​How do we innovate our products and processes in a world that is uncertain and constantly changing? ​How can we be innovative in risk-intelligent ways?

It’s a question we’ve been asking ourselves and other leaders in our community.

Recently, we hosted a private leadership dinner bringing together product design, UX research and engineering leaders from Pinterest, Notion AI, Scribd, Zendesk, Google, Calendly, Carta and more to explore the limitless potential of AI to shape business innovation and creative work.

Our guest Linus Lee, Research Engineer at Notion AI, emphasized the concept of "inventing at the margins." This involves harnessing AI's potential for innovation within existing product frameworks, rather than starting entirely from scratch. Linus advocates for maintaining connections between new ideas and existing work to ensure continuity and relevance.

Linus shared his three principles for fostering innovation in a rapidly changing AI landscape.

1. Explore Broadly

Linus stresses the importance of managing variance exploration, which involves embracing uncertainty and taking calculated risks. He highlights the need to strike a balance between high-reward, high-variance exploration and structured, predictable processes. Linus envisions exploration as dynamic, minimally structured, and high-variance, with gradual introduction of constraints as the process moves toward product development.

2. Measure Periodically

Linus discusses the challenge of measuring progress in exploration. It recommends creating a map of the explored space by documenting attempts, learnings, and insights, even if they don't lead to tangible product releases. Research sprints lasting one to two weeks, centered around specific design or technical questions, help structure the exploration process. The production of artifacts like decision documents and prototypes helps capture and reinforce knowledge gained.

3. Double Down on the Winners

In his discussion, Linus emphasizes investing in internal tools to streamline workflows and enhance productivity, particularly for engineering teams. It advocates for recognizing the value of tool development and its contribution to innovation. The development of AI-based tools, such as summarization and note-taking apps, can further amplify efficiency and collaboration.

Listen to the full talk to hear Linus Lee's insights on leveraging AI's potential within existing frameworks, managing uncertainty, measuring progress, and investing in tools to enhance productivity and foster innovation.

Linus Lee
Research Engineer, Notion AI