Where is the "super upvote button" when you need it?

YES! I have been playing with vibe coding tools since they came out. "Playing" because only on rare occasions have I created something that is good enough to commit/keep/use. I keep playing with them because, well I have a subscription, but also so I don't fall into the fuddy-duddy camp of "all AI is bad" and can legitimately speak on the value, or lack thereof, of these tools.

Claude Code is super cool, no doubt, and with _highly targeted_ and _well planned_ tasks it can produce valuable output. Period. But, every attempt at full-vibe-coding I've done has gotten hung up at some point and I have to step in an manually fix this. My experience is often:

1. First Prompt: Oh wow, this is amazing, this is the future

2. Second Prompt: Ok, let me just add/tweak a few things

10. 10th prompt: Ugh, everytime I fix one thing, something else breaks

I'm not sure at all what I'm doing "wrong". Flogging the agents along doesn't not work well for me or maybe I am just having trouble letting go of the control and I'm not flogging enough?

But the bottom line is I am generally shocked that something like Gas Town was able to be vibe-coded. Maybe it's a case of the LLM overstating what it's accomplished (typical) and if you look under the hood it's doing 1% of what it says it is but I really don't know. Clearly it's doing something, but then I sit over here trying to build a simple agent with some MCPs hooked up to it using a LLM agent framework and it's falling over after a few iterations.

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dceddia an hour ago | parent [-]

So I’m probably in a similar spot - I mostly prompt-and-check, unless it’s a throwaway script or something, and even then I give it a quick glance.

One thing that stands out in your steps and that I’ve noticed myself- yeah, by prompt 10, it starts to suck. If it ever hits “compaction” then that’s beyond the point of return.

I still find myself slipping into this trap sometimes because I’m just in the flow of getting good results (until it nosedives), but the better strategy is to do a small unit of work per session. It keeps the context small and that keeps the model smarter.

“Ralph” is one way to do this. (decent intro here: https://www.aihero.dev/getting-started-with-ralph)

Another way is “Write out what we did to PROGRESS.md” - then start new session - then “Read @PROGRESS.md and do X”

Just playing around with ways to split up the work into smaller tasks basically, and crucially, not doing all of those small tasks in one long chat.

	▲	joshstrange 41 minutes ago \| parent [-]
		I will check out Ralph (thank you for that link!). > Another way is “Write out what we did to PROGRESS.md” - then start new session - then “Read @PROGRESS.md and do X” I agree on small context and if I hit "compacting" I've normally gone too far. I'm a huge fan of `/clear`-ing regularly or `/compact <Here is what you should remember for the next task we will work on>` and I've also tried "TODO.md"-style tracking. I'm conflicted on TODO.md-style tracking because in practice I've had an agent work through everyone on the list, confidently telling me steps are done, only to find that's not the case when I check its work. Either a TODO.md that I created or one I had the agent create both suffer from this. Also, getting it update the TODO.md has been frustrating, even when I add it to CLAUDE.md "Make sure to mark tasks as complete in the TODO.md as you finish them" or adding the same message to the end of all my prompts, it won't always update it. I've been interested in trying out beads to see if works better than a markdown TODO file but I haven't played with that yet. But overall I agree with you, smaller chunks are key to success.