After months of coding with LLMs, I'm going back to using my brain

> You have the copilot mode which takes no learning at all which might give you some speedup, especially if you are doing repetitive stuff, it might even 10x+ you.

I have some grey hair and I've been programming since I was a kid. Using CoPilot autocompletion roughly doubles my productivity while cutting my code quality by 10%.

This happens because I can see issues in autocompleted code far faster than I can type, thanks to years of reading code and reviewing other people's code.

The 10% quality loss happens because my code is no longer lovingly hand-crafted single-author code. It effectively becomes a team project shared by me and the autocomplete. That 10% loss was inevitable as soon as I added another engineer, so it's usually a good tradeoff.

Based on observation, I think my productivity boost is usually high compared to other seniors I've paired with. I see a lot of people who gain maybe 40% from Copilot autocomplete.

But there is no world in which current AI is going to give me a 900% productivity boost when working in areas I know well.

I am also quite happy to ask Deep Research tools to look up the most popular Rust libraries for some feature, and to make me a pretty table of pros and cons to skim. It's usually only 90% accurate, but it cuts my research time.

I do know how to drive Claude Code, and I have gotten it to build a non-trivial web front-end and back-end that isn't complete garbage without writing more than a couple of dozen lines myself. This required the same skill set as working with an over-caffeinated intern with a lot of raw knowledge, but who has never written anything longer than 1,000 lines before. (Who is also a cheating cheater.) Maybe I would use it more if my job was to produce an endless succession of halfway decent 5,000-line prototypes that don't require any deep magic.

Auto-complete plus Deep Research is my sweet spot right now.

We're at the point where I'm starting to hear this exact "backlash" sentiment from a lot of people. While I never went that far out of discomfort (I like understanding things) I do kind of respect the "effort" of willing to let go a bit. One reason probably also is that I tend up working in large Unity projects which are as incompatible for letting AI "take the wheel" as projects come.

That aside, I wonder if the OP would have had all the same issues with Grok? In several uses I've seen it surprisingly outperform the competition.

20+ years dev here, started coding with AI when Javis was still a thing (before it became Jasper, and way before Copilot or ChatGPT).

Back then, Javis wasn’t built for code, but it was a surprisingly great coding companion. Yes. It only gave you 80% working code, but because you had to get your hands dirty, you actually understand what was happening. It didn't give me 10x but I'm happy with 2x with good understanding on what's going on.

Fast-forward to now: Copilot, Cursor, roo code, windsurf and the rest are shockingly good at output, but sometimes the more fluent the AI, the sneakier the bugs. They hand you big chunks of code, and I bet most of us don't have a clear picture of what's going on at ground 0 but just an overall idea. It's just too tempting to blindly "accept all" the changes.

It’s still the old wisdom — good devs are the ones not getting paged at 3am to fix bugs. I'm with the OP. I'm more happy with my 2x than waking up at 3am.

I noticed a funny thing a while back after using the “bird’s eye view” capability in my car to help with parallel parking: I couldn’t parallel park without that feature anymore after a few years. It made for an awkward situation every time I visited the Bay Area and rented a car. I realized I had become so dependent on the bird’s eye view that I had lost the ability to function without it.

Luckily in this particular case, being able to parallel park unassisted isn’t all that critical in the overall scheme of things, and as soon as I turned that feature off, my parking skills came back pretty quickly.

But the lesson stuck with me, and when LLMs became capable of generating some degree of functioning code, I resolved not to use them for that purpose. I’m not trying to behave like a stodgy old-timer who increasingly resists new tech out of discomfort or unfamiliarity—it’s because I don’t want to lose that skill myself. I use LLMs for plenty of other things like teaching myself interesting new fields of mathematics or as a sounding board for ideas, but for anything where it would (ostensibly) replace some aspect of my critical thinking, I try to avoid them for those purposes.

Same thing with GPS, I lost the ability to memorize routes.