Subvolts take AI augments human agents for better customer service, not just full automation. Oct 14, 2025 - Developers
- Learn about the technical challenges of deploying complex AI systems at scale, including real-time model orchestration.
- Business
- Understand how AI can augment human agents to improve customer experience and explore strategies for building fast-growing AI companies.
This is a solid interview with a CEO of an AI company and a prominent venture capitalist discussing AI's practical business applications.
Why AI Will Transform Customer Experience: Cresta CEO Ping Wu and Sequoia’s Doug Leone
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From Subvolts
Summary and analysis by Subvolts editorial, AI-assisted.
Cresta CEO Ping Wu and Sequoia Capital's Doug Leone discuss transforming customer experience with AI on the Training Data podcast. Wu advocates a hybrid approach, automating some tasks while using AI to assist human agents. Leone shares insights on building fast-growing AI companies, framing current AI advancements as an Industrial Revolution 2.0. The episode covers technical challenges and strategic opportunities in contact center AI.
This episode explains how AI can help customer service agents do their jobs better, not just replace them. It covers the technical hurdles and new customer experiences AI can create, making interactions smoother for everyone.
This episode offers a practical look at AI's impact on customer service, moving beyond pure automation to human augmentation. It's for business leaders and AI strategists interested in real-world deployment challenges and growth frameworks. The discussion on orchestrating multiple AI models in real-time connects to frontier labs like Google Gemini and OpenAI, which are developing increasingly complex multimodal systems.
- HostSequoia Capital
- GuestPing WuCEO, Cresta
- Episode Title: Why AI Will Transform Customer Experience: Cresta CEO Ping Wu and Sequoia’s Doug Leone
- Show: Training Data (an official AI show)
- Length: 45 minutes
- Guest's Previous Role: Built Google's contact center business
- AI Approach: Automating what's ready, assisting humans with the rest
- Technical Challenge: Orchestrating 20+ models in real-time
Ping Wu built Google's contact center business before becoming CEO of Cresta, where he's pioneering a unique approach to contact center transformation. Rather than full automation Ping advocates a dual approach, automating what's ready while using AI to assist humans with the rest. He makes the case for an abundance mindset—imagining new customer experiences like talking to airline apps or turning synchronous interactions asynchronous. Ping breaks down the technical challenges of deploying Contact Center AI at scale, from solving latency to orchestrating 20+ models in real-time. Sequoia’s Doug Leone shares his framework for building AI companies at speed and why he believes we're at the front end of an Industrial Revolution 2.0.
Hosted by: Sonya Huang and Doug Leone, Sequoia Capital
00:00 Introduction
01:13 The Evolution of Contact Centers
02:05 Debating AI's Impact on Call Centers
04:07 Challenges and Opportunities in Contact Centers
08:14 Technological Waves in Contact Centers
11:10 AI vs Human Agents: The Future
13:35 Customer Experience and AI
16:33 The Role of Data in AI Automation
19:05 Competing in the AI Space
22:34 Building a Company in the AI Era
24:05 Instilling Speed in AI Companies
24:53 Management Experience and Growth Challenges
26:01 Identifying Leadership Potential
26:37 Cresta's Leadership Transition
28:34 Future Goals for Cresta
29:56 AI Market Cycles and Investment
35:38 Cresta's Technical Stack
45:11 AI's Impact on Business Communication
- latency
- Ping Wu
- the delay before a transfer of data or computation begins
- synchronous
- Ping Wu
- happening at the same time, like a live phone call
- asynchronous
- Ping Wu
- not happening at the same time, like sending an email
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Questions people ask
- What is Cresta's approach to AI in contact centers?
- Cresta uses a dual approach, automating tasks ready for AI and using AI to assist human agents with the rest.
- What are the technical challenges of deploying AI at scale?
- Challenges include solving latency and orchestrating over 20 models in real-time.
Page generated Oct 19, 2026. Summaries are Subvolts' own; the audio, artwork and notes belong to Sequoia Capital.