I took a quick informal poll of my coworkers and the majority of us have found workflows where CC is producing 70-99% of the code on average in PRs. We're getting more done faster. Most of these people tend to be anywhere from 5-12 yrs professional experience. There are some concerns that maybe more bugs are slipping through (but also there's more code being produced).

We agree most problems stem from: 1. Getting lazy and auto-accepting edits. Always review changes and make sure you understand everything. 2. Clearly written specification documents before starting complex work items 3. Breaking down tasks into a managable chunk of scope 4. Clean digestible code architecture. If it's hard for a human to understand (e.g: poor separation of concerns) it will be hard for the LLM too.

But yeah I would never waste my time making that video. Having too much fun turning ideas into products to care about proving a point.

> Having too much fun turning ideas into products to care about proving a point.

This is a strange response to me. Perhaps you and others aren’t aware that there’s a subculture of folks who livestream coding in general? Nothing to do with proving a point.

My interest in finding such examples is exactly due to the posting of comments like yours - strong claims of AI success - that don’t reflect my experience. I want to see videos that show what I’m doing wrong, and why that gives very different results.

I don’t have an agenda or point to prove, I just want to understand. That is the hacker way!

2, 3, 4 are all what human coders need to be efficient too :)

I'm kinda hoping that this LLM craze will force people to be better at it. Have documentation up to date and easily accessible is good for everyone.

Like we're (over here) better at marking lines in the road, because the EU mandated lane keeping assist needs the road markings to be there or it won't work.