Assuming 10x on the speed of dev, Is the vscode repo a decent example? Recently they've been all in on AI augmented development so i'm thinking they'd be a reasonable subject?
How do you isolate out what counts as the "development" part of their delivery cycle (is that the dev inner loop, does that show up in frequency of commits then?) to measure it and see if it's running 10x?
https://github.com/microsoft/vscode/graphs/contributors?from...
AI is not delivering 10x shareholder value, anywhere. Software developers have quite the level of hubris about how important they are to companies. Yes our work is very complex and takes a certain mindset to do it well. It takes a lot of other roles to have a successful business, many of those roles will use AI to help draft slide decks, emails, etc. and that's the limit for them.
Look at recent companies doing layoffs claiming its because of AI, like CloudFlare and Coinbase, do their reported financials paint the picture that they are crushing it with AI? No, its net losses into the $100's of millions.
One of the latest things I made with Claude was a tool that allowed me to move a bunch of very low traffic Cloud Run services to a single VPS without losing any of the Cloud Run benefits such as easy Docker-based deployment and automatic certificate provisioning. I thought about making something like that for quite some time, and Claude finally made it possible, which makes me quite happy.
The fun thing here is that no other soul genuinely cares about it, or any other code I might publish. The code, especially AI generated, is so cheap that if anyone wants to repeat my steps to get rid of Cloud Run services, they will probably vibe-code their own tool instead of figuring out how to use mine, just like I did that instead of spending time on learning Dokku or similar solutions.
So, yes, 10x and more, but no one cares about the result, which makes the whole 10x measurement less useful.
I build things I never would have. My tooling is better and more robust than ever. I verify and test my work better than ever. I fix more bugs than I used to simply because no one needs to care if it fits into a cycle. I explore and solve more problems in more parts of the application, even if I don’t write code. I take better care of our infrastructure. Performance goes up, bugs go down, AWS resources scale back, costs go down. I’ve paid for my AI usage in scaled back resources several times over at this point.
It might not be 10x but it’s a significant multiple.
It's when they practically ignore the rabbit holes where it's suspect. I'm definitely seeing speed ups. I troubleshot a linux system yesterday with minimal effort using a local llm. It likely would have taken me a few hours to locate all the docs & testing procedures. the llm did it with only a few prompts. To ensure it did it correctly, I had to interrogate it a few times before letting it proceed.
Humans make really bad scientists, and it takes a lot of effort to properly catalog and provide statistics for these things.
There is an improvement, but I doubt any random dev can give a real estimate since before LLMs they couldnt really give you a real estimate anyway. I do know when I encounter a bug now, debugging is almost immediately possible.
Direct github link: https://github.com/open-noodle/gallery
Nothing wrong with forks though.
I've always been a backend engineer, never front end. And almost every team I've been on has lacked any front end skills at all, so all our tools end up being a mash of scripts, maybe sometimes an API.
Now we are all front end engineers creating UIs for things we could never do before, and this starts API first development, so the CLI + UI are just calling APIs. Nothing new here, but this used to be what teams do, now a single person does it.
1. I would not have attempted this without AI assistance because it's a big project.
2. I have built a functional program that I am able to use for real work in a handful of weeks, working part time on this (like literally a few hours per day prompting Claude and Kimi).
3. Had I decided to do this without AI assistance it would have been months of work.
https://github.com/KeibiSoft/KeibiDrop
It took me 2 years ago around 2k hours to build a cross platform FUSE vault, without using AI assisted tools.
The pain was debugging through logs and system traces. And understanding how things work.
Now managed to ship this one much faster, as an after hours project. Started it in may 2025, and around end of November 2025 started using claude on it.
Just by dumping logs into claude, and explaining the attack vector for the problems, saved me the FML moments of grindings walls of syscalls on 3 platforms.
I would say much easier to progress, and ship with the same rigour, minimize my time, focus and brain power involvement such that I can put the energy somewhere else.
Trying to fix syntax errors in strong interpolation on a 5-minute-delay loop is hell.
So my agent just listens for green checks and no PR comments and loops until those conditions are met.
Might tend to deviate and waste time, needs guiding once in a while, and to check what is it spewing out, point it in the correct direction.
If I had to output the code myself, would take around 8 hours of constant writing to get around 1k LoC of code. For FUSE level tricky stuff, I might need to spend 3 weeks for 10 LoC. Very easy to burnout and build pain.
Complete frontend + backend + database.
Yes, it is an internal app, but it works and everyone loves it.
Does that count as an example?
(Also I absolutely expect him to need help at some point, but so far it has taken his project from absolutely impossible to 3 weeks of work in between work, renovating his house and being a dad for the first time so I was very impressed.)
We decided to integrate our SaaS into Microsoft Business Central and NetSuite as plugins into those systems. BC has its own programming language, called AL, that has a lot of idiosyncrasies from any other language I've worked with. And NetSuite plugins are written in SuiteScript, which is a custom JS runtime with a ton of APIs to learn.
In the "before", it would've taken 5 developers a year or more to build those integrations. I did both by myself in well under a year. Thank you Claude.