这期访谈挺实在，DecagonAI说90%客服智能体跑在开源模型上，新场景先用贵的再用便宜的，搞微调能省成本。适合做AI应用的人听。
DecagonAI联合创始人与a16z对谈，透露其客服智能体90%运行在开源模型上。他们主张智能与便宜不是取舍，新用例先用前沿模型，成熟后迁移到开源。DecagonAI在应用层做按用例微调，降低支持成本后企业会购买更多支持服务。他们希望用AI缩小年付10万美元与10美元客户之间的客服差距。
A $100K/year customer gets white-glove treatment while a $10/year customer gets a help center. @Deca...
A $100K/year customer gets white-glove treatment while a $10/year customer gets a help center. @DecagonAI 's bet is that AI closes that gap, and enterprise is buying it. Co-founders Jesse Zhang and Ashwin Sreenivas sit down with a16z's Kimberly Tan and Sarah Wang to discuss what they've learned running agents inside the biggest banks, airlines, and telcos: - Smart-vs-cheap models are a false trade-off - Start with frontier models on new use cases, then migrate to open-source after they mature - Fine-tuning per use case works at the application layer - Support demand always outran supply: make it cheaper and companies buy more of it 00:00 Intro 01:07 90% of Decagon runs on open-source 05:00 The smart vs. cheap trade-off is false 09:26 Building a model factory in-house 15:07 Are the labs the last startups? 21:21 Are forward deployed engineers a trap? 28:36 The agent that builds the agent 37:02 Glass box beats black box 47:55 From help desk to AI concierge 1:14:45 Jevons paradox in customer support @thejessezhang @AshwinSreenivas @kimberlywtan @sarahdingwang Your browser does not support the video tag. 🔗 View on Twitter 💬 5 🔄 2 ❤️ 20 👀 8237 📊 7 ⚡