Replying to an earlier post

Well, yeah…

Most of the time it doesn’t work, rarely it does.

Intermittent rewards are what we’re wired for. That’s why random rewards/acknowledgment tickle our brains more than standard rewards we know are coming.

That’s the reason there’s such a big push “to just try it”.

It’s the same strategy the first crack dealers used

en

Replying to an earlier post

It feels so weird to read lemmy, as if I’m living in a different reality. To me, most of the time an agent can oneshot a ticket (if it has a good, non-vague description) or at least do 80-90% that can be fixed with several changes or prompts, and only odd tasks need more manual investigations than that.

Surely you still need a dev oversight and someone needs to do tech plans & lead the projects, but that’s not like anything people experience here.

Replying to an earlier post

Anthropic claims that Fable has low low low hallucination rate of just 40%.

LLMs outputting code solving this exact task is a compound function of luck, with non determined a priori chance of success and unknown a priori cost.

This is my main disappointment with agentic coding. Prompting is fine, quality assurance is there from the start. Greenfield, couldn’t care less. Established enterprise code? This is a minefield.

If the tokens were 10 to 100 times cheaper, then it would be a maybe.

I also hate how it makes half of my senior engineers dumber.

Replying to an earlier post

Yeah 100%, an agent failing at what I want it to do is extremely rare now, like, a 1% chance at most, and it’s usually easily fixed. I think most people with this experience aren’t developers at all in a professional sense and therefore don’t have the oversight to write a prompt properly with well defined goals and scope, or they’re using the free version or something.

The study methodology is also extremely dubious to boot. This is just getting clicks due to pure anti-ai sentiment. I have my own issues with AI too, but this is just classic internet clickbait.

Replying to an earlier post

It depends on the task. Oneshotting 80% of the new feature and then failing to pick up on details can leave hard part.

But oneshotting even 30% of UI tests based on QA regression means you have 30% of regression covered. Ofc you need to verify if the test is indeed covering the test case, and for a big volume of tests it takes time, but it’s nowhere near what it takes to actually write the tests.