Elle Wang

Elle Wang’s note-taking methodology focuses on structuring AI-generated information using critical frameworks. Core principles:

• Applies qec-framework (Question, Evidence, Conclusion) to transform raw information into actionable insights by explicitly framing questions, sourcing evidence, and deriving conclusions.
• Integrates la-approach (Limitations and Assumptions) to critically evaluate AI outputs, identifying hidden biases and contextual constraints.
• Optimizes AI tools by requiring structured inputs through QEC/LA, reducing hallucinations and increasing note utility.
• Implements whisper-transcription for audio-to-text transcription using Google Colab and OpenAI’s Whisper AI, achieving high accuracy without downloads (https://www.youtube.com/watch?v=ktNeWrkPwmg).

Video reference: https://www.youtube.com/watch?v=B1GOvWU90uw

2026 04 14 Elle Wang taking smart notes 2026 04 14 Elle wang audio to text transcription

Source Notes

• 2026-04-23: Engine Survival: The Critical Role of Oil Pressure and Warning Lights
• 2026-04-23: Engine Survival: The Critical Role of Oil Pressure and Warning Lights
• 2026-04-14: I Looked At Amazon After They Fired 16,000 Engineers. Their AI Broke Everything.
• 2026-04-14: [[lab-notes/2026-04-14-Optimizing-AI-Costs-and-Privacy-with-Local-Open-Source-Models-and-Hybr|“But OpenClaw is expensive…“]]