Has anyone tried using Claude Code / Ralph Wiggum to package Cloudron apps?
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It sounds like if you get good at very clearly defining what you need done it's pretty good at just going off and doing it:
See for example this write-up which has prompted this thread:
https://www.second-breakfast.co/blog/ralph-is-eating-the-world@charlesnw had previously shared a
CloudronPackagePrompt.mdhe'd be using but that seems to have moved, but @canadaduane posted a copy of a version of it here: https://forum.cloudron.io/post/108425I'd guess that @timconsidine has been harnessing AI to do all the packaging he's being doing recently too and my have some insights to share?
And @marcusquinn seems to have lots of AI agents doing his DevOps as per his https://aidevops.sh/
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It sounds like if you get good at very clearly defining what you need done it's pretty good at just going off and doing it:
See for example this write-up which has prompted this thread:
https://www.second-breakfast.co/blog/ralph-is-eating-the-world@charlesnw had previously shared a
CloudronPackagePrompt.mdhe'd be using but that seems to have moved, but @canadaduane posted a copy of a version of it here: https://forum.cloudron.io/post/108425I'd guess that @timconsidine has been harnessing AI to do all the packaging he's being doing recently too and my have some insights to share?
And @marcusquinn seems to have lots of AI agents doing his DevOps as per his https://aidevops.sh/
@jdaviescoates very interesting links, thank you.
Need to read them again to fully digest.And yes, I use AI to assist packaging !
Due to illness, I've taken a break from my main project that will make me rich (ha ha ha), and so have had time to do some Cloudron packaging. AI has certainly helped.My experience is mixed, but increasingly very positive. Some of it aligns with the article you posted.
journey
- I tried AI as standalone resource which helped with individual tasks, but slow and inefficient, and no leverage obtained through building knowledge.
- then I discovered Windsurf as an IDE with integrated AI engines, and big gains from leveraging the conversation flow
- I fell out of love with Windsurf just prior to their acquisition because of coding mistakes and flawed implementations
- often this was actually when using Claude, which many rave about, but my experience has been that it is nothing to get too excited about
- I discovered TRAE and now use this IDE with their AI in auto-mode exclusively for projects, and other standalone engines for ad-hoc tasks, and for sanity checking TRAE, and for planning (mostly Ollama/qwen3-coder:480b-cloud). I forget exactly but I think TRAE has stopped using Claude.
learnings
- AI is magical .... except when it isn't
- detailed specification really does matter, but don't get bogged down, some things can be delegated to its discretion
- initially ban your AI from creating code (!!), ask it to plan the overall task, and then the sub-tasks
- actually, first tell e.g. Ollama what your plan is, and ask it as PlanAI to explain the task for your chosen DevAI, asking DevAI to scaffold overall and sub-tasks
- point out errors, misunderstandings (maybe due to unclear specification) and issue reminders (e.g. Cloudron RO/RW constraints), maybe asking for a revised plan, maybe asking DevAI to consider different approaches to arrive at a best approach
- then instruct DevAI to start coding to implement the agreed plan
- watch it like a hawk to keep it to the plan
- this methodology plays to my strengths (I'm not a pro-dev) and AI's strengths (getting hands dirty)
- intriguingly TRAE does seem to learn cross-project, I can be pleasantly surprised that in a later project, it seemed to learn from mistakes in a previous unrelated project
The whole AI as developer landscape is changing so fast. I am probably missing some tricks and new tools, and I struggle to keep up.
I don't currently buy into the "go to bed and wake up to a finished product" but maybe it will come ... or maybe I am missing something.
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@jdaviescoates very interesting links, thank you.
Need to read them again to fully digest.And yes, I use AI to assist packaging !
Due to illness, I've taken a break from my main project that will make me rich (ha ha ha), and so have had time to do some Cloudron packaging. AI has certainly helped.My experience is mixed, but increasingly very positive. Some of it aligns with the article you posted.
journey
- I tried AI as standalone resource which helped with individual tasks, but slow and inefficient, and no leverage obtained through building knowledge.
- then I discovered Windsurf as an IDE with integrated AI engines, and big gains from leveraging the conversation flow
- I fell out of love with Windsurf just prior to their acquisition because of coding mistakes and flawed implementations
- often this was actually when using Claude, which many rave about, but my experience has been that it is nothing to get too excited about
- I discovered TRAE and now use this IDE with their AI in auto-mode exclusively for projects, and other standalone engines for ad-hoc tasks, and for sanity checking TRAE, and for planning (mostly Ollama/qwen3-coder:480b-cloud). I forget exactly but I think TRAE has stopped using Claude.
learnings
- AI is magical .... except when it isn't
- detailed specification really does matter, but don't get bogged down, some things can be delegated to its discretion
- initially ban your AI from creating code (!!), ask it to plan the overall task, and then the sub-tasks
- actually, first tell e.g. Ollama what your plan is, and ask it as PlanAI to explain the task for your chosen DevAI, asking DevAI to scaffold overall and sub-tasks
- point out errors, misunderstandings (maybe due to unclear specification) and issue reminders (e.g. Cloudron RO/RW constraints), maybe asking for a revised plan, maybe asking DevAI to consider different approaches to arrive at a best approach
- then instruct DevAI to start coding to implement the agreed plan
- watch it like a hawk to keep it to the plan
- this methodology plays to my strengths (I'm not a pro-dev) and AI's strengths (getting hands dirty)
- intriguingly TRAE does seem to learn cross-project, I can be pleasantly surprised that in a later project, it seemed to learn from mistakes in a previous unrelated project
The whole AI as developer landscape is changing so fast. I am probably missing some tricks and new tools, and I struggle to keep up.
I don't currently buy into the "go to bed and wake up to a finished product" but maybe it will come ... or maybe I am missing something.
@timconsidine said in Has anyone tried using Claude Code / Ralph Wiggum to package Cloudron apps?:
initially ban your AI from creating code (!!), ask it to plan the overall task, and then the sub-tasks
This is part of the work flow outlined here too:
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The coding isn't really the hard part any more. The testing and decision-making still remains a human in the loop domain.
We're going in the right direction, though.
IMO it won't replace developers, it'll just mean developers move up the food chain for creating and managing value by guiding and overseeing coding and devops agents.
Testing and gotchya checking still remains reliant on human experience.
Plus, like flying, you always want to know there's a pilot with a stake in survival.
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This works because you're dealing with a pile of low quality training data.
This is why we use tons of water to flush sewage/dirt/etc until something we want (diamond/gold) is left over.
Subtractive process like a sculptor removing debris to reveal the statue within the rock.
Requires lots of filtering. Just like with Ralph Wiggum
