Current LLMs are intelligent enough for many tasks but fail because they lack access to complete context—emails, Slack messages, past data. The next step is building products that ingest this real-world context, making it available for the model to act upon.

Instead of merely 'sprinkling' AI into existing systems for marginal gains, the transformative approach is to build an AI co-pilot that anticipates and automates a user's entire workflow. This turns the individual, not the software, into the platform, fundamentally changing their operational capacity.

Grammarly's new agent is designed around three attributes: it works everywhere, it proactively offers help, and it's connected to user data across platforms. This trifecta creates a powerful, integrated user experience that feels seamless and intelligent.

Modern AI models are powerful but lack context about an individual's specific work, which is fragmented across apps like Slack, Google Docs, and Salesforce. Dropbox Dash aims to solve this by acting as a universal context layer and search engine, connecting AI to all of a user's information to answer specific, personal work-related questions.

Early AI adoption by PMs is often a 'single-player' activity. The next step is a 'multiplayer' experience where the entire team operates from a shared AI knowledge base, which breaks down silos by automatically signaling dependencies and overlapping work.

AI is best understood not as a single tool, but as a flexible underlying interface. It can manifest as a chat box for some, but its real potential is in creating tailored workflows that feel native to different roles, like designers or developers, without forcing everyone into a single interaction model.

Legacy systems like CRMs will lose their central role. A new, dynamic 'agent layer' will sit above them, interpreting user intent and executing tasks across multiple tools. This layer, which collapses the distance between intent and action, will become the primary place where work gets done.

Sam Altman's ultimate vision for software isn't AI-assisted messaging but a proactive agent. Instead of managing Slack, users will state their goals for the day, and the AI will handle communication and tasks, providing batched updates. This signals a shift from augmenting existing workflows to replacing them entirely.

To get mainstream users to adopt AI, you can't ask them to learn a new workflow. The key is to integrate AI capabilities directly into the tools and processes they already use. AI should augment their current job, not feel like a separate, new task they have to perform.