Remi_Etien

Interesting list. One thing I've noticed while talking to founders across Europe: the adoption gap often isn't about features but discoverability and network effects. A European tool can be technically superior but loses because everyone's already on the US alternative. For early validation work especially, the switching cost rarely justifies the gains unless there's a specific regulatory or latency requirement. Worth considering what actual lock-in exists vs perceived lock-in.

The agent architecture here reminds me of challenges we hit building voice AI for startup validation — the gap between what works in benchmarks and what actually handles the messiness of real conversations is huge. One thing we learned: multi-turn context management and graceful error recovery matter way more than raw reasoning capability. Curious if you're seeing similar patterns with Qwen3.6-Plus in production deployments?

25MB is impressive. What's the tradeoff vs the 80M model — is it mainly voice quality or does it also affect pronunciation accuracy on less common words?