[avianlyric]

I think you’re being a little over critical of LLMs. They certainly have their issues, and most assuredly people often use them inappropriately. But it rather intellectually lazy to declare that because many people use LLMs inappropriately, that means they can’t offer real value.

I’ve personally found them extremely useful to test and experiment new ideas. Having an LLM throw together a PoC which would have taken me an hour to create, in less than 5mins, is a huge time saver. Makes it possible to iterate through many more ideas and test my understanding of systems far more efficiently than doing the same by hand.

[skydhash]

Maybe that’s alien to me because I don’t tend to build PoC, mostly using wireframes to convey ideas. Most of my coding is fully planned to get to the end. The experiment part is on a much smaller scale (module level).

[avianlyric]

Ah my apologies. I didn’t realise you’re an individual capable of designing and building complex systems made of multiple interconnected novel modules using only wireframes, and having all that work without any prior experimentation.

For the rest of us less fortunate, LLMs can be a fantastic tool to sketch out novel modules quickly, and then test assumptions and interactions between them, before committing to a specific high level design.

[skydhash]

> I didn’t realise you’re an individual capable of designing and building complex systems made of multiple interconnected novel modules using only wireframes, and having all that work without any prior experimentation.

Not really. It's just that there's a lot of prior works out there, so I don't need to do experimentation when someone has already done it and describe the lessons learned. Then you do requirement analysis and some designs (system, api, and ux), plus with the platform constraints, there aren't a lot of flexible points left. I'm not doing research on software engineering.

For a lot of projects, the objective is to get something working out there. Then I can focus on refining if needs be. I don't need to optimize every parameter with my own experiments.

[avianlyric]

How do you handle work that involves building novel systems, where good prior art simply doesn’t exist?

I’m currently dealing with a project that involves developing systems where the existing prior art is either completely proprietary and inaccessible, or public, but extremely nacient and thus documented learnings are less developed than our own learnings and designs.

Many projects may have the primary objective of getting something working. But we don’t all have the luxury of being able to declare something working and walk away. I specifically have requirements around long term evolution of our project (I.e. over a 5-10 year time horizon at a minimum), plus long term operational burden and cost. While also delivering value in the short term.

LLM provide are an invaluable tool for exploring the many possible solutions to what we’re building, and helping to evaluate the longer term consequences of our design decisions, before we’ve committed significant resources to developing them completely.

Of course we could do all this without LLMs, but LLMs substantially increase the distance we can explore before timelines force us to commit.

[skydhash]

Maybe the main problem is not solved yet, but I highly doubt that the subproblems are not. Because that would be cutting edge domain, which is very much an outlier.

[avianlyric]

Ah so what exactly do you mean when you say

> Most of my coding is fully planned to get to the end. The experiment part is on a much smaller scale (module level).

I would seem that these statements taken together mean you don’t experiment at all?