alt Hacker NewsThis is also my experience. Everything I’ve ever tried to vibe code has ended up with off-by-one errors, logic errors, repeated instances of incorrect assumptions etc. Sometimes they appear to work at first, but, still, they have errors like this in them that are often immediately obvious on code review and would definitely show up in anything more than very light real world use.
They _can_ usually be manually tidied and fixed, with varying amounts of effort (small project = easy fixes, on a par with regular code review, large project = “this would’ve been easier to write myself...”)
I guess Gas Town’s multiple layers of supervisory entities are meant to replace this manual tidying and fixing, but, well, really?
I don’t understand how people are supposedly having so much success with things like this. Am I just holding it wrong?
If they are having real success, why are there no open source projects that are AI developed and maintained that are _not_ just systems for managing AI? (Or are there and I just haven’t seen them?...)
Replies
I worry about people who use this approach where they never look at the code. Vibe-coding IS possible but you have to spent a lot of time in plan mode and be very clear about architecture and the abstractions you want it to use.
I've written two seperate moderately-sized codebases using agentic techniques (oftentimes being very lazy and just blanket approving changes), and I don't encounter logic or off-by-one errors very often if at all. It seems quite good at the basic task of writing working code, but it sucks at architecture and you need occasional code review rounds to keep the codebase tidy and readable. My code reviews with the AI are like 50% DRY and separating concerns
Yeah, it sounds like "you're holding it wrong"
Like, why are you manually tidying and fixing things? The first pass is never perfect. Maybe the functionality is there but the code is spaghetti or untestable. Have another agent review and feed that review back into the original agent that built out the code. Keep iterating like that.
My usual workflow:
Agent 1 - Build feature Agent 2 - Review these parts of the code, see if you find any code smells, bad architecture, scalability problems that will pop up, untestable code, or anything else falling outside of modern coding best practices Agent 1 - Here's the code review for your changes, please fix Agent 2 - Do another review Agent 1 - Here's the code review for your changes, please fix
Repeat until testable, maybe throw in a full codebase review instead of just the feature.
Agent 1 - Code looks good, start writing unit tests, go step by step, let's walk through everything, etc. etc. etc.
Then update your .md directive files to tell the agents how to test.
Voila, you have an llm agent loop that will write decent code and get features out the door.