Verdex

Patrick Stewart was the first actor that I noticed who always seemed to bring his A game. Even for productions where clearly everyone else was phoning it in. It was a good lesson to observe when I was young. Just because you find yourself in a dumb situation doesn't mean you can't do a good job.

This was a person who from a relatively young age looked old, but more importantly behaved with a sort of dignity and thoughtfulness that projected way beyond his years. I'm not really sure how to assimilate the news because on the one hand obviously this was going to be happening sooner or later. He has always just felt old. But on the other, he's felt old for my whole life, so why shouldn't he just continue on that way without bound.

Ah yes, the audience is ignoring our low quality content because it's low content and ignorable so we're going to lower the quality even more strategy. I wonder if it'll pay off for them...

Speaking for myself. Not really. The problem that I had with enjoying programming was that many of my coworkers who didn't enjoy programming have some opinions that were frustrating to need to entertain.

Now all I have to do is make sure they're not peddling an actively bad idea and if not I can just tell the bot to incorporate their dubious ideas.

In the past it was all, I'm not familiar with this construct that solves our problem perfectly, why don't we cludge adapter pattern in here again.

This was my take on it as well. Which in many ways makes a lot of sense and is pragmatic.

The thing which I think is going to be a very sore lesson for everyone at some point is that if anyone uses AI it becomes a burden for everyone. Even in projects that reject all AI usage.

What I can do is create 50 personas that all contribute patches. 40 of them get called out and are distrusted, but 10 make it through. I can give more focus on those 10 to ensure their trust level increases. Then slowly have them all come together to shepard some subsystem where I'm going to be the only real person involved and can sign off on my own work in a that looks like I have oversight from the outside.

In the past this was possible but took a very high cost. You need a bunch of competent software engineers who you can trust not to blab their secret mission. Today anyone can give it a try.

My theory is that the LLMs can only think in terms of data structures of a certain "dimensionality".

So for example I tried to have LLMs write xml parsers from scratch in Q3 2025, but they kept getting confused and midstream would migrate from c# to xml (that is their solution was half c# half xml file). So thinking in a tree data structure was beyond them.

Then Q1 2026 they were able to write parsers including parsers for languages where I specified with a bunch of examples.

But I tried specifying a language that I thought would require storing the AST in a graph structure. Everytime the LLM would instead parse into a tree and then do post processing on the tree to get the right output. So perhaps graph structures are (were?) beyond them.

I haven't investigated forth for a while, but it's been on my to-do list. I'll have to bump it up some because it sounds like I can kill two birds with one stone here.

I do kind of wonder if tree space is a local maximum, though. You can do quite a lot of things in that space and most of the code that I've read that leans on some sort of graphical thinking (like heavy usage of global variables that effect the execution path all over the call graph) is a less than ideal substrate to have to think through.

[One of the problems with investigating this is that I can't just ask it to solve a problem that is obviously just dijkstra because that's in the training data.]

There are perhaps two different modes of communication between people.

On the one hand we have vibing. Everyone just sits around telling each other things that affirm the group to be correct. No actual information is being transferred in the traditional information theory sense because saying something surprising would kill the vibe.

I don't really understand what this is good for but it happens all the time so I'm going to assume it has some social function.

Then there's communication that's more in line with information theory. That is information theory at least in part is dealing with some percentage of being surprised at what you receive. And so some human to human communication seems to be about hearing not what you expect but what you don't.

Personally, I seek the later, but I think most people desire the former.

And so, when the AI (or other people for that matter) tell me that I'm right, I assume that I don't understand the whole picture yet or am otherwise confused about something.

I don't personally like the comparison.

On the one hand we've got a spinning disk.

And on the other hand we've got the latent space of everything a human has ever written sitting inside a harness of ever increasing complexity.

Even if you put aside the qualitative nature of the analogy, the quantitative difference is so great that I'm not convinced there's any meat to get out of it.

Edit:

Actually here's a competing analogy. 210 BC emperor Qin Shi Huang drinks mercury in an attempt to live forever.

Then in 1996 Dr. Karen Wetterhahn has a drop of an organic mercury compound soak right through her latex glove, through her skin, and into her bloodstream. Where it kills her after a year of worsening physical symptoms.

Mercury, a tool that was super scary thousands of years ago, but remains unbelievably dangerous nightmare fuel.

The universe, plot, and characters are all aggressively atheistic[1]. Meanwhile the prose is heavily infused with Christian religious language, references, and allusions.

Consequently, I'm not really sure who the book is for. I don't know any Christians who like atheistic hard scifi (although, I exist so there must be others). And I don't know many people into hard scifi who really care for the religious imagery.

Personally, I find the experience to be unique, so I think it's worth it if you can get into it.

Besides that (and to spoil the point of the book) the biggest flaw is that the author doesnt seem to trust the reader to get the point, which is that consciousness is an unnecessary (and detrimental) evolutionary dead end. Real intelligence is totally orthogonal.

As a software engineer who has seen very intelligent systems with no more consciousness than a paperclip for decades, I got on board with the premise as soon as it showed up. But then I kind of had to wade through case study after case study highlighting the idea.

[1] - this isnt atheism that's aggressive, but rather a universe where there's no doubt that there is no god with all of the consequences thereof.

Yeah, the end was in desperate need of another editing pass. He takes you by the head, smashes your face into the ground, and then drags you for half a mile.

Anyone who gets that far into the book doesn't need to have their hand held that much. I get that it's the entire point of the book, but everything until this point has been a challenging read.

Personally, I think it might have been interesting to rewrite the whole thing such that conclusion is ambiguous.

My pet theory is that there are different types of intelligence that have different pros and cons. Social/cultural, intuition, and structural.

Structural is like step by step reasoning or math or raw compute.

Intuition is statistical from repeated trial and error.

And social is leaning on the wisdom of the crowds. So like high latitude countries where they eat fish for breakfast and get better health outcomes.

So I believe that LLMs have stumbled upon a partial component of our social intelligence. Word distribution, ontologies, jargon, information theory (frequently used symbols should be short). We mutate the language that we speak to be useful to us based on the problems we face. To some extent being able to talk the talk means you can also walk the walk. At least partially.

It's kind of shocking how far they can get, but at the same time it's kind of a surprise how far they don't. The existence of agentic harnesses is sort of an admission of defeat.

While some might be fooled into thinking that they reason, everyone I've met isn't. As a software engineer I'm drowning in work. And if that's not an admission that this isn't a real intelligence then I don't know what is.

But ultimately it looks like we've got all the individual components sorted. The old school 70s era stuff has a lot of the structural intelligence covered. The data science era of statistical ML has the intuition. And LLMs have the intelligence from our culture.

Maybe there are more general or energy efficient or powerful or special purpose techniques out there. And maybe combining everything together requires some additional insight. Regardless it feels like moving forward to something better than our current AI landscape is plausible, albeit with a completely unknown level of effort.

English is my first language. I have always found this discrepancy deeply unsettling. A personal problem on my part I'm sure.

I think the issue is that there are rules but they're really complicated. So nobody learns them. And then they teach kids by cultural taboo violation.

"The letter 'c' makes two sounds. An 's' sound and a 'k' sound."

Atlantic osean.

"Wrong! It's Atlantic oshean! Why are you wrong!"

Then iterate for 20 years.

YouTube videos talking about linguistics and history have been a significant eye opener about the source for half a lifetime of frustration.

> Once you come to terms with the idea that translating an exact specification into decent code isn't a unique skill

My employer moved out of the "accept spec; produce code" space back in the early aughts. It was clear that early that this was going to be a bad space to operate in. (Although not for LLM reasons, obviously)

Yeah, I primarily use rust because it's got algebraic data types, pattern matching, and cargo.

If ocaml had a cargo like experience, then I would migrate there.

I feel like the weather app makes a lot of sense from a corporate politics point of view.

A 1mb weather app would have a significantly less impressive pie chart associated with it come "here are our improvements" presentation.

Also if times get tough and you're told to reduce headcount by 10%, who do you want to get rid of. Sally who knows the USB driver end to end or Todd who wrote the bloated 1gb weather app. (Don't feel bad for Todd, he knew what he was getting himself into.)

A quick search suggests that the most expensive education in the world is something like $100k.

So like you spend a million times more than that and you still think you're not going to see some results?

Don't the children of the wealthy famously have a tendency to be successful? Or have I badly misinterpreted the last several thousand years of human history.

To really drill down into that I would think you would need to figure out how many millionair children get tutored vs how many get spoiled.

I couldn't do any of those, but then ~$10k of education later I was able to accomplish one of those things.

I think LLMs are really impressive, but I suspect that we might have overpaid just a bit.

I would be willing to bet that any human for which we spend $100billion - $3 trillion (depending if you want to count single corporations or global totals) on in an attempt to make them as capable as possible would be able to reach all of those levels.

To be sure I don't like the phrase. But more importantly I also don't like the outcomes when improper abstractions are setup and vital details ignored.

Clearly I misspoke. But it looks like you've got the gist of what I was trying to say.

I don't believe that AI is the 'higher level of abstraction[1]' that it is often claimed to be. However I wonder if it's possible to work with a codebase when other developers are treating AI as a higher level of abstraction.

Analogously, people can write in assembly, but can you write in assembly when the codebase is frequently altered by someone with an optimizing compiler?

[1] - Do higher levels of abstractions even exist? By my way of thinking that's called not an abstraction. C isn't a higher level of abstraction; it's a different abstraction implemented by assembly. There are more powerful abstractions and more ergonomic abstractions, but that doesn't make them 'higher level'.

Meanwhile I'm sure there's people out there baffled that anyone finds dwarf fortress challenging to get into.

I'm old enough that I've had the pleasure of handholding software engineers through their first anonymous function usage. Effect system, refinement types, totality checker? The best I get is blank stares before they go back to C# and JavaScript. These days I'm just glad they tolerate linq expressions and typescript.

It matters where you're standing for what feels incomprehensible. But then again, you can say the same thing about dwarf fortress.

Fearmonger? Me? Well I never.

Also

> if you've worked with other proof oriented languages.

That's doing a lot of heavy lifting.

To borrow your video game analogy. F* is the dwarf fortress of programming languages. Screenshots are only going to confuse anyone who isn't ready to take a significant mental journey.

It has to be done by next week.

Here it is. It is done.

Great, now we put it on a shelf and ignore it for 6 months.

From my perspective, every time.

Edit: the last time this happened to me, they later revealed that it was going to be shelved for a year.

Today we see someone being arrested because they used a software feature. Next year we'll see someone being arrested because they played a cutesy trick and got the LEO to enter in the self destruct code.

The engineers and techies involved have so far shown themselves to have poor intuition for understanding how the law is going to react. I think it behooves anyone still listening to their advice to also check in with someone who has a good intuition for how the law will react to this new idea.

This is an interesting idea, but was that GrapheneOS person a lawyer giving legal advice?

At least for me, the technical chops to be able to program a computer was always just table stakes for software engineering.

The majority of my job more or less reduces to mitigating the consequences of having all the stakeholders dreams come true. Most normal people consider rules as run by people. They expect them to ignore rules that don't make sense, apply rule of thumb, get the gist, and do what it takes to achieve success.

When you take these sorts of rules and try to put them into silicon, the end result is often an undesirable result despite all the rules being successful implemented.

The law are these sorts of rules. They're designed to be "executed" by people using judgement. Part of the reason why the law works is specifically because we don't have a bunch of computers watching everyone all the time. Secure in your person and papers is literally right there in the constitution. Like they didn't know about computer surveillance when they added that amendment but they knew that without privacy the law doesn't work as intended.

Which seems a bit off to me. Can they even ipo right now due to the apple business?

Although I don't think you're wrong. The number of "organic" social media posts I've seen in the past few weeks of the form: 'Wow, Anthropic users are ugly losers...nothing like those handsome openai tiger blood winner sages' is simply too high in my mind for anything other than an ipo prelude.

[Also are altman and musk really fighting on x? Like, that's got to be a sign of some sort of internal stressors right?]

This isn't a great comparison.

Im not that familiar with elixir, but erlang is hands down the best dynamic language to build systems in. It feels like they made only right decisions. I can only assume that elixir has made improvements on that.

Meanwhile java and kotlin have the least useful types I've encountered in my career. Scala has some pretty powerful stuff, but it's like the c++ of powerful types. The ergonomics aren't great. Finally, typescript has a lot of impressive typing constructs but it really falls down on the runtime side (because javascript).

The real comparison to make would be erlang/elixir vs rust or ocaml.