Packaging AI Pipelines So They Actually Get Reused
Daniel has a working podcast pipeline: a language model writes scripts, retrieval tools feed it, and text-to-speech reads it out. But the occasional Hebrew word keeps breaking things, and the pipeline itself is trapped in his head. This episode digs into two questions at once — how to handle Hebrew code-switching in TTS, and how to package a chained AI workflow so it survives past the project that spawned it. We talk through script-based segmentation versus small classifiers, why unvocalized Hebrew makes TTS inherently unstable, the tradeoff between chaining small models and using one large…
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