The microphone is the first thing that breaks
The speech models were never our biggest source of production issues. Audio capture was. A Bluetooth headset can connect, report itself ready, and then never deliver a single audio buffer. A microphone can disconnect mid-sentence. macOS can route audio somewhere unexpected the moment another device appears.
Alder’s answer is to trust evidence, not status: recording doesn’t count as started until audio actually arrives, input levels are normalized across devices, and a device disconnect is detected instead of silently producing an empty take. If the signal is silence or noise, Alder says so — it will not hand you an empty result and call it success.
Interruptions must not destroy the take
People quit apps mid-sentence. Macs sleep. Sessions get interrupted. Alder writes dictation audio crash-safely while you speak, so an interrupted session leaves a recoverable recording instead of nothing. On the next launch, Alder notices the orphaned take and offers to process it — the thought you spoke yesterday is still there today.
The promise is simple: you spoke it, you keep it. Everything else is implementation detail.
Bad output is blocked before it reaches you
Reliability isn’t only about keeping audio — it’s about refusing to deliver garbage. Local speech models can produce pathological output on silence or noise. Alder quality-gates the transcript before insertion: output that fails those checks is blocked rather than typed into your document. Cleanup is held to the same standard — it removes high-confidence fillers and repeats, and preserves your meaning instead of rewriting it.
Delivery is verified, never assumed
The last step is the most delicate: putting text where you meant it. Before inserting, Alder checks that the app where you started dictating still has focus. If you switched apps mid-transcription, the result is not typed into the wrong window — it stays on the result card, visible and ready to place. If a field blocks insertion entirely, the result remains available to copy, and your history keeps every take.
None of this shows up in a feature list, and that’s the point — it’s the engineering that makes the feature list true. For how the models themselves are chosen and delivered, read Why Alder runs multiple speech models and The hard part of on-device AI isn’t inference.