How Enterprise AI Really Gets Deployed
Sarah Wang and Kimberly Tan are joined by Jesse Zhang and Ashwin Sreenivas, co-founders of Decagon, to discuss the evolution of enterprise AI agents, why the company increasingly relies on open-source models, and how it is helping some of the world’s largest companies deploy AI in production.
Decagon has become one of the fastest-growing AI companies by building agents that automate customer support, sales, and operational workflows. Jesse, Decagon’s CEO, and Ashwin, its president, explain how the company is building enterprise AI at scale.
They unpack why Decagon moved most of its inference to open-source models, how latency, evaluation, and fine-tuning shape production AI systems, and why enterprise AI requires far more than simply plugging into frontier models. The conversation also explores forward-deployed engineering, enterprise sales, AI’s impact on jobs, and why application companies will continue to thrive alongside the foundation model labs.
Resources:
Follow Jesse Zhang on X: https://x.com/thejessezhang
Follow Ashwin Sreenivas on X: https://x.com/AshwinSreenivas
Follow Sarah Wang on X: https://x.com/sarahdingwang
Follow Kimberly Tan on X: https://x.com/kimberlywtan
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Jesse Zhang - Building Decagon - [Invest Like the Best, EP.443]
My guest today is Jesse Zhang. Jesse is the co-founder and CEO of Decagon, one of the fastest-growing AI customer service companies. Decagon provides a centralized AI engine to auto-resolve issues at any time, in every language, and across every channel. Jesse shares his systematic approach to finding product-market fit by asking potential customers exactly how much they'd pay for solutions. We explore why customer service and coding have emerged as the two clearest AI use cases for enterprises, and the key business and technical factors behind Decagon's momentum. We discuss the intense competitive dynamics of building in AI today, strategic decisions around building proprietary models, and deploying AI agents at enterprise scale. Please enjoy my conversation with Jesse Zhang.
For the full show notes, transcript, and links to mentioned content, check out the episode page here.
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Editing and post-production work for this episode was provided by The Podcast Consultant (https://thepodcastconsultant.com).
Show Notes:
(00:00:00) Welcome to Invest Like the Best
(00:05:49) Building a Company in a Competitive Market
(00:07:26) Personal Background and Competitive Upbringing
(00:10:32) Challenges and Lessons from Previous Ventures
(00:12:21) Ideation and Customer Discovery Process
(00:19:31) Developing and Refining AI Customer Service Agents
(00:32:26) Voice AI and Future Prospects
(00:38:20) Utilizing Customer Interaction Data
(00:39:59) Frameworks for Implementing AI in Business
(00:41:48) Evaluating the ROI of Coding Agents
(00:42:53) The Future of Company Agents
(00:45:15) Brand Personality in AI Agents
(00:47:48) Investor Interest in AI Companies
(00:54:32) The Competitive Landscape of AI Talent
(00:57:21) Building Proprietary AI Models
(01:10:36) Customer Qualification and Engagement
(01:17:27) The Kindest Thing
20VC: Why 90% of Founders Build Startups Wrong | Why AI Growth Rates are Sustainable & Remote Work is BS and the AI Talent War | Competing with Brett Taylor and Sierra: Who Wins the Customer Service War with Jesse Zhang, Decagon
Jesse Zhang is the Co-Founder and CEO @ Decagon, the conversational AI platform for customer experience. As one of the fastest growing companies in the valley, they have raised over $230M at a last round price of $1.5BN. Prior to Decagon, Jesse founded Lowkey (acquired by Niantic), studied CS at Harvard, and worked at places like Google, HRT, Citadel, and Intel.
AGENDA:
00:00 Introduction and Sponsor Messages
03:43 Olympiad Mathematician to Startup Founder
05:34 Selling to Niantic and What I Did Differently the Second Time
07:16 Why 90% of Founders Build Companies the Wrong Way
12:19 Scaling to $50M ARR in 15 Months
31:31 Is the AI Talent War Out of Hand: How To Compete with Meta Pay Packets
32:38 Why Remote Work is Total BS
34:06 Competitors in AI Customer Experience: Sierra, Intercom and more
37:34 AI Market Predictions
44:56 Embracing Stress and Winning Culture
50:13 Quick Fire Questions: Most Underrated AI Founder, Biggest Changed Opinion
AI Agents Talking to AI Agents: Reinventing Commerce with Decagon CEO Jesse Zhang
The traditional call center may soon be a thing of the past. Jessie Zhang is building AI agents designed to replace monotonous human labor and transform how consumers interact with brands. Elad Gil sits down with Jesse Zhang, co-founder and CEO of Decagon, an AI agent company at the forefront of AI customer service. Jesse talks about how Decagon secured large enterprise clients and the impact of its AI agents, his journey as a second-time founder, and Decagon’s company culture. Plus, they discuss what the future of agentic customer service may look like.
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Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @thejessezhang | @DecagonAI
Chapters:
00:00 – Jesse Zhang Introduction
00:30 – Decagon’s Services
01:11 – Decagon’s Customers and Growth
02:41 – Productivity Gains with Decagon
03:33 – How Decagon Integrates in Customer Workflows
04:25 – Jesse’s Second Time Founder Story
05:41 – Jesse’s Hiring Philosophy
09:13 – Counter-intuitive Advice for Founders
11:19 – How Decagon Thinks About Talent
14:12 – Areas for Longer Term Planning
15:37 – Decagon’s Path to Customer Service
16:57 – Thoughts on Pushing Into the Application Layer
19:40 – What Decagon Does Uniquely
22:05 – Pricing Services in the AI Age
24:46 – How Decagon Sees Customer Service
25:53 – Defining Long-Term Success for Decagon
27:41 – Jesse’s Views on an Agentic Future
31:22 – Conclusion
How AI Agents Are Transforming Customer Support, with Decagon’s Jesse Zhang
Today on No Priors, co-founder and CEO of Decagon, Jesse Zhang, joins Elad to discuss the future of agentic customer support. Decagon provides AI-powered customer interactions for companies like Rippling, Notion, Duolingo, Classpass, Substack, Vanta, Eventbrite, and more. Jesse shares the thesis behind starting Decagon, why he sees customer support as the ideal entry point for agentic technology, and what areas of AI excite him most. They also discuss voice-based interfaces, issues with latency in current capabilities, and the connection between young math olympiad communities and today’s AI startups.
Sign up for new podcasts every week. Email feedback to show@no-priors.com
Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @TheJesseZhang
Show Notes:
0:00 Introduction
0:30 Starting Decagon
3:15 Business impact of adopting agents for customer support and customer ops
8:00 AI infrastructure and models for customer success agents
12:05 Voice-based capabilities and text-to-speech engines
15:00 Combatting latency
16:25 Crossover of math and AI communities
21:12 Exciting areas of AI
25:29 Strengths and weaknesses of agents