Just Now Possible

Building Todoist Ramble: How Doist Turned Voice Braindumps into Real-Time Task Capture

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Guests

  • Ernesto Garcia, Front-end Product Engineer, Doist
  • Thomas Jost, Backend Software Engineer, Doist
  • Hugo Fauquenoi, Product Manager, Doist

    • In this episode

    • How Doist's 2-3 month AI exploration phase led to Ramble — and why voice-to-task emerged as the top contender
    • The user research insight behind Ramble: people using pen and paper or ChatGPT voice to brainstorm tasks before committing them to Todoist
    • Why Ramble skips transcription entirely and processes raw audio directly with a Gemini live audio model
    • How the model makes tool calls (add task, edit task, delete task) in real time while the user is still speaking — no text output at all
    • Designing for the driving use case: sound effects as audio confirmation cues alongside visual task cards
    • The challenge of teaching an LLM to capture tasks literally without over-interpreting or doing them — and how temperature tuning played a role
    • Date handling complexity: injecting the current date, normalizing to days vs. months, and always outputting dates in English for the natural language parser
    • Building an LLM-judge eval system with 20+ language recordings from 100+ employees across 35 countries to catch prompt regressions
    • Why Doist chose to inject the full project/label list into the system prompt instead of building a RAG pipeline — and why it worked
    • How easy correction beats perfect first-time accuracy in natural language interfaces
    • What's next: multimodal task capture from images and text blobs, Apple Watch support, and automation integrations

      • Resources & Links

      • Todoist
      • Doist
      • Google Vertex AI (Gemini)

        • Chapters:

        00:00 Meet the Doist Team
        01:40 What Doist Builds
        02:27 Ramble Voice to Tasks
        04:16 Why Voice Matters
        07:42 Brain Dump Insight
        09:46 Prototyping With LLMs
        11:08 Live Audio Workflow
        14:32 Driving Friendly UX
        18:47 Tool Only Architecture
        26:06 Evals and Multilingual Testing
        28:41 Taming Dates and Time
        33:28 Fixing Date Confusion
        33:43 Defining Task Boundaries
        34:34 Capture Versus Do
        37:17 Tuning Creativity Levels
        39:01 Evals Across Languages
        41:23 Feedback and Regressions
        44:09 Model Upgrades Over Time
        46:33 Projects Labels Context
        51:40 Handling Ambiguous Names
        54:23 Whats Next Multimodal
        58:48 From Capture to Execution
        59:46 Closing Thoughts

        ...more
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        Just Now PossibleBy Teresa Torres