Dhananjay Nene

Information guzzler, Programmer, Traveler

[Debasish (দেবাশিস্) Ghosh 🇮🇳 @debasishg]

https://t.co/dB4v0YpEiW

[Dhananjay Nene @dnene]

@jaidevd Hmm .. had tried out a year ago. Found out, I could write code faster than trying edit generated code (most of my time goes on trying to figure out what to write than actually writing things)

Intend to dip my toes into coding AI again in a month or so.

[Dhananjay Nene @dnene]

Interesting. "When I apply my attention, I come up with solutions that reduce the surface area of the code.

I tend to refactor so the change is easy, comprehensible, elegant. Working with the LLM felt like building channels for effluent. Somehow contain the slop."

[svs 🇮🇳 @_svs_]

People asked me why I cancelled.

LLMs ruined my code.

Once I prompt and the LLM starts spewing code, it sets the direction of my thoughts. And it rarely arrives at the elegant solution.

Because verbosity is not a problem for the LLM, it provides verbose solutions. And in coding verbosity is inversely correlated with elegance and also correctness.

In a well factored system, verbosity should not be a thing. In general I found the LLM never pointed to a refactoring that would make the code less verbose. And this was painful as it happened. And it is going to be 10x more painful in teams and large codebases and so on.

When I apply my attention, I come up with solutions that reduce the surface area of the code. I tend to refactor so the change is easy, comprehensible, elegant.

Working with the LLM felt like building channels for effluent. Somehow contain the slop.

I used to think that LLMs would be useful in the hands of masters. But masters have no need for verbosity. Once you line up the system correctly, you rarely need to specify much. If my system is poorly specified, I find it much more edifying to read documentation until I understand how to specify it correctly rather than deal with a badly factored system.

I went back to chatting with Claude as a documentation copilot. That's enough for me. Some basic copilot autocompletion is enough. Programming through prompting has negative RoI for the moment.

Of course this can change in future. I'll be waiting.

[Dhananjay Nene @dnene]

@jaidevd So you like the fact LLMs give you a good amount of boilerplate that you can then trim down.

Did I get you right?

[Dhananjay Nene @dnene]

Any thoughts? https://t.co/GYg3Vd4wg4

In my experience, AI helps writing new code. But is not helpful when adding changes to an existing codebase. At least not yet, and perhaps not very soon.

But the observation AI increased bugs by 41% caught me surprised.

[Dhananjay Nene @dnene]

Swift is a language with good intentions at heart, seemingly designed by a committee

[Dhananjay Nene @dnene]

@brijwhiz Yes, M3

[Dhananjay Nene @dnene]

Have been doing a fair amount of Android programming lately. Will be learning Swift/iOS soon as well. My second ever Apple purchase after a 2005 iPod Mini

[Dhananjay Nene @dnene]

@jaidevd @pyconindia Awesome

[Dhananjay Nene @dnene]

Correction: I meant KMP not KMM (few months ago jetbrains rechristened KMM as KMP)

[Dhananjay Nene @dnene]

I had learnt flutter for mobile development over a year ago. A couple of weeks ago when I started programming all over again I decided to give Kotlin a try. Especially given KMM (Kotlin Multiplatform) was near maturity. Here are some observations.

[Dhananjay Nene @dnene]

I don't have much experience with KMM but will get there. For a month I'm planning to just learn iOS programming the native apple recommended way. Before then exploring KMM apps. If I had to bet at the moment, I think KMM will be a huge deal

[Dhananjay Nene @dnene]

@_swanand Yeah, this was indeed me telling myself so 😀

[Dhananjay Nene @dnene]

@_zenman Yes. 😀