A deep technical analysis of Yodai's distributed architecture, examining the critical tension between moving AI analyzers from client-side to cloud infrastructure. This episode explores three major architectural decisions: migrating six code analyzers from the VS Code extension host to cloud MCP agents (and the privacy implications of shipping user code to infrastructure), the Deepgram Aura-2 TTS migration to Cloudflare Workers AI (and the resilience tradeoffs of single-vendor coupling), and WebSocket integration for real-time progress tracking in Durable Objects (and its connection scaling implications). The hosts dissect how performance optimization can obscure trust boundaries, how architectural coupling affects failure domains, and why designing privacy and resilience constraints early prevents costly refactors later. Essential listening for engineers building IDE extensions, distributed systems, or tools that process sensitive developer code.

In this episode:
00:10 - Why client-side AI analyzers drain your extension host
01:24 - Moving analyzers to the cloud: the privacy tradeoff nobody mentions
02:17 - Single-vendor AI inference: latency wins, resilience loses
03:43 - Real-time WebSocket progress and Durable Object connection limits

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Copy this prompt into Cursor to start implementing:

Based on my podcast episode "Durable Objects Architecture: Balancing Performance, Privacy, and Resilience", help me:
- Understanding software architecture principles
- Best practices in code organization

Analyze my codebase, identify the relevant files, create a plan, then implement the changes.