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7 points fnimick | 1 comments | | HN request time: 0.202s | source

This is the advice I've gotten on how to adapt to AI driven development at breakneck speed - to the point of having AI tooling write and ship projects in languages the 'operator' doesn't even know. How do you get confidence in a workflow where e.g. a team of agents does development, another team of agents does code review and testing, and then it is shipped without a human ever verifying the implementation?

I hear stories of startup devs deploying 10-30k+ lines of code per day and that a single dev should now be able to build complete products that would ordinarily take engineer-years in under a month. Is this realistic? How do you learn to operate like this?

1. chaidhat ◴[] No.46289606[source]
Hi, I’m running a 4-person startup based in Bangkok, Thailand and we differentiate code quality based on priority. We try to ship only clean code on master but when we talk with clients and they want a demo of a new product/feature, we use AI to rapidly create an MVP to see if it aligns with their needs. If they are happy, we then refine this MVP until we are happy with the code through manual review and refactoring, or we even rewrite it. We make sure our data is shaped correctly, hot paths are tested and things are well separated by domain (Domain driven design). DDD ensures us that if the code is shitty, only that part of the project is shitty. Only when the code is acceptable, we rebase to master. I try to let engineers talk to clients so that they learn the most from them first hand and then let them dictate smaller tasks for AI to do —- they are more product managery than what a typical engr would be ten years ago. Do you think this is a good approach? I’m also curious what other startups do too.

tldr we aren’t confident of the code we write quickly but we then take time to make sure we’re confident before we merge to master