I've been using LLMs to help with my software engineering work since ChatGPT originally came out.
When Anthropic released their Claude 3 series models, I was shocked at the code quality they produce and was able to get new projects running with minimal debugging.
I've been listening a lot of the big interviews from Dwarkesh with people like Demis Hassabis and some of the technical discussion around task execution gave me the inspiration to attempt creating a full AI Software Engineering system requiring only a text prompt.
It's not accurate enough to programmatically deploy, but seeing what the system can produce in 30mins-1hr has continually blown me away.
Unlike Devin, which is still in a 'waitlist period', saas-quick is available to use right now.
I'm a solo developer and the frontend isn't polished or anything, but you can follow along the process as each task is executed and download the project zip at the end.
I appreciate your time and am grateful for any feedback!
Desperately needs some examples of what it created or even a demo (maybe show the resulting app, and one file, pay for full repo). Need some signal this is worth it.
"Key Features
Cutting-edge repository generation powered by Claude 3
Flat rate fee for each project generation
Generates highly functional code that serves as a robust starting point
Minimal debugging required to deploy the generated code"
"Our advanced AI technology creates highly functional repositories that serve as a solid foundation for your projects".
I agree if there was a demo video it would clear up a lot of confusion. Or maybe screenshots/feature details on the landing page would help. The project page has an input box to describe your project, it writes all the files for the project, and then shows a download button for the zip. All projects are containerized with Docker and have configs that you'd want in a production deployment environment.
I think they have the M and V but not quite the P. P is proposition. Just needs a bit more info as to what to expect, some examples and perhaps social proof.
Got it! I have been trying to think of creative ways to show a demo video when it takes 30 min to an hour. I might try to a few timelapse/speedrun type clips for commonly cloned projects (like a Notion Clone). Thanks for the feedback
Andrej Karpathy, founding member of OpenAI and former Director of AI at Tesla, recently shared his thoughts on the future of programming:
The hottest new programming language is English
— Andrej Karpathy (@karpathy) January 24, 2023 https://twitter.com/karpathy/status/1617979122625712128?lang...
I've been using LLMs to help with my software engineering work since ChatGPT originally came out.
When Anthropic released their Claude 3 series models, I was shocked at the code quality they produce and was able to get new projects running with minimal debugging.
I've been listening a lot of the big interviews from Dwarkesh with people like Demis Hassabis and some of the technical discussion around task execution gave me the inspiration to attempt creating a full AI Software Engineering system requiring only a text prompt.
It's not accurate enough to programmatically deploy, but seeing what the system can produce in 30mins-1hr has continually blown me away.
Unlike Devin, which is still in a 'waitlist period', saas-quick is available to use right now.
I'm a solo developer and the frontend isn't polished or anything, but you can follow along the process as each task is executed and download the project zip at the end.
I appreciate your time and am grateful for any feedback!
"Key Features Cutting-edge repository generation powered by Claude 3 Flat rate fee for each project generation Generates highly functional code that serves as a robust starting point Minimal debugging required to deploy the generated code"
"Our advanced AI technology creates highly functional repositories that serve as a solid foundation for your projects".
I agree if there was a demo video it would clear up a lot of confusion. Or maybe screenshots/feature details on the landing page would help. The project page has an input box to describe your project, it writes all the files for the project, and then shows a download button for the zip. All projects are containerized with Docker and have configs that you'd want in a production deployment environment.