
Anthropic built an inspection layer that lets enterprises block sensitive data before it reaches Claude
THE SO WHAT
Anthropic's inference hooks — routing every Claude Enterprise prompt through a customer DLP server — move data governance from "trust the vendor" to "enforce your own policy in-line." If you're blocked on LLM adoption over data leakage, this is the pattern to demand from every provider: pre-inference inspection, explicit allow/deny, and auditable hooks into your security stack.
READ THE SOURCE
MORE FROM THE WIRE
Applied AIMeta is offering a cheaper Muse Spark 1.2 "contributor" tier priced at $0.10/1M input and $0.20/1M output tokens in exchange for using user prompts for training
Meta is explicitly pricing data rights into its API — $0.10–0.20 per million tokens is the discount for letting your prompts become training fuel. If you’re building on third-party models, you now need a written policy on which workloads can opt into “contributor” tiers and which must stay on non-training SKUs.
Applied AIFigma’s push into AI agents drives an earnings beat
Figma is turning AI agents into a metered line item — AI credits — and it’s already moving the revenue needle. If your product is a daily workspace, the window to bolt on transactional AI usage before it gets bundled away by the platform layer is narrowing.
Anthropic confirmed it is designing custom chips for Claude. It wants engineers who have “shipped silicon.”
Anthropic moving into in-house silicon — and explicitly hiring people who’ve shipped chips — is another step toward vertically integrated AI stacks where model and hardware co-evolve. If you’re a heavy Claude customer, start asking roadmap questions about performance, deployment options, and how custom hardware might change your cost and latency curves over 12–24 months.
Applied AIThe Most Dangerous AI Hacking Techniques Still Have Humans in the Loop
The finding that the most potent AI-enabled hacking still relies on humans in the loop means threat models need to cover human–AI teaming, not just autonomous attacks. Security teams should be red-teaming with AI copilots themselves to understand how much capability a moderately skilled attacker can now wield.