The best code I've written with an LLM has been where I architect it, I guide the LLM through the scaffolding and initial proofs of different components, and then I guide it through adding features. Along the way it makes mistakes and I guide it through fixing them. Then when it is slow, I profile and guide it through optimizations. So in the end, it's code that I know very, very well. I could have written it but it…
It's fascinating how a report like yours or theirs acts as a lightning rod for those who either haven't been able to work it out or have rigid mental models about how AI doesn't work and want to disprove the experience of those who choose to share their success.
A couple of points I'd add to these observations: Even if AI didn't speed anything up... even if it slowed me down by 20%, what I find is that the mental load of coding is reduced in a way that allows me to code for far more hours in a day. I can multitask, attend meetings, get 15 minutes to work on a coding task, and push it forward with minimal coding context reload tax.
Just the ability to context switch in and out of coding, combined with the reduced cognitive effort, would still increase my productivity because it allows me to code productively for many more hours per week with less mental fatigue.
But on top of that, I also antectodally experience the 2-5x speedup depending on the project. Occasionally things get difficult and maybe I only get a 1.2-1.5x speedup. But it's far easier to slot many more coding hours into the week as an experienced tech lead. I'm leaning far more on skills that are fast, intuitive abilities built up from natural talent and decades of experience: system design, technical design, design review, code review, sequencing dependencies, parsing and organizing work. Get all these things to a high degree of correctness and the coding goes much smoother, AI or no AI. AI gets me through all of these faster, outputs clear curated (by me) artifacts, and does the coding faster.
What doesn't get discussed enough is that effective AI-assisted coding has a very high skill ceiling, and there are meta-skills that make you better from the jump: knowing what you want while also having cognitive flexibility to admit when you're wrong; having that thing you want generally be pretty close to solid/decent/workable/correct (some mixture of good judgement & wisdom); communicating well; understanding the cognitive capabilities of humans and human-like entities; understanding what kind of work this particular human/human-like entity can and should do; understanding how to sequence and break down work; having a feel for what's right and wrong in design and code; having an instinct for well-formed requirements and being able to articulate why when they aren't well-formed and what is needed to make them well-formed.
These are medium and soft skills that often build up in experienced tech leads and senior developers. This is why it seems that experienced tech leads and senior developers embracing this technology are coming out of the gate with the most productivity gains.
I see the same thing with young developers who have a talent for system design, good people-reading skills, and communication. Those with cognitive flexibility and the ability to be creative in design, planning and parsing of work. This isn't your average developer, but those with these skills have much more initial success with AI whether they are young or old.
And when you have real success with AI, you get quite excited to build on that success. Momentum builds up which starts building those learning skill hours.
Do you need all these meta-skills to be successful with AI? No, but if you don't have many of them, it will take much longer to build sufficient skill in AI coding for it to gain momentum—unless we find the right general process that folks who don't have a natural talent for it can use to be successful.
There's a lot going on here with folks who take to AI coding and folks who dont. But it's not terribly surprising that it's the senior devs and old tech leads who tend to take to it faster.