Successful B2B AI companies create "dashboard" products that become the daily home screen for a worker's core task, like Graphite for code review. This "cockpit" approach captures user workflow and attention, proving more valuable than "pipes" infrastructure that runs invisibly in the background.

In AI acquisitions, a startup's underlying technology is less important than its "workflow proximity." Atlassian's AI head advises buyers to assess how deeply a tool is integrated into a user's fundamental daily tasks. A tool central to a core workflow is far more valuable and defensible than a specialized, peripheral one.

Instead of relying solely on top-down, consultant-led workflow automation, enterprises should empower individual employees with AI tools. This builds user fluency and intuition, allowing them to pull AI into their own workflows, resulting in greater overall impact and less disempowerment.

Simply offering the latest model is no longer a competitive advantage. True value is created in the system built around the model—the system prompts, tools, and overall scaffolding. This 'harness' is what optimizes a model's performance for specific tasks and delivers a superior user experience.

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.

An impressive AI capability, like a multi-language voice agent, is a differentiator that can be copied. Lasting defensibility is achieved not by the AI feature itself, but by embedding it within an end-to-end workflow that becomes the system of record for the user.

User workflows rarely exist in a single application; they span tools like Slack, calendars, and documents. A truly helpful AI must operate across these tools, creating a unified "desired path" that reflects how people actually work, rather than being confined by app boundaries.

The race in enterprise AI isn't just about agent capabilities, but about owning the central dashboard where employees direct agents across all applications (Salesforce, Jira, etc.). Companies like OpenAI and Microsoft are vying to become this primary interface, controlling the customer relationship and relegating other apps to the background.

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.