Personal AI shouldn’t be a passive Q&A box—it should be a proactive mentor.

One direction I’m exploring is agents that efficiently gather high-quality context and surface insights proactively, instead of waiting for perfect questions. When AI is purely reactive, answer quality is capped by question quality. If users can’t frame the right question, the AI won’t deliver the right answer—and its potential goes unused.

Recently, I noticed an exponential effect in my language learning: as my level rises, I learn faster. After recognizing this pattern, conversations with GPT-5 sparked a wave of ideas. Without that recognition—or a proactive nudge—those insights wouldn’t have happened. This experience shapes how I think about AI product design.

What a proactive agent needs #

A context engine to pull trusted, opt-in signals (notes, calendar, docs, portfolio, learning history).

Semantic memory to track patterns and hypotheses over time.

Timely triggers that deliver the right insight at the right moment.

Privacy by design so users stay in control.

Enterprises already benefit from this approach: Palantir delivers context-rich, proactive decision support to operators. I believe there’s a huge gap for individuals—a “Palantir-for-One” that helps learners, professionals, and investors expand awareness and unlock potential.