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I've been using Claude Code heavily for about 3 months now, and I'm pretty sure I'm between 10 and 20 times more productive while using it. How I measure performance is how many features I can implement in a given period of time. It's nice that people have done studies and have opinions, but for me, it's 10x to 20x better.
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There are definitely swings. Last night it took about 2 hours to get Monaco into my webpack built bootstrap template, it came down to CSS being mishandled and Claude couldn't see the light. I just pasted the code into ChatGPT o3 and it fixed it first try. I pasted the output of ChatGPT into Claude and viola, all done. A key skill is to sense when the AI is starting to guess for solutions (no different to human devs)…
Is there a way to have two agentic AIs do pair programming?
It would be interesting to set up a MCP style interface, but even me copy/pasting between windows was constructive.
The time this worked best was when I was building a security model for an API that had to be flexible and follow best practices. It was interesting seeing ChatGPT compare and contrast against major API vendors, and Claude Code asking the detailed implementation questions.
The final output was a pragmatic middle-ground between simplistic and way too complex.
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I find the swings to be wild, when you win with it, you win really big. But when you lose with it, it's a real bite out of your week too. And I think 10x to 20x has to be figurative right, you can do 20x by volume maybe, but to borrow an expression from Steve Ballmer, that's like measuring an airplane by kilograms. Someone already operating at the very limit of their abilities doing stuff that is for them high comple…
> Someone already operating at the very limit of their abilities doing stuff that is for them high complexity, high cognitive load, detail intense, and tactically non-obvious? When you zoom in, even this kind of work isn't uniform - a lot of it is still shaving yaks, boring chores, and tasks that are hard dependencies for the work that is truly cognitively demanding, but themselves are easy(ish) annoyances. It's thos…
Yeah, I'm not a dev but I can see why this is true, because it's also the argument I use in my job as an academic. Some people say "but your work is intellectually complex, how can you trust LLMs to do research, etc.?", which of course, I don't. But 80% of the job is not actually incrementally complex, it's routine stuff. These days I'm writing the final report of a project and half of the text is being generated by Gemini, when I write the data management plan (which is even more useless) probably 90% will be generated by Gemini. This frees a lot of time that I can devote to the actual research. And the same when I use it to polish a grant proposal, generate me some code for a chart in a paper, reformat a LaTeX table, brainstorm some initial ideas, come up with an exercise for an exam, etc.
What bothers me more than any of this particular discussion is that we seem to be incapable of determining programmer productivity in a meaningful way since my debut as a programmer 40 years ago.
what about the $ you make? isn't that an indicator? you've probably made more than me, so you are more successful while both of us might be doing the same thing.
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I find the swings to be wild, when you win with it, you win really big. But when you lose with it, it's a real bite out of your week too. And I think 10x to 20x has to be figurative right, you can do 20x by volume maybe, but to borrow an expression from Steve Ballmer, that's like measuring an airplane by kilograms. Someone already operating at the very limit of their abilities doing stuff that is for them high comple…
> Someone already operating at the very limit of their abilities doing stuff that is for them high complexity, high cognitive load, detail intense, and tactically non-obvious? When you zoom in, even this kind of work isn't uniform - a lot of it is still shaving yaks, boring chores, and tasks that are hard dependencies for the work that is truly cognitively demanding, but themselves are easy(ish) annoyances. It's thos…
When I said that after you've done all the other stuff, I was including cutting all the ridiculous bullshit that's been foisted on an entire generation of hackers to buy yachts for Bezos and shit.
I build clean libraries from source with correct `pkg-info` and then anything will build against it. I have well-maintained Debian and NixOS configurations that run on non-virtualized hardware. I use an `emacs` configuration that is built-to-specifications, and best-in-class open builds for other important editors.
I don't even know why someone would want a model spewing more of that garbage onto the road in front of them until you're running a tight, optimized stack to begin with, then the model emulates to some degree the things it sees, and they're also good.
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Unfortunately not, but ensuring the final code quality will be well written is a challenge I am putting off for now. I'm leaning into the future growth of AI capabilities to help me here, otherwise I'll have to do it myself. That is a tomorrow problem, too much project structure/functionality to get right first.
So you are more productive, as long as you don't have to consider code quality.
With most projects where innovation is a key requirement, the goal isn't to write textbook quality code, it's to prove your ideas work and quickly evolve the project.
Once you have an idea of how it's going to work, you can then choose to start over from scratch or continue on and clean up all the bits you skipped over.
Right now I'm in the innovation cycle, and having AI able to pick up whole API path strategies and pivot them, is incredibly amazing.
How many times have you used large API's and seen clear hands of different developers and URI strategies, with an AI, you just pivot.
Code quality and pen tests are critical, but they can come later.
Earlier quoted context omitted.
Unfortunately not, but ensuring the final code quality will be well written is a challenge I am putting off for now. I'm leaning into the future growth of AI capabilities to help me here, otherwise I'll have to do it myself. That is a tomorrow problem, too much project structure/functionality to get right first.
So you are more productive, as long as you don't have to consider code quality.
I've been using Claude Code heavily for about 3 months now, and I'm pretty sure I'm between 10 and 20 times more productive while using it. How I measure performance is how many features I can implement in a given period of time. It's nice that people have done studies and have opinions, but for me, it's 10x to 20x better.
Same, I’ve done stuff that should have taken me 2-3 weeks in days
I've been using Claude Code heavily for about 3 months now, and I'm pretty sure I'm between 10 and 20 times more productive while using it. How I measure performance is how many features I can implement in a given period of time. It's nice that people have done studies and have opinions, but for me, it's 10x to 20x better.
I cringe when I see these numbers. 20 times better means that you can accomplish in two months what you would do in 4 years, which is ridiculus when said out loud. We can make it even more ridiculous by pointing out you would do in 3 years the work of working lifetime (60 years) I am wondering, what sort of tasks are you seeing these x20 boost?
Claude code has made bootstrapping a new project, searching for API docs, troubleshooting, summarizing code, finding a GitHub project, building unit tests, refactoring, etc easily 20x faster.
It’s the context switching that is EXTREMELY expensive for a person, but costless for the LLM. I can focus on strategy (planning features) instead of being bogged down in lots of tactics (code warnings, syntax errors).
Claude Code is amazing, but the 20x gains aren’t evenly distributed. There are some projects that are too specialized (obscure languages, repos larger than the LLM’s context window, concepts that aren’t directly applicable to any codebase in their training corpus, etc). But for those of us using common languages and commodity projects, it’s a massive force multiplier.
I built my second iOS app (Swift) in about 3 days x 8 hours of vibe coding. A vocab practice app with adjustable learning profile, 3 different testing mechanisms, gamification (awards, badges), iOS notifications, text to speech, etc. My first iOS app was smaller, mostly a fork of another app, and took me 4 weeks of long days. 20x speed up with Claude Code is realistic.
And it saves even more time when researching + planning which features to add.
Earlier quoted context omitted.
I cringe when I see these numbers. 20 times better means that you can accomplish in two months what you would do in 4 years, which is ridiculus when said out loud. We can make it even more ridiculous by pointing out you would do in 3 years the work of working lifetime (60 years) I am wondering, what sort of tasks are you seeing these x20 boost?
It is amazing, cringe all you want :) I scoped out a body of work and even with the AI assisting on building cards and feature documentation, it came to about 2 to 4 weeks to implement. It was done in 2 days. The key I've found with working as fast as possible is to have planning sessions with Claude Code and make it challenge you and ask tons of questions. Then get it to break the work into 'cards' (think Jira, but…
If one of these things isn’t true, you’re either a fool or those productivity increases aren’t real.