The Speed of Prototyping in the Age of AI

righthand

But is it really any faster than using an already existing code generator/scaffolding tool? How do you know your project isn’t just a regurgitation of another repository? Would it be just as fast to clone some existing project and hack on it? These are the questions everyone seems to be ignoring and saying “only LLMs can make projects quickly” but ignoring everything those LLMs are built on (your llmis probably calling a code gen tool). For the at work side, I personally haven’t experienced any disadvantages or missed any project deadlines because I didn’t use an LLM, so what does velocity get me? Thumb twiddling time?

rossjudson

I'm truly hopeful that AI will open a new of prototyping. Back in the day, prototyping was how you figured out what to build, you'd very deliberately toss the entire first (or second!) version, and you'd plan to do that. High quality ensued. Usually ;)

tim-projects

Prototype? Why stop there..

kadhirvelm

What are people doing with prototypes afterward? Do you end up shipping it as is to production? What about at work? Are the prototypes useful in that context?

baisampayans

While the speed of prototyping and even shipping to production has increased, I have been asking myself at what cost? I see a lot of garbage being shipped. Not because the code quality is bad, because execution has become cheap now. Ideas even though crap, are getting prototyped. Things which look effective on the surface, but has real UX problems in the underneath, are getting prioritised because someone in the room can talk better and enrol a leader to align with the idea. Good old user research or talking to users to validate ideas, iron out issues in the user flows has become too slow for the new process!!

anssip

AI makes it possible to ship a lot of junk really fast

rmnclmnt

For the past few months, many times i’ve tried this workflow: 1. Ask a coding agent to think and implement a feature that is non trivial 2. This leads to really understand pros and cons for many possible solutions and see it happen end to end 3. Revert all changes and implement it myself when i’m settled on a solution i’m satisfied with 4. At this point the agent is just an iterative reviewer I’ve felt that any non trivial amount of code not written myself tends to be hard to own. And like the author said, need to keep skills sharp also