AI workflow
Prompting by Voice
Most prompts fail from missing context, not missing syntax. Voice is a fast way to provide richer context, constraints, and intent without breaking focus.
Four-part spoken prompt structure
- Objective: what the model should produce.
- Context: relevant domain facts and constraints.
- Format: exact output shape.
- Quality bar: acceptance criteria or checks.
Refinement loop
Dictate v1 quickly, review model output, then dictate only the missing constraints as a concise follow-up.
This avoids over-editing and keeps each iteration explicit.
Why voice helps prompt quality
Speaking encourages complete thought blocks, which usually improves prompt clarity versus fragmented typing.
Benchmark qualifier
Based on Almond internal testing (February 15, 2026): same 20-second spoken phrase, measured from end of dictation to visible final text result versus Wispr Flow and other cloud-first dictation models.
- Test date: 2026-02-15
- Input: Same 20-second spoken phrase
- Metric: Elapsed time from end of dictation to visible final result
- Comparison group: Wispr Flow and other cloud-first dictation models
Related resources
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