Man... I spent the last 6 months writing code using voice chat with multiple concurrent Claude code agents using an orchestration system because I felt like that was the new required skill set.

In the past few weeks I've started opening neovim again and just writing code. It's still 50/50 with a Claude code instance, but fuck I don't feel a big productivity difference.

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tossandthrow an hour ago | parent | next [-]

There has always been a difference on modality and substance.

This is the same thing as picking a new smart programming language or package, or insisting that Dvorak layout is the only real way forward.

Personally I try to put as much distance to the modality discussion and get intimate with the substance.

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cwbriscoe 3 hours ago | parent | prev | next [-]

I just write my own code and then ask AI to find any issues and correct them if I feel it is good advice. What AI is amazing at is writing most of my test cases. Saves me a lot of time.

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LtWorf an hour ago | parent | next [-]

I've seen tests doing:

a = 1

assert a == 1

// many lines here where a is never used

assert a == 1

Yes AI test cases are awesome until you read what it's doing.

	▲	ownagefool an hour ago \| parent [-]
		To be fair, many human tests I've read do similar. Especially when folks are trying to push % based test metrics and have types ( and thus they tests assert types where the types can't really be wrong ). I use AI to write tests. Many of them the e2e fell into the pointless niche, but I was able to scope my API tests well enough to get very high hit rate. The value of said API tests aren't unlimited. If I had to hand roll them, I'm not sure I would have written as many, but they test a multitude of 400, 401, 402, 403, and 404s, and the tests themselves have absolutely caught issues such as validator not mounting correctly, or the wrong error status code due to check ordering.

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porridgeraisin 3 hours ago | parent | prev [-]

Yep. Especially for tests with mock data covering all sorts of extreme edge cases.

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koakuma-chan 2 hours ago | parent [-]

Don't use AI for that, it doesn't know what your real data looks like.

	▲	porridgeraisin 2 hours ago \| parent [-]
		Majority of data in typical message-passing plumbing code are a combination of opaque IDs, nominal strings, few enums, and floats. It's mostly OK for these cases, I have found. Esp. in typed languages.

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p0w3n3d an hour ago | parent | prev | next [-]

> voice chat ... required skill set

But we're still required to go to the office, and talking to a computer on the open space is highly unwelcome

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stavros 35 minutes ago | parent | prev [-]

Really? The past two weeks I've been writing code with AI and feel a massive productivity difference, I ended up with 22k loc, which is probably around as many I'd have manually written for the featureset at hand, except it would have taken me months.