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- Hacker News
- From the article: "merge with at most one human in the loop, who can be the author". Curious to see how this handles enterprise compliance requirements and insider threats?
- How was this approved for SOC2 compliance? Our SOC2 reviewer explicitly mentioned that all code needs to reviewed by at least one other human before it goes to production. Claude Code says they are SOC2 compliant (https://code.claude.com/docs/en/security).
- This assumes all engineers will not do anything malicious. What is preventing a Claude engineer from spying on their ex's or some other companies Claude searches by pushing malicious code? Recently an OpenAI engineer was caught planting a recording device at their own office.
by gaal_dornick - > Low - Docs, copy, internal-only features, additive changes behind a flag
> None required once automated review and security checks are green
How anybody can let an LLM write docs and not even read them is pure insanity.
by koolba - Anthropic has amazing models. But they should really stop commenting on software practices. Most of what they say seem out of touch with what's happening in software shops. A lot of it seems hype driven. And the entire message looks to be written by AI.by TNWin
- And so the wildly unprofitable AI company explains how it token maxes it's code and review process.
Authors should really try and view this article from the perspective of someone who has to think about cost to use the models.
- The ownership component is the toughest and least enjoyable part of coding with ai. AI saves the time of coding, but 100% of the responsibility remains on you. You then have to invest an imbalanced amount of time to understand and fix the issue vs the time it took to generate the code. Then on top of that is the emotional feeling of something you “owned” messed up, but it wasn’t really your doing - it was the AI that did the keyboard work and now I need to parent/manage the AI. This destroys trust in AI and the cycle restarts. But we keep coming back to the slot machine as we often get those returns where things just work, but like gambling, you’re not satisfied by those wins and you’re immediately on to looking for the next fleeting high.by squidlib
- No wonder most people at Anthropic believe our jobs are in jeopardy, they've already made a system wherein the machines are treating them like pets.
I really don't get the tendency here from Anthropic to describe what's most likely churn? A high pressure amount of changes/PRs a day on a TUI to wrap a while loop? I'm not going to be a reductionist here so I'm going to cut it off there, I'm positive that the complexity of handling multiple terminal emulators is something that needs some handling (even if doing their own rendering engine was a self made problem). Yes I've vibe coded my own harness from scratch without writing any of it, I still know how it works.
I'm also not sure that they addressed point 2 in any actual capacity? They say "the system verifies itself" which is cool and is something that automated testing has done for decades, but they eschew the mental model of how the system works as a whole and prefer instead to have the LLM focus and summarize a slice of the system when they need to know about it or ask for it. But.... That's not knowledge? That's just search a la google? And thus seems to be subject to the same problems where the quality of your search dictates the quality of your knowledge that you surface at any given time?
N.B. Changed "1000 PRs" to "A high pressure amount" to be vague since the article is vague here on what CC undergoes.
by status_quo69 - I saw someone say the other day (in response to another blog post being well written) that Anthropic employees have a rule against using AI for writing/external comms? That seems clearly not the case here, normal people don't write like this:
> Most of the path is automated; a person's attention goes where the risk is
> The eval grows with every incident, and every change to the reviewer is scored against all of it.
by mk12 - This is like one of Google’s infrastructure blog. Google scale things are only relevant and appropriate for them. We had lots of bitter lessons from smaller engineering teams following the process with the justification that “this is how Google does it”.
Similarly, Anthropic can afford to do this because they have virtually unlimited tokens and labs to train models for their specific usecase. The rest of us need code comprehension lest we become dependent on continuous supply of tokens (which is a state these labs badly want to achieve)
So, unless you work at a lab, or have unlimited tokens guaranteed through the life of your company, it would do both the company and you good to continue to read the code and not let these 30k PRs per engineer be the norm.
An excerpt from the article makes my point
> Nobody on the team keeps a complete mental model of Claude Code in their head, and we don't think anyone needs to. When someone wants to understand a part of the codebase, they ask Claude to write an explainer for exactly that slice. It takes minutes and reflects the code as it is today.
by avinoth