TL;DR

In two days, I shipped an open-source, cross-platform desktop AI English-speaking tutor: EchoWise.

Built end-to-end with Vibe Coding / Agentic Engineering.

Why EchoWise

Almost every English-learning app on the market teaches you to study English: flashcards, drills, scores, leaderboards. But what I actually needed when I was learning English wasn’t more learning — it was more using.

Stop studying English. Start using English.

EchoWise is built on the opposite philosophy:

• Communication before perfection — Imperfect English that connects beats perfect grammar that stays silent
• Relationship before knowledge — Polite stranger on Day 1, easy old friend by Day 30. Your AI companion’s tone evolves naturally with the day count
• Gentle nudges, never interruptions — The AI never lectures mid-reply. Scores sit quietly in the corner of your bubble — one glance when you want them
• Local-first — Every conversation, recording, and AI voice playback stays on your machine. Nothing is uploaded

What EchoWise actually does

The whole product revolves around one core idea: a companion that grows with you.

🗣️ A companion that grows

You give them a name, pick an avatar, choose a voice, write a persona. EchoWise tracks the Day count and maps the relationship into 5 tiers: Stranger → Acquaintance → Familiar → Friend → Old friend. The AI’s tone follows naturally — polite stranger on Day 1, the kind of old friend who teases you and remembers what you said by Day 30.

🎙️ Voice-first conversation

Hold the mic to record, release to transcribe; type when you can’t talk. The AI’s reply comes back as a voice-message-style bubble — tap the waveform to play. Don’t want to listen? Click “Show transcript” for the text. The whole flow feels like a normal messaging app, not a drill exercise.

💡 Coaching that never interrupts

The most annoying anti-pattern is an AI that breaks mid-conversation to lecture you about “you should have used the present perfect here.” EchoWise refuses to do that.

• The AI never mixes grammar lectures into its replies
• After every sentence you say, a 1–100 score chip appears in the corner of your bubble, in 5 color bands:
  • 🔴 Try again (< 50)
  • 🟠 Getting there (50–59)
  • 🟡 Clear (60–69)
  • 🟢 Natural (70–89)
  • ⭐ Native-like (90+)
• Tap the chip to see original / better / native-like + a short note
• Don’t tap? Keep talking. It never interrupts you

📈 Growth that actually means something

Not “how many words you reviewed today,” but:

• Confidence trend — rolling average of your last 5 sentences, updates as you talk
• 5-band distribution — where do your sentences cluster
• Auto-picked “best so far” and “worth revisiting”

Open the Growth view and see at a glance that you’re getting better. That positive feedback loop beats streak-counting any day.

🎨 Full appearance customization

Theme (system / light / dark), 4 fonts, 4 sizes, 6 preset gradient backgrounds — or upload your own image. Each companion can have their own avatar and background, too.

🔌 Multi-provider

OpenAI / Azure OpenAI in one click. Defaults to gpt-5 + gpt-4o-transcribe + gpt-4o-mini-tts. TTS voice instructions adapt dynamically to the companion’s persona — a lively companion gets a more energetic voice, a calm one gets a quieter delivery.

💾 Fully local

SQLite database + filesystem. Every conversation, every recording you made, every AI voice clip — lives on your machine forever, never uploaded to any server.

About the “two days”

The entire build was a Vibe Coding / Agentic Engineering workflow: I focused on product decisions and architectural judgment, the AI handled implementation and grind work.

My job:

• Decide what features ship, how the UX should flow, how many tiers in the relationship arc
• Judge whether the architecture holds, whether an abstraction is worth it, where bugs actually live
• Write the PRD, iterate on UX, review PRs

The AI’s job:

• Write React components, call Tauri APIs, write unit tests
• Tune Vite / Cargo / Tailwind config
• Edit GitHub Actions workflows, fix CI failures
• Propose improvements, catch my mistakes

After two days, this is what the product looked like:

Try EchoWise

• GitHub: https://github.com/hujiulin/EchoWise
• Download: Releases page has macOS .dmg and Windows .msi
• Setup: Built-in OpenAI and Azure OpenAI presets — drop in your own API key and you’re talking

macOS note: the first time you open it you’ll see “Apple could not verify…”. That’s because I haven’t paid for an Apple Developer ID ($99/year) for notarization. Open System Settings → Privacy & Security → scroll to the bottom → click Open Anyway once, and you’re done forever. Full steps are in the README.

If you enjoy it, a ⭐ on the EchoWise repo is very welcome — it helps more people find it. Feedback, bugs, ideas — open an Issue or PR on GitHub.