Hacker News Reader

Comment by samlinnfer | Hacker News Reader

And they are early adopters of the vibe coding paradigm, having a 100% Claude generated codebase.

I assume most of their outages is related to this insane scaling and lack of available compute.

Vibe coding doesn't automatically mean lower quality. My codebase quality and overall app experience has improved since I started using agents to code. You can leverage AI to test as well as write new code.

Well if we use Claude Code's code quality as a benchmark ...

After the CC leak last week I took a look at their codebase and my biggest criticism is they seem to never do refactoring passes.

Personally I write something like 80-90% of my code with agents now but after they finish up, it's critical that you spin up another agent to clean up the code that the first one wrote.

Looking at their code it's clear they do not do this (or do this enough). Like the main file being something like 4000 LOC with 10 different functions all jammed in the same file. And this sort of pattern is all over the place in the code.

How do you do the cleanup? Just /simplify or something you rolled yourself?

It's not an automated process (at least in my case). I primarily use Codex so I will do the initial pass with 5.3 or 5.4 xhigh and then cleanup with spark on medium or low.

Spark is great for this kind of cleanup work because the feedback loop is so tight compared to just about anything else. It's quite hampered by a very small context window but in the context of cleanup/refactoring that's more of a feature than a bug IMHO.

My suggestion for folks that want to do this is make sure you keep reasoning low. The cleanup should be very much human directed and derived from your "taste", at that point you don't want the model to think at all and just blindly do what you tell it to. You want reasoning to be just high enough so it doesn't eff up the code in the process.

I have a buddy who used to work at Shopify and was proud about having sprints dedicated to removing unused features. This is really underrated but is the only reliable way to prevent bloat. Oh and getting rid of bloat is way more satisfying!

If that works it's already built in the system

Isn't the whole selling point of AI agents that you now can do things like scale 3x without scaling your team accordingly?

I assume so. They're doing it with around 99% uptime.

Or, to put it another way, almost 2 9s.

I haven't seen anyone claim that applies to infrastructure or compute.

Since apparently LLMs have also conquered physics, “Claude, transmute this lead to gold for me.”

Yeah, it's almost like the point I was making is that everyone is overselling AI agents' capabilities.

I’m sure someone is out there claiming that AI is going to solve all your business’s problems no matter what they are. Remotely sane people are saying it will solve (or drastically improve) certain classes of problems. 3x code? Sure. 3x the physical hardware in a data center? Surely not.

Implying that software is somehow divorce from Infrastructure/compute efficiency and utilization isn't a claim I've seen many make either.

    > I assume most of their outages is related to this insane scaling and lack of available compute.
    > 
    > Vibe coding doesn't automatically mean lower quality

Scalability is a factor of smart/practical architectural decisions. Scalability doesn't happen for free and isn't emergent (the exact opposite is true) unless it is explicitly designed for. Problem is that ceding more of the decision making to the agent means that there's less intentionality in the design and likely a contributor to scaling pains.

My theory is that most of their outages are compute and scale related. IE. A few GPU racks blows out and some customers see errors. They don't have any redundant compute as backup because supply is constrained right now. They're willing to lower reliability to maximize revenue.

Why would you think that the person you are replying to didn't design in scalability? What exactly are emergent features when vibe coding? If scalability is an explicit requirement it can be done.

    >  What exactly are emergent features when vibe coding?

Regression to the mean. See the other HN thread[0]

The LLM has no concept of "taste" on its own.

Scalability, in particular, is a problem that goes beyond the code itself and also includes decisions that happen outside of the codebase. Infrastructure and "platform" in particular has a big impact on how to scale an application and dataset.

[0] https://dornsife.usc.edu/news/stories/ai-may-be-making-us-th...

This is only true for small companies that can infinitely scale within AWS without anyone noticing.

You are talking about software scaling patterns, Anthropic is running into hardware limitations because they are maxing out entire datacenters. That's not an architectural decision it's a financial gamble to front-run tens of billions in capacity ahead of demand.

Reply on news.ycombinator.com