The Principles for Building Excellent AI Features with Superhuman’s Lorilyn McCue
Nov 7, 2024
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Lorilyn McCue, Product Manager at Superhuman, discusses her journey from Apache helicopter pilot to leading AI features in email. She shares the importance of a 'learning-first' approach and leveraging user feedback to create practical tools like Ask AI and instant replies. The conversation explores balancing on-demand versus always-on AI features, prompt engineering for effective summarization, and the seamless integration of AI into user workflows. Lorilyn emphasizes the need for continuous improvement and staying updated in the fast-evolving AI landscape.
Superhuman's success in building AI features hinges on a continuous learning approach that prioritizes user feedback for ongoing optimization.
Seamless integration of AI into the user experience ensures that users naturally engage with AI tools, enhancing productivity without awareness of the technology.
Deep dives
Key Principles for AI Development
The primary principles emphasized are focusing on optimized learning and seamless integration of AI into products. Optimized learning involves creating lightweight mechanisms to test functionalities with both internal and eventually external users, enhancing the ability to gather user feedback. Seamless integration means that AI features should be so embedded in the user experience that users engage with them without even realizing they’re using AI. The ideal scenario is when users encounter efficiency improvements and utilize AI features intuitively, enabling them to focus on more meaningful tasks.
AI Features of Superhuman
Superhuman, an email client aimed at enhancing productivity, incorporates several AI features designed to streamline user workflows. Notable features include 'Write with AI', which generates full emails from short prompts, and 'Instant Reply', allowing quick responses to straightforward emails. The 'Auto Summarize' feature provides one-line summaries of emails upon receipt, while 'Ask AI' allows users to query their inbox for specific information efficiently. These features collectively reduce the time users spend on email management, enhancing their overall productivity.
Challenges in AI Feature Development
Developing AI features such as those in Superhuman comes with unique challenges, particularly when considering user interaction with the AI. Features like 'Always On' summarization require high-quality processing while managing costs and latency. Ensuring the AI generates contextually appropriate responses—such as avoiding irrelevant replies to farewell emails—requires extensive testing and optimization. The team’s continuous learning, driven by user feedback, helps refine these features and tackle complex edge cases effectively.
Iterative Development and Feedback Integration
The development process for AI features at Superhuman involves an iterative approach where features are released in stages, beginning with internal testing and progressing to broader user betas. Internal teams are encouraged to rigorously test and provide candid feedback, facilitating the discovery of edge cases and enhancements. User input is also gathered through a curated beta group to identify areas for improvement. This approach emphasizes the importance of agility in product development, allowing the team to adapt and enhance features dynamically based on real-world usage.
How do you build AI tools that actually meet users’ needs? In this episode of High Agency, Raza speaks with Lorilyn McCue, the driving force behind Superhuman’s AI-powered features. Lorilyn lays out the principles that guide her team’s work, from continuous learning to prioritizing user feedback. Learn how Superhuman’s "learning-first" approach allows them to fine-tune features like Ask AI and AI-driven summaries, creating practical solutions for today’s professionals.
00:00 - Introduction 04:20 - Overview of the Superhuman 06:50 - Instant Reply and Ask AI 10:00 - Building On-Demand vs. Always-On AI Features 13:45 - Prompt Engineering for Effective Summarization 22:35 - The Importance of Seamless AI Integration in User Workflows 25:10 - Developing Advanced Email Search with Contextual Reasoning 29:45 - Leveraging User Feedback 32:15 - Balancing Customization and Scalability in AI-Generated Emails 36:05 - Approach to Prioritization 39:30 - Real-World Use Cases: The Versatility of Current AI Capabilities 43:15 - Learning and Staying Updated in the Rapidly Evolving AI Field 46:00 - Is AI Overhyped or Underhyped? 49:20 - Final Thoughts and Closing Remarks
-------------------------------------------------------------------------------------------------------------------------------------------------- Humanloop is an Integrated Development Environment for Large Language Models. It enables product teams to develop LLM-based applications that are reliable and scalable. To find out more go to humanloop.com
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