2025 is the year of the AI Brain, as a16z calls it.

One of the biggest human challenges is articulating the context behind our thoughts, emotions, and decisions. Much of our cognition is unstructured data, making it difficult to communicate effectively.

What if we could externalize our thoughts into a structured, understandable format? LLMs now enable this by extracting insights from vast information, summarizing key takeaways, and preserving context.

This “brain export” concept has profound implications—enhancing personal reflection, decision-making, and even interpersonal communication. By recording and analyzing our cognitive patterns, we can optimize both personal growth and professional efficiency, fundamentally reshaping how we process and convey knowledge.

AI can bridge this gap by acting as an ever-present cognitive assistant, mapping our thought processes and structuring them for optimal clarity. Imagine an AI companion that has observed every step of your experience—understanding your reasoning, emotional context, and preferred communication style. It could help you articulate complex ideas concisely, adapting messages based on past interactions with the recipient or their own AI assistant.

1. Consider, if you're co-parenting, an AI could suggest phrasing that minimizes misinterpretation and aligns with previous discussions.

2. Similarly, in professional settings, AI can serve as a memory augmentation tool—recalling decisions made months earlier, summarizing rationales, and surfacing alternatives considered.

3. Imagine an AI assistant for (long-distance) couples that can help you understand each other better, act as a health monitor - take actions like booking an appointment or reminding taking medicines, and also help in dispute resolution.

Beyond self-awareness, AI also addresses a fundamental human limitation: memory. It can surface forgotten context, helping to counter biases in recall. For example, I once worried that a colleague was upset with me due to a terse message.

The very same can be applied to application interactions as well. This extended memory has powerful professional applications as well. AI can track and retrieve information across conversations, projects, and research.

The concept of an “AI brain” has clear real-world applications, but current AI models like ChatGPT are not fully optimized for this role. While effective as a general assistant, they lack key functionalities necessary for a true personal or professional AI companion. Current limitations include rudimentary memory, the inability to view your screen, lack of proactive engagement, and constraints in input modalities (text and voice only).

Imagine an app that instantly understands your preferences—your DoorDash feed aligns with your taste and budget, shopping recommendations match your style, and your dating app suggests only genuinely compatible matches. Instead of endless scrolling, you get precisely what you need, with the flexibility to adjust. 

You control your “AI brain,” deciding which apps can access your data and how. This could revolutionize personalization, cutting through the noise of overwhelming choices in food delivery, travel, entertainment, and shopping, finally making recommendations truly relevant.

For an AI companion to be truly effective, it should ingest and process information across multiple modalities—text, image, and audio. Users will have different interaction preferences: some will text, others will prefer voice calls, and many will simply send screenshots for real-time analysis. Whether this manifests as an app, a hardware product (e.g., smart glasses or a pendant), or something else remains an open question.

In professional settings, AI must have real-time visibility into user workflows to provide meaningful assistance. While this level of integration may seem intrusive today, similar skepticism surrounded location tracking and facial recognition before they became mainstream.

An always-on AI that passively observes emails, Slack messages, and other digital activity could drastically improve efficiency by surfacing relevant context on demand.

A key design question remains: Should AI brains be horizontal—one system integrating work and personal life—or vertical, with separate instances for different domains? A unified AI makes sense, as work and personal contexts often overlap, but consumer comfort levels may dictate a gradual transition toward this model.

Export Your Brain: How I Uploaded Myself to AI (by a16z)