Stet vs Chrome Skills

Open-source, local-first transcription with BYOK is the right architecture. I've been burned by voice tools that upload my audio to servers I can't audit. The voice profile approach for preserving style is technically interesting — I want to see how it handles domain-specific jargon and code-switching between formal and casual registers.

The multi-tab Skill execution is actually clever for bulk workflows — run a content extraction prompt across 10 research tabs at once. Limited to Gemini only right now, but the slash-command UX is well thought out and makes AI workflows feel native rather than bolted on.

The 'sounds like you' promise needs a lot of data to actually deliver — your voice profile is only as good as the writing samples it's trained on, and most people don't have a consistent, large corpus of their own writing. For casual dictators, this might just be Whisper with extra steps. Apple's built-in dictation is free and surprisingly good now.

This is Google locking you deeper into their ecosystem and making switching browsers more costly over time. Your carefully curated Skills library becomes a migration barrier. Also, English-US only at launch in 2026 is baffling for a product with global ambitions.

Voice-first computing is coming back, and the arms race for authentic AI writing assistance is heating up. The distinguishing factor won't be transcription accuracy — everyone has solved that — it will be voice fidelity. Stet is building in the right direction: local processing plus personal style models. Expect this architecture to be standard in two years.

The browser as an ambient computing layer — this is the long game. Skills today are prompts, but in two years they'll be multi-step agentic workflows that span apps. Google is quietly building the infrastructure for a browser that acts on your behalf. Pay attention.

This is genuinely exciting for writers and content creators. The homogenization of AI-assisted writing is a real aesthetic problem — everything starts sounding like the same LinkedIn post. A tool that actively fights that tendency by learning your specific voice is solving the right problem. Even if the voice model needs work, the direction is exactly right.

The ability to save and reuse creative workflows — summarize competitor landing pages, generate caption variations, extract color palettes from shopping sites — is legitimately useful for creative research. The remix-from-community-library feature is the hidden gem here.