back

by musha68k·1y ago·view on hn ↗
Prototypes unfortunately often stick. IMO refactoring someone else's code is less efficient vs whatever code I wrote myself. I'm pondering net productivity.

Have you personally deployed anything based on agent results (predominantly)? I'm just trying to gauge if the current state ("early days") is actually worth investing time and money in from a professional perspective.

In my experience, hype often precedes actual usefulness by a significant margin.

TL;DR are we there yet?

1 comments
I have an API project in development where the majority of the code has been written through Claude Code. It offers an integration of the Congress.gov and GovInfo.gov APIs, and analysis tools for their respective (somewhat overlapping but not always) public information.

I put significant effort in constructing the product & project requirements beforehand and have built a number of simple tools as I ran into roadblocks or inefficiencies, so I can attest to there being a large amount of hype. I can also comfortably state that without the use of LLMs, I would not be this far along.

Having a background in software development (UX side) and a deep interest in technology gives me some insight in to which questions to ask and when to “throw a flag” and ask the LLM to explain why it’s doing something. I don’t believe the hype around one-shot enterprise applications, but the current state of AI programming is usable if people take the care they hopefully would with their own output.

Cool, thanks for sharing!