Granola’s success stems from deliberate, counterintuitive choices: rejecting meeting bots and audio storage to prioritize discretion and trust; cutting 50% of features pre-launch to preserve simplicity; and anchoring its entire product around meetings—not email—as the richest, most actionable source of contextual data. Built without ML PhDs, it leverages best-in-class third-party models (OpenAI, Anthropic, Google) with dynamic routing and rigorous internal eval tooling to maintain a consistent 'voice' despite model volatility. Transcription—not LLM tokens—remains its largest cost driver, shaping infrastructure decisions like on-device echo cancellation and partnerships with Deepgram and Assembly. The team prioritized a year of stealth onboarding, continuous user calls (4–6/week), and calendar-triggered habit loops—recognizing that retention hinges on reliable triggers like scheduled meetings, not just value. Looking ahead, Granola is evolving from notes toward cross-meeting insights, self-updating documents, and even AI coaching—always grounded in augmenting human cognition, not replacing it.