, its still much cheaper to run cloud based models.

On a price-per-wattage level, this is not true, people have done the math on /r/LocalLLaMA many times over[1]. Local models, while not as good as premier models (GPT 5.5, etc.), are like ~80%+ of the way there, and often converge to a similar solution after a few dead ends.

[1] https://www.reddit.com/r/LocalLLM/comments/1kshq4f/electrici...

AI future is clearly local, and my recent pitch has been "infinite tokens." Because that's what my M1 MBP can do; and that's what my RTX3090 can do. I don't need to pay hundreds of dollars a month and no one else does either.

From the article: "I’ll probably never be a snowboarder at all [...] I’d love to take snowboarding lessons." It doesn't seem like he even snowboarded a day in his life.

Athletes, artists, entrepreneurs say "this has been my dream" all the time when achieving something superlative. But you qualified with "necessarily" so I guess technically you're correct, but it would be kinda' weird if someone told me that "X is their dream" and never did anything about it, especially if it's relatively achievable (i.e. not "going to Mars" or something).

Getting decent at snowboarding isn't some crazy goal (and you need to be decent before you're good, or great). I started skiing late in life and I try to go a few times a season to keep up with it. I'm by no means good, but slowly getting better.

> And yet, somehow, the more years go by, the more rarely I watch snowboarding videos.

I'd argue that snowboarding wasn't author's "dream" to begin with. I think it's reductive and unfair to compare your "oh it would be cool to do that" with someone else's actual dream: as in, a passion they pour their life and soul into. Being great at anything takes much more than a passing "it would be neat to be able to do X."

And achieving a dream (say, competing at the Olympics) is a lot less glamorous than a casual tourist might imagine.

Calling liminalism the "defining" aesthetic of our time is a bit much (though I get the article is trying to hitch its wagon to the Backrooms, aka the "current popular thing"). It's an aesthetic microniche, about as popular as vaporwave, or cyberpunk, grunge, or Y2K (think flip phones, bulky plastic cameras, etc.). There's a ton of these, and some are surprising: for example, there's even been a relatively recent revival of the "old-money" aesthetic, especially motivated by fashion brands like Rowing Blazers, etc.

Literally working on a product that does this, hah :) I really do think that AI + automation + carefully-designed guardrails will unleash a deluge of productivity for normies, and we've barely scratched the surface.

The state of AI apps is absolutely trash right now, it’s embarrassing that these companies that raised millions are releasing the shittiest slop around without any product ethos. Obviously we're seeing what sticks, but come on guys.

I'm using Brett Cannon's `https://github.com/brettcannon/cpython-wasi-build` running inside a WASI rust container with a carefully-designed host SDK (e.g. sandboxed Chromium access, diff, sandboxed filesystem, pandas subset, PDF reading, etc.). Essentially the AI sees a goal, a plan, and essentially treats the "task space" as a WASI-powered Python notebook.

Mainly focused on the user experience, and I think that local LLMs (secure/private) + standard Python + host functions + (some external stuff like screen reading & quarantined web access) is more than enough for 90% of actionable tasks.

Very exciting times ahead.

It's always the most insufferable people that make the biggest hullabaloo about a project they have nothing to do with and have never contributed to. People with literally zero skin in the game using the AI boogeyman to push some agenda or some anti-agenda. OSS has become so incredibly toxic in the past decade, and consumers of OSS have become extremely entitled.

I run a smallish project with ~1k stars and I've stopped maintaining it last year because people feel like they're absolutely owed features or bug-fixes or whatever. It's tiring and a complete shame that author has to make such an insane deep dive into a random accusation that just caught on social media. I want to emphasize that this has nothing to do with AI, it's just tech tourists, consumers (as opposed to creators), and engagement farmers that have taken over. AI slop probably doesn't help, but the underlying issue has been brewing for at least a decade.

Also, the "making soup for the homeless & pissing in it" is not only an off-base analogy (software is pretty low on Maslow’s Hierarchy of Needs), but also somehow looks down on both people in need and the volunteers that help them. Just absolutely gross.

I'm not a psychologist or a mental health professional, but I think that this might serve a similar purpose as journaling. It's obvious that AI can't "fix your problems," but just writing stuff down can help us process.

It is (especially the self-reflection).

Can you source this? My cursory research shows the opposite[1]. Imo, the fiscal disaster is in part due to enrollment declining (which, ironically enough, mainly affects low-income households).

[1] https://myelearningworld.com/cost-of-college-vs-inflation/

The idea that AI is somehow at fault for the absolute fiscal disaster the UC and the CSU systems find themselves in is laughable at best and damaging at worst. These systems (and I say this as a graduate of UCLA that was on a full academic scholarship) have been taken over by parasitic administrators and bureaucracies-on-top-of-bureaucracies that have milked not only the students, but also the taxpayers, completely dry. Tuition has consistently gone up since the 70s, while housing, facility, classroom quality have all gone down.

It's been literally the biggest grift of the past 50 years[1]. Education should be free.

[1] https://eliterate.us/wp-content/uploads/2011/03/Tuition.png

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]

Feel free to reach out at d(at)dvt(dot)name—happy to connect!

WASI provides a very nice mental model where you can mount, e.g., /input, as read-only, and where every mutation is saved in /output or what-not. At least that's my favorite contract: input files remain untouched, but we can copy them and do whatever we want with them in /scratch or /output (which the user can later investigate and make sure nothing went horribly wrong while still having backups).

I was actually curious, on my Mac, it uses `gs -q -sDEVICE=txtwrite -o output.txt input.pdf` (not sure why I have Ghostscript installed, maybe Adobe?) to read a PDF, and on my PC it just rawdogs `pdftotext`.

LLMs can live in the cloud, but all tools need to be (1) local, and (2) containerized. It's clear to me that just willy-nilly "running stuff" is going to blow things up eventually. Maybe folks don't know this, but even Codex installs random binaries on your PC. "Read this PDF" installs a pdf reader executable. Is it vetted? Where's it from? Is it a virus? Who knows, who cares. Model goes brrrr.

I'm working on a project that includes WASI containerization for local LLM workflows (which is a pretty tough problem), and I'm flabbergasted that Anthropic and OpenAI aren't more worried about these attack vectors. It feels like amateur hour.

> Either I'm bad at communicating today or you're bad at reading

Could be both :)

The way I look at it is like this, and you could call this my thesis: I do not categorically think that code in itself is primarily relevant to us looking at a "software engineer" and saying "wow, she's good." The product (the Linux kernel, in Torvalds' case) is, on the other hand, what actually matters. I think we're getting caught up on the idea of a code review; a code review can serve many purposes, as a code review is basically just people talking about the code, the product, their feelings, and so on. Sure, sometimes it's like "this `i` should be a `j`", but other times it's "this should serve feature X, not feature Y."

Overall, I don't think Torvalds is judged by his code quality. And the snippet I cited is the man himself saying "I don't write code anymore" so I took that at face value, even though my conviction stands wether or not he actually does still write code. I don't think anyone actually cared that much about his code quality (maybe with the caveat that the kernel didn't crash).

PS: I could be totally wrong, and this is an interesting & stimulating conversation, regardless.