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Critical Claude Code vulnerability: Deny rules silently bypassed because security checks cost too many tokens

Clause Code security bypass: Anthropic's performance fix silently disabled deny rules for 500K+ developers when more than 50 subcommands were used in a command, impacting permission validation and security policy enforcement. The vulnerability stemmed from a tradeoff between security and performance.. read more  

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Scaling MCP adoption: Our reference architecture for simpler, safer and cheaper enterprise deployments of MCP

Cloudflare centralized MCP servers in a monorepo. It added governed templates, Cloudflare Access auth, audit logs, and DLP behind an MCP server portal. It launched Code Mode to collapse many tool schemas into two portal tools. Token use fell ~94%. Cloudflare Gateway now finds shadow MCP servers... read more  

Scaling MCP adoption: Our reference architecture for simpler, safer and cheaper enterprise deployments of MCP
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China has ‘nearly erased’ America’s lead in AI

Stanford HAI's 2026 AI Index shows China cut the U.S. lead inArenascores. In March 2026,Claude Opus 4.6ledDola‑Seed 2.0by 2.7%. A 2.7% margin is a photo finish. China outpaces the U.S. inpublicationcitations (20.6% vs 12.6% in 2024) and inindustrial robots(~295,000 vs 34,200). It also holds surplusc.. read more  

China has ‘nearly erased’ America’s lead in AI
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Anthropic releases Claude Opus 4.7, narrowly retaking lead for most powerful generally available LLM

Anthropic has unveiled Claude Opus 4.7, a powerful large language model that outperforms key rivals like GPT-5.4 and Google's Gemini 3.1 Pro in benchmarks such as agentic coding and financial analysis. Opus 4.7 leads the market on the GDPVal-AA knowledge work evaluation with an Elo score of 1753 and.. read more  

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I Measured Claude 4.7's New Tokenizer. Here's What It Costs You.

Anthropic's Claude Opus 4.7 migration guide states the new tokenizer utilizes "roughly 1.0 to 1.35x as many tokens" compared to 4.6. Actual measurements show a higher ratio on technical docs and real CLAUDE.md files. The cost of the new tokenizer was measured using real content and synthetic samples.. read more  

I Measured Claude 4.7's New Tokenizer. Here's What It Costs You.
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Figma's next-generation data caching platform

Figma rearchitected their storage systems to support scalability, including horizontally sharding their Postgres stack and building FigCache, a stateless proxy service for Redis. FigCache decouples connection scalability from Redis, centralizes traffic routing, enhances security, and provides end-to.. read more  

Figma's next-generation data caching platform
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Shell Tricks That Actually Make Life Easier (And Save Your Sanity)

This post provides a collection of lesser-known terminal tricks that can improve productivity and efficiency when working in various POSIX shells. The tricks cover a range of functions, from efficient text manipulation to file operations and script writing. By incorporating these tips into daily wor.. read more  

Shell Tricks That Actually Make Life Easier (And Save Your Sanity)
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Don’t trust, verify

Daniel Stenberg, creator of curl, argues that software security should be built on verification rather than trust, outlining the many ways a widely used project like curl could be compromised - from malicious insiders and breached credentials to hacked distribution sites and CI tool exploits. To cou.. read more  

Don’t trust, verify
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Reducing our monorepo size to improve developer velocity

Dropbox cut itsmonorepofrom 87GB to 20GB. It ran a GitHub‑approved server‑sidegit repack, tuned bywindow/depth. Clone times dropped to under 15 minutes. Engineers traced growth to Git’s 16‑char path heuristic. That heuristic mispairedi18nfiles. They tested--path-walklocally, then ran phased replica .. read more  

Reducing our monorepo size to improve developer velocity
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A Couple Million Lines of Haskell: Production Engineering at Mercury

Mercury runs ~2M lines ofHaskellin production. They choseTemporalto replace cron and DB-backed state machines. Durable workflows replace brittle coordination. They open-sourced aHaskellSDK forTemporal, wired inOpenTelemetryhooks, and pushed records-of-functions plus domain-error types... read more  

A Couple Million Lines of Haskell: Production Engineering at Mercury
Vertex AI is Google Cloud’s end-to-end machine learning and generative AI platform, designed to help teams build, deploy, and operate AI systems reliably at scale. It unifies data preparation, model training, evaluation, deployment, and monitoring into a single managed environment, reducing operational complexity while supporting advanced AI workloads.

Vertex AI supports both custom models and foundation models, including Google’s Gemini model family. It enables organizations to fine-tune models, run large-scale inference, orchestrate agentic workflows, and integrate AI into production systems with strong security, governance, and observability controls.

The platform includes tools for AutoML, custom training with TensorFlow and PyTorch, managed pipelines, feature stores, vector search, and online and batch prediction. For generative AI use cases, Vertex AI provides APIs for text, image, code, multimodal generation, embeddings, and agent-based systems, including support for Model Context Protocol (MCP) integrations.

Built for enterprise environments, Vertex AI integrates deeply with Google Cloud services such as BigQuery, Cloud Storage, IAM, and VPC, enabling secure data access and compliance. It is widely used across industries like finance, healthcare, retail, and science for applications ranging from recommendation systems and forecasting to autonomous research agents and AI-powered products.