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Deep, recent reads ranked by depth and freshness.

  1. Cutting our inference bill by 68% by being obsessive about optimization

    An engineering team investigated a steady rise in AI code review costs and found that cache misses and redundant model calls were driving up expenses. By restructuring system prompts to enable cross-repository prompt caching, eliminating wasted tool calls, and switching to more efficient models, the team cut inference costs by 68% while also significantly improving review latency.

    DEPTH ■■■■■15 min read6 days ago

    Machine Learning

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  2. Rewinding the exponential: How we keep hardware usage down

    Cloudflare tackled exponential traffic growth against linear hardware growth by continuously evolving their data pipeline architecture over five years. Key optimizations included breaking up monolithic schemas, switching to zstd compression, decoupling pipeline transit from database replication, decentralizing sampling, and moving aggregations earlier in the pipeline. These strategies significantly reduced backbone bandwidth usage, network congestion, and storage requirements while preserving data quality.

    DEPTH ■■■■■12 min read12 days ago

    Infrastructure

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  3. How Commerce.com and Cloudflare are getting storefronts ready for AI agents

    Commerce.com and Cloudflare collaborated to enable WebMCP at the edge for nearly 100,000 storefronts, allowing AI agents to interact reliably with e-commerce sites using structured tools rather than fragile HTML scraping. The team implemented edge-level configuration rules using custom hostname metadata to provide individual merchants with a seamless opt-out mechanism and added support for custom MCP paths. This integration allows agents to execute shopping tasks directly within the active browser session while ensuring fallback safety and zero extra latency for opted-out stores.

    DEPTH ■■■■■6 min read4 days ago

    Machine Learning

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