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Public story · 2026-03-04 · source-backed
Beyond binary human-vs-machine detection: identifies which specific LLM generated a code snippet. Enables vulnerability triage (which model produced the bug?), licensing audits, and distillation detection. Directly relevant to the Anthropic distillation crackdown. (arXiv 2603.04212)
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1. Flip your multi-model pipeline to review-then-generate. Instead of using a reasoning model to plan before code generation, let the specialist generate freely and use reasoning tokens for review. Paper shows 90.2% pass@1 vs 87.2% for the planning pattern. Source 2. Audit you...
Go rotate a key. I'll wait. Claude Code 2.1.246, released August 25, lists this in its changelog: a fix for "telemetry and metrics requests to Anthropic carrying the API key configured for a third-party gateway (ANTHROPIC_BASE_URL); a credential is now only sent to its own hos...
poetiq.ai — Detailed technical breakdown of how a $40K-hardware startup achieved 54% on ARC-AGI-2 (vs. Google's 45% at nearly 3x the cost). The key innovation: "learned test-time reasoning" — an iterative refinement meta-system where solutions are generated, receive structured...
Anthropic's own docs confirm prompts, model responses, tool results (which include code Claude reads) and session transcripts still travel to and are retained by Anthropic. Inference can't be routed through Amazon Bedrock, Google Cloud's Agent Platform, Microsoft Foundry, or a...
The help-center doc confirms models launching on or after August 2, 2026 weave an imperceptible watermark into generated text plus C2PA-signed provenance metadata on image files. Model-level means it's present across the API, Claude, Claude Code, Claude Cowork, and through AWS...
For two years the technique was accumulation. Longer system prompts, longer CLAUDE.md, more numbered do/don't lists, more "always verify your work" imperatives. Anthropic's context-engineering guidance for Claude 5 models inverts it, with an 80% deletion figure attached. The s...
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