A VC explains an indispensable daily use case for AI: inputting the names of people attending a dinner or meeting and having the AI generate bios and backgrounds. This replicates a key function of a chief of staff, leading to richer, more informed conversations.

For 60 years, software digitized physical filing cabinets into databases, improving data retrieval but not the work itself. The current AI wave represents a paradigm shift where software (the "filing cabinet") can now autonomously perform tasks, evolving from a system of record to a system of action.

Power users are building personal AI assistants not just by feeding data, but by creating curated context layers. This involves exporting all digital communications (email, Slack), then using LLMs to create tiered summaries (e.g., monthly chief-of-staff briefs) to give agents deep, usable context.

The next wave of AI tools, like the prototype Nebula, will operate in the background. By connecting to work apps like Slack or GitHub, they will anticipate needs and proactively generate summaries, meeting prep docs, and updates without being asked.

Recent updates from Anthropic's Claude mark a fundamental shift. AI is no longer a simple tool for single tasks but has become a system of autonomous "agents" that you orchestrate and manage to achieve complex outcomes, much like a human team.

The primary interface for AI is shifting from a prompt box to a proactive system. Future applications will observe user behavior, anticipate needs, and suggest actions for approval, mirroring the initiative of a high-agency employee rather than waiting for commands.

An executive created a custom AI agent to handle repetitive tasks like meeting prep, calendar triage, and email. This "chief of staff" provides analysis, suggests delegations, and even offers blunt feedback, demonstrating how AI can be personalized to augment executive functions.

Tools like Granola.ai offer a key advantage by recording locally without joining calls. This privacy, combined with the ability to search across all meeting transcripts for specific topics, turns meeting notes into a queryable knowledge base for the user, rather than just a simple record.

Clawdbot can autonomously identify market trends (like X's new article feature), propose new product features, and even write the code for them, acting more like a chief of staff than a simple task-doer.