gck1

Heck, agents don't start editing before they're already at 70k for me.

I've played with explorer agents giving exploration summaries to help the implementer agents use more of their context for implementation, but it doesn't work as well. There's always something lost in the handoff.

This will absolutely not end well.

You seem to be putting a lot of weight on Anthropic employees being the smartest people in the world.

And I don't doubt that, not in the slightest. But I've seen exceptionally smart people in one field being dumber than a random kid from around the block in another.

This incident is clearly at least 2 failures that could've been easily avoided: failure to communicate, and failure to investigate the logs after letting the "most dangerous" roam free.

No, it doesn't require creating a mock internet with an alert as a side effect. Their own "most dangerous" model could have probably told them this happened if they supplied logs to it.

They had a model escape in April, roughly the same time when they were fearmongering about Mythos and how Anthropic should be the sole keyholder of cybersecurity capabilities, and it only occured to them to look inside logs when they saw someone else winning in their own game.

What, Anthropic didn't know model could escape sandbox without OpenAI reporting it?

They also gave access to Mythos (the Mythos) to some companies, based on... vibes.

Who knows how these companies are using it. If Anthropic can't effectively contain their own models, can the partners?

While the rest of us get fallbacks and warnings, not even being able to defend against the attacks they themselves are causing.

Do we really have to re-learn all the industry's knowledge the hard way?

> On July 21, OpenAI disclosed that several of their models had broken out of an isolated test environment

> In response to this incident, we began a large-scale retrospective review of our own cybersecurity evaluations

> we identified three incidents

> The incidents involved three different Claude models: [...] and an internal research test model

This reads like an attempt by Anthropic to re-secure their leading spot in "our models are the most dangerous and we also have unreleased, super-secret, research models" index.

I may be too cynical, but the well of benefit of the doubt is running very dry towards AI labs that like to engage in this game.

Recent-ish models learned to use the same trick engineers played on non-engineers, where they try to sound very smart by overcomplicating very simple concepts.

It's very taxing, especially since these are usually multi-paragraph texts. I noticed I've started doing a lot of "hey, you're talking gibberish again" a lot with 5.6 Sol.

They do have subagents, released v2 of that feature with the launch of 5.6 model series in fact. It's just... very poorly executed, is a significant regression from subagents v1 and thousands of miles behind subagents of Claude code.

- Models that can be launched as subagents are hardcoded (can only be another Sol or Terra, but not Luna). Most of the time it'll just launch same model as parent anyway.

- They encrypt initial task delegation from root agent to subagent, for whatever reason

- You can't switch into subagent view at all, despite the fact that apart from initial root>subagent task handoff, all session is visible in transcript.

It's funny how codex itself can't do Sol orchestrator / Luna implementor out of the box.

Luna is comparable to GPT 5.4 from 4 months ago on many benchmarks. I know many who have said during that time, myself included, that if that's the model they had to use for the rest of their lives, they'd be fine.

GPT 5.4 is/was a very capable model.

They're supposed to bring 5h today.

I did a full circle and essentially dropped all of my personal static workflows encoded in skills because I observed recent models picking better ad-hoc workflows for particular problems, when a static one would force a subpar one.

It seems like we all tried to contain and organize a system that simply prefers to select its own organization.

Which makes me to think that these skill packs of workflows are really made to make it easier for humans rather than agents.