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by mekael
98 days ago
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Most people I know don't write any code with agents, 90ish percent is still written by hand. I'm personally still trying to figure out where to fit them into my workflow: there's not much boilerplate to write as well known frameworks and libraries had already taken care of the heavy lifting, templates for major project types cut down on the initial startup overhead, and all of the project planning is done upfront with business partners. Despite my ethical issues with AI, I am using it for a handful of personal projects so I am at least keeping up with what the frontier models are doing and I'm quite impressed with them for doing reverse engineering (they need a lot of hand holding, but I've been able to knock out months of trial and error pretty quickly). That being said, I'm still perplexed when people state they're getting huge gains from them in terms of knocking out boilerplate, or helping them plan out the project. I was under the impression that the former was a solved problem, and the latter was a requirement of being a decent engineer. |
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It want solved. There was some generic boilerplate that was added to IDEs but it wouldn't be project specific. It wasn't able to look at patterns within your own codebase and repeat them.
>and the latter was a requirement of being a decent engineer.
Most software projects are too big to fit in one engineers head. Having AI be able to research what the relevant code is, how it works, what race conditions exist, what pitfalls or other things you may run into saves a lot of time in regards to planning.