[kloud]

My "pelican test" for coding LLMs now is creating a proof of concept building UIs (creating a hello world app) using Jetpack Compose in Clojure. Since Compose is implemented as Kotlin compiler extensions and does not provide Java APIs, it cannot be used from Clojure using interop.

I outlined a plan to let it analyze Compose code and suggest it can reverse engineer bytecode of Kotlin demo app first and emit bytecode from Clojure or implement in Clojure directly based on the analysis. Claude Code with Sonnet 4 was confident implementing directly and failed spectacularly.

Then as a follow-up I tried to let it compile Kotlin demo app and then tried to bundle those classes using clojure tooling to at least make sure it gets the dependencies right as the first step to start from. It resorted to cheating by shelling out to graddlew from clojure :) I am going to wait for next round of SOTA models to burn some tokens again.

[Grimblewald]

mine is seeing if they can implement brown et al (2007) image stitching algorithm. It's old, plenty of code examples exist in training data, the math at this stage is quite well developed, but funnily enough, no decent real open source examples of this exist, especially anything that gets close to Microsoft research's demo tool, the image composite editor (ICE). Even if you heavily constrain the requirements, i.e. planar motion only, only using multi band blending and gain correction, not a single model currently manages to pull this off. Few even have something working at the start. Many other things they excel at, even look downright competent, but in all those cases it simply turns out decent open source examples of the implementation exist on git-hub, usually a touch better than the LLM version. I have yet to see a LLM produce good code for something even moderately complex that I couldn't then find a copy of online.