You can't be too prescriptive or verbose when interacting with them, you have to interact with them a bit to start understanding how they think and go from there to determine what information or context to provide. Same for understanding their programming styles, they will typically do what they're told but sometimes they go on a tangent.
You need to know how to communicate your expectations. Especially around testing and interaction with existing systems, performance standards, technology, the list goes on.
I think this is something a lot of people are telling themselves though, sure.
What about git stats?
I can tell you the guys that are consistently pushing code AND having the biggest impact are using LLM tools.
What you meant by that?
That plus the completion of high impact projects makes good strong engineers.
Those are the people I see using LLMs
The OP was right to assume it was lines of code. Another assumption could be number of commits, which also doesn’t measure impact.
The problem is some 0.05X developers thought they were 0.5X and now they think they're 2X.
In my real life experience it's been the middling devs that always talk about "ai slop" and how the tools can't do their jobs.
- those who have embraced AI and learned to use it well
- those who have embraced AI but treat it as a silver bullet
- those who reject AI
First group is by far the most productive and adds the most value to the team.
If anything the silver bullet people are mostly managers and C levels... some of which don't even use the tools themselves.
Of the devs that rejected it at first, the ones with the same sentiment I'm seeing online in threads like these, we forced one to give it a try. He now treats totters between using it well and treating it as a silver bullet. I still hear him incredulous about the things claude does at meetings, "I had to do <thing> and I thought I'd let claude get a crack at it... did it in one shot"
Are you guys just trying to one shot stuff? Are you not using agents to iterate on things? Are you not putting agents against each other (have one code, one critique/test the code, and put them in a loop)?
I still look at the code that's produced, I'm not THAT far down the "vibe coding" path that I'm trusting everything being produced, but I get phenomenal results and I don't actually write any code any more.
So like, yeah, first pass the llm will create my feature and there's definitely some poorly written code or duplicate code or other code smells, but then I tell another agent to review and find all these problems. Then that review gets fed back in to the agent that created the feature. Wham, bam, clean code.
I'm not using gastown or ralph wiggum ($$$) but reading the docs, looking over how things work, I can see how it all comes together and should work. They've been built out to automatically do the review + iteration loop that I do.