solomonb

This is such a tired take. The burden of using static types is incredibly minimal and makes it drastically simpler to redesign your program around changing business requirements while maintaining confidence in program behavior.

I disagree. I think the key insight is to carry the proof with you in the structure of the type you 'parse' into.

that sounds really cool but i've already made a commitment to HTMX, at least for the foreseeable future. My main goal here is building a physical radio station.

Yeah I'm pretty happy with HTMX. I first cut my teeth on programming in the early 2000s with LAMP stack then Ruby on Rails and Django. It feels pretty great to be able to do a web 2.0 style application but still get most of the functionality of a SPA.

https://github.com/solomon-b/kpbj.fm

Still working on my LPFM radio station, www.kpbj.fm. We launched our regular online stream and have secured a site for our transmitter.

The transmit site is in the Verdugo hills and will need to be off grid. We're going to need about $20k to get the entire transmit system setup (including a solar/battery backup system).

I've also been working on our web infrastructure. The site is built with Haskell and HTMX. The stream is Icecast, and stream scheduling is done using an internal schedule system in the web app and LiquidSoap (so no external tools like airtime, libretime, or azuracast).

This really isn't a big deal as it resolved via type universes.

> that world has definitely not stood still, and the prices have come down considerably. But I'd love to have my old frequency counter and pulse generator back

My whole workbench is mid to late 90s HP equipment I've picked up very cheap at swap meets. I love this older stuff but it is really crazy what you can buy out of China now. The Rigol Oscilloscopes and Spectrum Analyzers are crazy. They can actually replace a lot of other test equipment and do some pretty complex analysis.

> I'm really happy that you found an alternate path because such a put-down is terrible and should have never happened in any mature education institution.

I actually had a near identical experience at a different university when seeking advice about how to read Hegel. I think this is a common issue with our academic system.

I never went back to that engineering department.

I ended up befriending a former Northrop RF Engineer and a (sadly) homeless genius who was involved in early silicon valley. Those two guys were incredibly impactful on me and got me all the way up to building RF equipment.

When I was in college I was not in an engineering program but I was self-learning electronics. I was trying to learn to use a 555 timer to do something and couldn't get it to work.

So I went to the office hours of a random EE professor thinking they would help me out. Instead I got scolded about how 555 timers are not real engineering and that I shouldn't waste his time.

I never used a 555 timer ever since.

Thank you! I genuinely think its an awesome project and will probably end up supporting.

I didn't realize I could potentially use it as a highly hackable phone. Whats the battery life like?

EDIT: I just went ahead and pledged my support. I wanna see you guys succeed.

Lol, Cyberdeck aka high effort paper weight.

There are so many cool vaguely scifi tech projects one could build these days but almost none of them have actual utility. : (

Stumbled across this thing a while back and thought it looked really cool but I have never been able to come up with an idea for how I would use it so I haven't pledged.

I want to want it but I fear it would just sit on my desk. Does anyone have cool ideas for uses?

This seems largely the same as any other technology. The prices of new technologies go down initially as we scale up and optimize it's production, but as soon as demand fades, due to newer technology or whatever, the cost of that technology goes up again.

okay how about the Francis Scott Key Bridge?

https://marylandmatters.org/2025/11/17/key-bridge-replacemen...

I agree. I think that once your LLM hits a baseline level of computer science / programming "understanding" it can pretty easily work with whatever language. Using narrow DSLs and low code platforms could be a great way to constraint an LLM and keep it on the happy path.

> After I “Requested changes” he’d get frustrated that I’d do that, and put all his changes in an already approved PR and sneak merge it in another PR.

This is outrageous regardless of AI. Clearly there are process and technical barriers that failed in order to even make this possible. How does one commit a huge chunk of new code to an approved PR and not trigger a re-review?

But more importantly, in what world does a human think it is okay to be sneaky like this? Being able to communicate and trust one another is essential to the large scale collaboration we participate in as professional engineers. Violating that trust erodes all ability to maintain an effective team.

The Corn Demon is alive and well in 2026.

Such an incredible essay (and book) and author. I highly recommend all of her essay writing. She captures the dark death of the California hippy era in a captivating and beautiful way.

Whenever I drive up the 5 leaving Los Angeles I get this strange sense of freedom and I think about Joan Didion and Philip Dick.

That its impossible to find an oil can with a zerk fitting. I need one for my bridgeport that uses zerks for oil and not grease.

I write Haskell professionally and I can tell you that Opus 4.5 can do a great writing industrial Haskell code consistent with an existing code base.

I don't think it is capable of writing galaxy brain Haskell libraries, it absolutely missed the forest for the trees, but if you have an existing code base with consistent patterns it can emulate then it can do a surprisingly good job.

Here is an example side project I have done extremely heavily with Claude: https://github.com/solomon-b/kpbj.fm

I built a library (without Claude) that wraps in an opinionated way Servant and a handful of other common libraries used to build Haskell web-apps and then have let Claude use that to build this site. There is absolutely some hairy code and I have done a ton of manual refactors on what Claude produces, but claude has been highly effective for me here.

> But it could be that different programming languages are a bit like different human languages for these models: when they have more than some threshold of training data, they can express their general problem solving skills in any of them? And then it's down to how much the compiler and linters can yell at them.

I think this is exactly right.

You are right that there is significantly more Javascript in the training data, but I can say from experience that I'm a little shocked at how well opus 4.5 has been for me writing Haskell. I'm fairly particular and I end up re-writing a lot of code for style reasons but it can often one shot an acceptable solution that is mostly inline with the rest of the code base.

I'm biased by my preferred style of programming languages but I think that pure statically typed functional languages are incredibly well suited for LLMs. The purity gives you referential transparency and static analysis powers that the LLM can leverage to stay correctly on task.

The high level declarative nature and type driven development style of languages like Haskell also make it really easy for an experienced developer to review and validate the output of the LLM.

Early on in the GPT era I had really bad experiences generating Haskell code with LLMs but I think that the combination of improved models, increased context size, and agentic tooling has allowed LLMs to really take advantage of functional programming.

Still working on my new LPFM radio station https://www.kpbj.fm

We are a 501c(3) and are actively fundraising to build a tower here in Shadow Hills and are launching our live stream and regular schedule February 1st. So far we have about 60 shows in the schedule.

If you're in Los Angeles and have an interest in radio, please hit me up.

> But your argument could be made against anything novel.

What matters IMO is the lack substance not the quantity of novelty. Your chosen television show examples demonstrate that pretty well IMO.

I hear you but I think you are simply asking for an entirely different blog post. I don't think Verity's aim here is to give an introduction to `Selective`, but rather to introduce a formalization for it; something which has been notably missing for those who think about these sorts of things.

Both are responses to a miss-interpretation of my original comment (which I will grant is at least in part my fault).

We are operating deep in the grey area here so I suppose that case could be made. Personally, I see creativity as more of a life long process which can express itself in a multitude of ways including strokes of genius and the daily iterative grind. I don't think any creative act occurs in a vacuum but I also think that there are moments where big things occur.

AI, as it stands, does not have a lifespan over which for creativity to occur.

Did you really interpret my statement as "AI content producers are being so creative and then quitting posting"?

I'm not talking about people posting good content and then stopping posting.

I guess its fair to say that "become repetitive" was unclear, what I should have said was "reveals itself to be repetitive."

I'm saying that these AI generated world building channels produce lots of content that looks creative and exciting at first but over time reveals itself to be repetitive and lacking in creativity.