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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 [email protected]
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
4.6
9393 ratings
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 [email protected]
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
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