The role of developer skills in agentic coding

I use Cursor for most of my development these days. This article aligns pretty closely with my experiences. A few additional observations:

1. Anecdotally, AI agents feel stuck somewhere circa ~2021. If I install newer packages, Claude will revert to outdated packages/implementations that were popular four years ago. This is incredibly frustrating to watch and correct for. Providing explicit instructions for which packages to use can mitigate the problem, but it doesn't solve it.

2. The unpredictability of these missteps makes them particularly challenging. A few months ago, I used Claude to "one-shot" a genuinely useful web app. It was fully featured and surprisingly polished. Alone, I think it would've taken a couple weeks or weekends to build. But, when I asked it to update the favicon using a provided file, it spun uselessly for an hour (I eventually did it myself in a couple minutes). A couple days ago, I tried to spin up another similarly scoped web app. After ~4 hours of agent wrangling I'm ready to ditch the code entirely.

3. This approach gives me the brazenness to pursue projects that I wouldn't have the time, expertise, or motivation to attempt otherwise. Lower friction is exciting, but building something meaningful is still hard. Producing a polished MVP still demands significant effort.

4. I keep thinking about The Tortoise and The Hare. Trusting the AI agent is tempting because progress initially feels so much faster. At the end of the day, though, I'm usually left with the feeling I'd have made more solid progress with slower, closer attention. When building by hand, I rarely find myself backtracking or scrapping entire approaches. With an AI-driven approach, I might move 10x faster but throw away ~70% of the work along the way.

> These experiences mean that by no stretch of my personal imagination will we have AI that writes 90% of our code autonomously in a year. Will it assist in writing 90% of the code? Maybe.

Spot on. Current environment feels like the self-driving car hype cycle. There have been a lot of bold promises (and genuine advances), but I don't see a world in the next 5 years where AI writes useful software by itself.

40 seems way too much. “}” alone probably makes up a significant portion of lines. Another thing is auto-complete that does the majority of typing anyway.

In English, the average word length is 5 characters. If you can type 60 WPM that means you're typing on average at least 300 characters per minute or at least 5 characters per second (at least because this is not counting the needed whitespace and punctuation). That makes it technically possible for a moderately capable typist to pull off 7000 lines in a day using your numbers. Pair that with IDEs and autocomplete and it becomes much more feasible, if you have a solid understanding of the objective for your code.

There are certain pieces of text that appear right before some of the greatest pieces of code ever written. For example, we've all heard of NASA code requirements. If you get the LLM into the "mindset" of a top-tier professional developer before getting it to spit out code, the code quality will reflect that. If your prompt is sloppy and poorly defined, you'll get copy-pasted StackOverflow code, since that's how most SO questions look. If it's stupid but it works, it's not stupid.

The hard part is that finding a local optimum for prompting style for one LLM may or may not transfer to another depending on personality post-training.

And whatever style works best with all LLMs must be approaching some kind of optimum for using English to design and specify computer programs. We cannot have better programs without better program specifications.

you seem to be projecting your own experience rather than giving an accurate representation of developer productivity - 15k is not the norm at all or even close to it.