<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Zylver Case Studies</title><description>Zylver methodology applied to real production AI systems. Each study includes the problem, the approach, the measurements, and what we would do differently.</description><link>https://zylver.com/</link><language>en-us</language><item><title>Coordinating 327 specialized agents in one production environment</title><link>https://zylver.com/case-studies/internal-forge-multi-agent/</link><guid isPermaLink="true">https://zylver.com/case-studies/internal-forge-multi-agent/</guid><description>How Zylver Forge orchestrates a hierarchical multi-agent system in our daily development environment, with full observability, cost caps, and policy hooks per agent role.</description><pubDate>Wed, 22 Apr 2026 00:00:00 GMT</pubDate><category>Forge</category><category>AI Engineering</category></item><item><title>Cutting our own AI bill 73% with intelligent distillation</title><link>https://zylver.com/case-studies/internal-meter-distillation/</link><guid isPermaLink="true">https://zylver.com/case-studies/internal-meter-distillation/</guid><description>How Zylver Meter applied to our internal AI usage identified 327 high-frequency prompts and converted them into deterministic functions, eliminating 73% of repeated inference spend without changing developer ergonomics.</description><pubDate>Wed, 15 Apr 2026 00:00:00 GMT</pubDate><category>Meter</category><category>AI Engineering</category></item></channel></rss>