Compare/Asana vs Stet

AI tool comparison

Asana vs Stet

Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.

A

Productivity

Asana

Manage your team's work, projects, and tasks

Skip

33%

Panel ship

Community

Free

Entry

Asana is a mature project management tool with portfolios, goals, workload management, and robust reporting. Strong for cross-functional teams but complex to set up well.

S

Productivity

Stet

Local macOS dictation that sounds like you — not like generic AI prose

Ship

75%

Panel ship

Community

Free

Entry

Stet is an open-source macOS dictation app that transcribes speech locally and then uses AI to clean up the output while actively preserving your personal writing style and tone. The core innovation is a voice model — a lightweight profile that learns from your past writing so the AI corrections don't flatten your voice into generic AI-ese. The result is meant to sound like you dictated it, not like it was passed through a generic LLM. The technical approach combines local Whisper-based transcription (nothing leaves your device during speech-to-text) with an optional AI refinement pass that can use your own API key (BYOK) or a $6.99/month subscription. The open-source release includes the voice profiling code, making it auditable and forkable. It's a direct response to Wispr Flow, which is closed-source and subscription-only. For writers, podcasters, and productivity users who dictate significant amounts of content, the voice preservation angle is genuinely differentiated. The proliferation of AI writing tools has created a recognizable 'AI voice' — flat, over-structured, and devoid of personality — that sophisticated readers are increasingly adept at detecting. Stet's bet is that preserving your actual voice is the most valuable thing an AI writing assistant can do.

Decision
Asana
Stet
Panel verdict
Skip · 1 ship / 2 skip
Ship · 3 ship / 1 skip
Community
No community votes yet
No community votes yet
Pricing
Free tier, Premium $13.49/user/mo
Free (BYOK) / $6.99/mo
Best for
Manage your team's work, projects, and tasks
Local macOS dictation that sounds like you — not like generic AI prose
Category
Productivity
Productivity

Reviewer scorecard

Builder
45/100 · skip

API is decent but the tool itself is overkill for dev teams. Linear or GitHub Projects do the job with less overhead.

80/100 · ship

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.

Skeptic
45/100 · skip

Another PM tool in a sea of PM tools. The AI features feel bolted on. Fine if you're already using it, not worth switching to.

45/100 · skip

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.

Creator
80/100 · ship

Portfolio views and workload balancing are essential for agencies managing multiple client projects simultaneously.

80/100 · ship

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.

Futurist
No panel take
80/100 · ship

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.

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