35M Users. $100M ARR. My 10-Year Bet Was Right. | Otter.ai, Sam Liang

Critique of Traditional Education and Loss of Voice Knowledge00:00

At Harvard University two days ago, many professors do not allow students to use tools like Otter for learning, which represents old thinking. The education system was created at least 100 years ago and must allow students to use AI tools. Although humans have been talking for thousands of years, most voice knowledge in history has been lost. We never heard Shakespeare or Charles Darwin, representing a tremendous loss of human knowledge and intelligence. These frustrations and insights led to the belief that voice AI will be huge in the future.

Introduction to Otter.ai and Company Evolution00:31

Sam Liang is co-founder and CEO of Otter.ai. Started as a transcription tool, evolved into an AI meeting assistant, and now building a meeting-centric enterprise knowledge base with Agentic workflows on top. Over 35 million users and exceeded $100 million ARR. Enterprises are adopting it to manage huge meeting content.

Background and Influences01:02

Did PhD at Stanford University. Learned from PhD advisor David Cheriton, who has vision for big impact and world-changing ideas. Cheriton recognized talent of Larry Page and Sergey Brin, writing a $100,000 check before they had anything. Learned to think big from him. At Google from 2006-2010, led Google Maps location platform. Quit in 2010 to start mobile startup in Palo Alto.

First Startup and Inspiration for Otter.ai02:02

First startup built the first location tracking system and persistent sensing on mobile devices to understand user behaviors for personalized mobile services. Company successfully acquired. In 2016, thinking about something new and bigger. While building first startup, had many meetings with investors, internal team, and customers. Hard to remember all meeting content and share knowledge with team. Needed a better way.

Initial Challenges and Vision for Recording Meetings02:30

In 2016, planned to record everything and enable sharing with team members. Most people uncomfortable: being recorded is uncomfortable, and sharing meeting notes uncommon since traditionally people take notes in personal paper notebooks. Anticipated mindset and culture would change, so built product to enable that change.

Product Adoption Curve03:01

You can convince some people, not everyone. New products follow adoption curve. Early adopters of Otter get value sooner, become more effective and productive, show value to colleagues, and help convince others. To go big, pick something most people haven't been convinced about yet.

Importance of Deep Technology03:31

Need deep technology roots to go big. From technology background, likes technologies and engineering. Revolutionary companies like Google built on deep technologies. Today, many APIs allow quick building of meeting note takers—even college students could do it. But in 2016 (10 years ago), waiting for APIs would mean being years late.

Building Own Speech Recognition04:03

Decided to build own speech recognition technology. Didn't know how long it would take, high risks, fewer resources than Google or Microsoft. What if they caught up fast? Choice to build deep technologies to create new revolution. Differentiation is biggest problem for startups.

Advantages of Owning Technology04:32

From day one, belief in owning technology: keeps costs low, allows more free service (third-party APIs costly). Still deep problems requiring AI scientists, e.g., using hundreds of millions of voice data to model human conversation and multi-speaker interactions in meetings—unsolved problems. Cannot rely on third-party APIs; must build own deep AI stack.

If it's too easy for you to build, it's very easy for 100 other people to build as well.

Behavior Changes with New Technologies05:31

Behavior changes with new technologies. Before internet common, emails felt forever, but Slack popularity reduced emails. With mature voice technology, voice will become primary interface for enterprise intelligence.

Future of Voice as Primary Interface06:01

In a few years, people will rarely write or use keyboards; they will talk, and AI will write everything. Already happening: people use AI for documents, emails, LinkedIn posts. Will accelerate. Voice becoming primary interface for business intelligence.

Long-Term Vision06:32

Looking forward many years, long way to go: at least 95% or 90-99% of world hasn't adopted tools like Otter yet. Look at next 10 years, not just today. That's how generational companies are built.

Persistence in Building Startups07:01

Building a startup is way harder than running a marathon (has run 11 marathons, planning another in 2 months). Marathons help stay healthy, handle stress, push through challenges. Most people give up fast. For challenging things, difficulties expected. Must persist and pursue goals.