Clay Bavor is the Co-Founder of Sierra, one of the world's fastest-growing enterprise AI companies. Sierra is valued at approximately $15.8 billion, has raised more than $1.5BN from leading investors including Sequoia, Benchmark, Greenoaks, GV and Tiger Global, and today serves more than 40% of the Fortune 50. The company recently surpassed $150 ARR, making it one of the fastest-growing enterprise software businesses in history.
AGENDA:
00:00 – Why Frontier AI Demand Will Be Unlimited
08:00 – Open Models vs Frontier Models: Who Actually Wins?
17:00 – China's AI Advantage & The Distillation Debate
20:30 – Inside Sierra: The AI Agents Running the Entire Company
24:00 – The $100,000 Token Budget Every Engineer Will Soon Need
29:00 – Building AI for 40% of the Fortune 50
37:00 – Why Forward-Deployed Engineers Are the Future of Enterprise AI
43:00 – Sierra's Unusual Board Meetings & Billion-Dollar Company Playbook
48:00 – The Four Values Behind a $16B Startup: Craftsmanship, Intensity & Family
56:00 – Clay Bavor's Hiring Philosophy, AI-First Teams & What's Coming Next
Is AI just better software? Or something completely different that requires a new paradigm to understand? Today we sit down with Bret Taylor and Clay Bavor, two of the best product builders in the world to tackle that question. Bret and Clay are the co-founders of the AI company Sierra.
Brett's resume reads like a greatest hits of Silicon Valley: co-creator of Google Maps, founder of FriendFeed (acquired by Facebook where he became CTO), founder of Quip (acquired by Salesforce where he became co-CEO), former Chairman of the Board at Twitter, and current Chairman of the Board at OpenAI. Clay spent 18+ years at Google, starting as an APM alongside Brett and eventually running product for Gmail, Drive, Docs (all of Google Workspace), Google Labs, and the company's AR/VR efforts.
In addition to AI, today’s conversation has some great tech industry history discussion and old Google stories, perfect to tide us all over between Google Part I and Part II!
Additional Topics:
The accelerating adoption curves of technology waves, and if we’ll ever see an app that gets a billion users in one day
Second- and third-order effects of agents on the internet economy and customer experience
Making predictions on which AI terminology will stick and what won’t
New pricing models in the era of AI, like “outcome-based pricing”
What it’s like to build teams in this new AI era
Links:
Sierra
Customer service is hands down the first killer app of generative AI for businesses. The reasons are simple: the costs of existing solutions are so high, the satisfaction so low and the margin for ROI so wide. But trusting your interactions with customers to hallucination-prone LLMs can be daunting.
Enter Sierra. Co-founder Clay Bavor walks us through the sophisticated engineering challenges his team solved along the way to delivering AI agents for all aspects of the customer experience that are delightful, safe and reliable—and being deployed widely by Sierra’s customers. The Company’s AgentOS enables businesses to create branded AI agents to interact with customers, follow nuanced policies and even handle customer retention and upsell. Clay describes how companies can capture their brand voice, values and internal processes to create AI agents that truly represent the business.
Hosted by: Ravi Gupta and Pat Grady, Sequoia Capital
Mentioned in this episode:
Bret Taylor: co-founder of Sierra
Towards a Human-like Open-Domain Chatbot: 2020 Google paper that introduced Meena, a predecessor of ChatGPT (followed by LaMDA in 2021)
PaLM: Scaling Language Modeling with Pathways: 2022 Google paper about their unreleased 540B parameter transformer model (GPT-3, at the time, had 175B)
Avocado chair: Images generated by OpenAI’s DALL·E model in 2022
Large Language Models Understand and Can be Enhanced by Emotional Stimuli: 2023 Microsoft paper on how models like GPT-4 can be manipulated into providing better results
𝛕-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains: 2024 paper authored by Sierra research team, led by Karthik Narasimhan (co-author of the 2022 ReACT paper and the 2023 Reflexion paper)
00:00:00 Introduction
00:01:21 Clay’s background
00:03:20 Google before the ChatGPT moment
00:07:31 What is Sierra?
00:12:03 What’s possible now that wasn’t possible 18 months ago?
00:17:11 AgentOS
00:23:45 The solution to many problems with AI is more AI
00:28:37 𝛕-bench
00:33:19 Engineering task vs research task
00:37:27 What tasks can you trust an agent with now?
00:43:21 What metrics will move?
00:46:22 The reality of deploying AI to customers today
00:53:33 The experience manager
01:03:54 Outcome-based pricing
01:05:55 Lightning Round
