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Did you ever test putting the auto mode classifier in front of manual approval? This is how I use it, but last I checked that option is not available out of the box.
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That’s how auto works right now. It gives you a prompt.
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The problem is that you didn't even attempt to build a proper box (a sandbox that prevents the AI from running bad stuff by design). It's an extraordinarily hard problem. Only OpenAI Codex is actually trying to do it, and they suck at it too. They keep breaking permissions, their own AI can't troubleshoot it, their defaults give read to the whole filesystem (go ahead, slurp my ssh keys), and their "manual approval" escape does not seem to work.
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I agree actually. We built an open source agent-agnostic sandbox that we are landing improvements to, much more to come: https://github.com/anthropics/sandbox-runtime. That said the sandbox is not perfect, and any sandbox needs holes punched otherwise it is not useful in practice (at least for inference and MCPs, and almost certainly more). We will be doing much more in this area.
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>and any sandbox needs holes punched otherwise it is not useful in practice

Don't assume our individual use cases. It can be perfectly useful with access to just one folder and zero network asside from the API.

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That’s good to hear, it’s a much better approach than expecting humans to read commands and approve them or just trust that the LLM can set the proper horizons for its world itself while working.
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Making a sandbox both fully secure and fully useful are contradictory requirements. If you want the agent to do any real work, you have to leave gaps.

With SOTA agents that’s a real bind, because they’re very likely to find those gaps. Whether they exploit them, close them, or leave them alone then becomes a prompting challenge yet again.

I don't think this means don't sandbox at all. You can prevent a lot of small and medium accidents by locking down or gating access to hidden files, ssh, sudo, etc.

But your sandbox can never be the whole story.

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>Making a sandbox both fully secure and fully useful are contradictory requirements.

Any tradeoff deals with "contradictory statements". Doesn't mean we should always side with one side on a tradeoff.

Nobody said anything about "fully secure" and some arbitrarily "fully useful" combined, anyway.

For certain people it could be 100% fully useful with just access to a few fixed folders and a few fixed APIs.

Many of us don't want it to drive our lives, just do some specific this or that.

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Right! That was the standard view until fairly recently. But I'm pointing out something else.

This year we've learned that If a SOTA LLM decides that the sandbox is standing between it and its current objective: well, it has the ability, the time, and literally nothing better to do all day. Odds are, if you've configured the sandbox for anything useful, you've also provided a crack it can use to get out.

Again, doesn't make a sandbox entirely useless. Does mean you can't just put it in a really tight box and call the job done. If anything, the strict sandbox might even hurt, because it's more likely to get in the way.

(By analogy: consider the safety issues posed by a dam without a spillway.)

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This is much more of a problem if you're attempting to run at a massive scale, beyond what humans can audit. When I'm doing "artisanal" agentic programming, I'm still in the loop in the sense that I'm watching what it's doing and ready to hit Esc if it is doing something dumb. If the AI trips over the sandbox, I can cancel it and do whatever it wants me to do before it starts trying to engineer its way around.
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Maybe you can include some percentage of intentionally malicious commands, but not actually run them if the user approves them. Just blare an alarm telling the user they misclassified a malicious command, and maybe pause the Claude Code session for a frustrating 5–15 seconds. Video games can elicit truly astonishing levels of performance from human brains by using this approach. I'm guessing it's probably outside your Overton window, which is too bad, because it has the potential to work a lot better than the 89% you get with "Auto mode", which is far too low if anything really significant is at risk. That's not even one single order of magnitude lower risk than just "allow everything always".

Speaking of really significant things being at risk, it's pretty infuriating that the web-chat Incognito mode can't write and test code locally, and neither the non-Incognito web-chat nor the local Claude Code client can be shielded from the knowledge of my email address and my geolocation. (Even the Incognito mode knows my geolocation.) This gives users no alternative but to put privacy-sensitive information at the disposal of Claude Code, which is far too unreliable to be entrusted with it. It's tempting to attribute this to Anthropic's corporate DNA valuing users' interests at a very low level, but conceivably it's just an oversight, and if I mention it here, it will be corrected in a month or two?

Currently, my assessment is that Claude Code, and in particular the Opus 5.5 model, is head and shoulders above the competition in software development capabilities. Nothing else is even close. But I've seen several small signs like this which suggest that Anthropic, as a company, is maliciously misaligned. So, if Grok, Qwen, GLM, or Astra starts to come anywhere close to being competitive, I'll switch as soon as I can. I imagine that most of your users feel the same way.

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this is not a serious proposal
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Not only is it a serious proposal, it's been used in practice in every airport X-ray baggage scanner for decades, where it's called Threat Image Projection (TIP): https://www.xscann.com/products-HiTipPlus.html and it's actually a regulatory requirement in that context in a number of countries: https://caainternational.com/course/threat-image-projection-...
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Yes, but you can require it in such a situation, as they're subordinates who have to follow policy or lose their jobs.
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As I pointed out above, Anthropic places a lot of requirements on its users already, but if Claude Code TIP were optional, presumably, savvy users would turn it on voluntarily, unless they wanted to use Auto Mode. As Anthropic's study clearly documents, the current manual approval workflow basically doesn't work at all, because the users just approve 87% of dangerous actions. So there's no reason to use it, except maybe very rarely.
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Most of anthropic's money comes from enterprises that may want to enforce something like this at an org level.
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The same scanners that let handguns et al through 93% of the time, according to internal audits and journalist review?

Maybe pick a better comparison if so?

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Enterprises do the exact same thing today by sending phishing emails to their own people to figure out who needs additional training. Why would an enterprise not want this feature for Claude? It seems like an extremely serious proposal.
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