The root of the problem is that AI-as-a-service is corked, because companies providing it have a hell of an incentive to use all that data to out-compete their competitors, and they can do so in secret. To say nothing of salivating law-enforcement who really, really wants to tap into it. I'm hoping there will be at some point open-source and affordable hardware that can run competent models.

This policy applies across all providers. Here is the warning in Cursor: https://i.redd.it/7sfyker2ya6h1.png

Note that Anthropic has committed not to train models on logged data, so I don’t understand some of the concerns here. What exactly is your threat model? That Anthropic would train models contrary to their terms of service? That you trust them enough not to log your data prior to this, but not enough to trust their stated limits on how logged data will be used now?

This is odd behaviour, and provides some evidence that Anthropic isn't being managed by serious people. With this policy across AWS/GH/Zed/etc, they're taking their massive lead in enterprise/govt sales and handing it to any competitor who can serve a model anywhere near these capabilities with a modestly nice UI.

This smells like an advanced version of corporate espionage. Assuming most companies will use their AI in the future, this will be fed directly to an Echelon-like network that will be leaking "interesting info" to friendly parties, like the Boeing vs Airbus scandal that was first widely reported and then swept under the rug officially.

Pretty sure this doesn't work for any regulated enterprise or government client. But AWS knows this, so I am curious why they'd agree to it.

Ugh. I'm sure we're not the only company that's going to face the difficult decision to either stay with Opus 4.8, switch to a different model provider or update and significantly weaken our terms of service around no model re-training, not sending data to third parties and the like. I understand why Anthropic wants to do this but I'd be much more comfortable with it if the data never made it to Anthropic unless an analysis Amazon ran, maybe even using tools from Anthropic, determined that there was something to look at. That'd be an easier carve out in an enterprise Terms Of Service / Privacy Policy.

They want your data like you everybody else and enterprise data is juicy to say at least

That rules it out for all sorts of apps.

I've worked on a few apps for UKGov and I would absolutely be raising this as a massive red flag.

you've got to respect anthropic being willing to shoot themselves in the foot over a belief around Mythos performance

Same as for GitHub Copilot?

"For more on how Anthropic handles this data, see Anthropic’s commercial terms and data retention policy. Enabling the Claude Fable 5 policy constitutes acknowledgement of this requirement. Leaving it off keeps Claude Fable 5 unavailable to your organization."

https://github.blog/changelog/2026-06-09-claude-fable-5-is-g...

Is this also the case for Google Cloud? https://docs.cloud.google.com/gemini-enterprise-agent-platfo...

What I do is route general data to Mythos, and my own IP to a local model.

I expect them to train on their traffic, and I train on mine.

"Legally required" ... gotcha, script writing on Melania Movie 3 has begun in exchange for a national security letter requiring Amazon to both keep the data and not exclude it from training.

I guess this is an anti-distillation move?

They say it's opt-in but since they are capable of agreeing to this, I am just waiting until they hide this opt-in into the regular ToS when asking for a new model access...

Very confident. But will it stick? And if it doesn't -- what then? Back to scheming?

OpenAI ... your move. The enterprise market just cracked wide open. Do you want it?

Similar for GCP if anyone's wondering, and in fact a bit further in some ways: https://cloud.google.com/terms/advanced-ai-safety-addendum

60 days.

This is not going to fly in EU.

They want your data.

> After 30 days, the data is deleted automatically

Do we believe that?

> or we're legally required to keep it.

Aha - so, data is forever.

Note that if you use AWS Bedrock then you're choosing to pay 10X to 20X because you trust AWS more than Anthropic.

It is literally 10X to 20-X cheaper to directly buy Anthropic subscriptions for your devs.

Woah, if anthropic does it, even OpenAI would start doing the same with Azure models

This is BS. They want to train on user data.

> except in the rare cases where it's part of a safety investigation or we're legally required to keep it

So basically all your data will flow to NSA/CIA/Mossad if they show even slight interest in your org or you as a person. Gotcha.

it's either this or playing x30 for a token, anyhow i physically can't write code again

Got an email from Zed about the same this morning.

What a "frontier."

Because they didn't store data before? Don't be so naive.

My thesis is that in software you don't want aggregators. They provide the promise of vendor neutrality, but it comes at the expense of increased supply chain compromise risk, small print technically legal data exfiltration.

Even in the happy case where nothing bad happens, you get a badly integrated product, because you integrate not against the actual vendor, but against a abstraction layer that commoditizes the actual product, effectively forcing you to either use the least common denominator of features, or circumventing the actual aggregation model itself with some kind of 'vendor_specific_parameters' parameter in the aggregator API.

My thesis is drop the vendor neutrality, and build your integration with the vendor directly.

lol

[dead]

[dead]

aaaand there it is.

The data leaving AWS boundary kills this for any regulated workload. We've been running side-by-side evals of open models against Claude on private test suites, using Neo as the orchestration layer. Keeps everything in-house and gives us objective comparison data.

The regulated-enterprise angle is the interesting part. Bedrock's whole pitch to those customers was "your data never leaves your AWS boundary" — that's the line that gets it through procurement and compliance reviews. A 30-day retention requirement where traffic crosses into the vendor's boundary quietly invalidates that, and for healthcare/finance/gov it's not a knob they can flip no matter how good the model is. This is exactly why we keep our LLM layer provider-agnostic with a self-hosted fallback (Ollama-class models) for data-sensitive paths — you eat a capability hit, but you keep the option of not sending regulated data anywhere. The risk TZubiri names is real: the moment you're reaching for "vendor_specific_parameters," the neutrality you bought the aggregator for is already gone.

I understand the safety/misuse argument, but I wonder where enterprises will draw the line here. “30-day retention for advanced models” sounds reasonable in isolation, until you remember many teams are sending proprietary code, internal docs, or customer-sensitive context through these systems.

[dead]

Thinking about this from a product perspective: the best early-stage tools I've seen (including wyyno.com, a price comparison tool I'm building) succeed by solving a very narrow problem for a very specific user. The 'boring' use case of price comparison turned out to be compelling because the savings are tangible and immediate.