Hacker News Reader

Comment by pqdbr | Hacker News Reader

Same impression here.

I've been using Cursor for around 10 days on a massive Ruby on Rails project (a stack I've been coding in for +13 years).

I didn't enjoy any productivity boost on top of what GitHub Copilot already gave me (which I'd estimate around the 25% mark).

However, for crafting a new project from scratch (empty folder) in, say, Node.js, it's uncanny; I can get an API serving requests from a OpenAPI schema (serving the OpenAPI schema via swagger) in ~5 minutes just by prompting.

Starting a project from scratch, for me at least, is rare, which probably means going back to Copilot and vanilla VSCode.

View on HN

I feel like this whole "starting a new project" might be the divide between the jaded and excited, which often (but not always) falls between senior and junior lines. I just don't do that anymore. Coding is no longer my passion, it's my profession. I'm working in an established code base that I need to thoughtfully expand and improve. The easy and boilerplate problems are solved. I can't remember the last time I started up a new project, so I never see that side of copilot or cursor. Copilot might at its best when tinkering.

If I struggle on a particularly hard implementation detail in a large project, often I'll use an LLM to set up a boilerplate version of the project from scratch with fewer complications so that I can figure out the problem. It gets confused if it's interacting with too many things, but the solutions it finds in a simple example can often be instructive.

To fully extract maximum value out of LLMs, you need to change how you architect and organize software to make it easy for them to work with. LLMs are great with function libraries and domain specific languages, so the more of your code you can factor into those sorts of things the greater a speed boost they'll give you.

I start new projects a lot and just have a template that has everything I would need already set up for me. Do you think there is a unique value prop that AI gives you when setting up that a template would not have?

AI has templates for the languages you seldom use (as long as the language is not too niche for the LLM to have trained on it).

I do both. I have a basic template that also includes my specific AI instructions and conventions that are inputs for Aider/Cursor. Best of both worlds.

GH Copilot chat specifically has directives like

  @workspace /new “scaffold a ${language} project”

that automagically creates a full project structure and boilerplate. It’s been great for one off things for me at least

You don't need AI to implement that.

How do you use AI in your workflow outside of copilot?

I haven’t been able to get any mileage out of chat AI beyond treating it like a search engine, then verifying what it said…. Which isn’t a speedy workflow

Reply on news.ycombinator.com