Customer Results and Feedback, Importance of Human in the Loop

Discussion on customer feedback and results of using Sage, including two types of customers and their responses, the importance of putting the human in the loop, and the value of customer feedback for a startup like Sage.

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This episode is a perfect fit for anyone who wants to learn how to apply AI into their product especially for high fidelity analytics use cases.

Utkarsh Ohm is Director of AI at Thoughtspot. He previously was a Co-Founder & eng leader at various startups. In this episode, we cover applying LLMs alongside other models to customer facing products. We discuss where LLMs in particular are helpful vs traditional ML models, why text to SQL use cases need to be supplemented by internal insights to improve accuracy, and how to approach data security for LLMs. We deep dive specifically into Sage, Thoughtspot’s LLM enabled product and the infrastructure that allows Sage to produce accurate insights for customers. Over the course of the episode, we discuss plenty of advice for teams building with LLMs to learn from and take into account.

Where to Find Utkarsh:

* Twitter: https://twitter.com/utkarshohm

* LinkedIn: https://www.linkedin.com/in/utkarshohm/

Where to Find Shomik:

* Twitter: https://twitter.com/shomikghosh21

* LinkedIn: https://www.linkedin.com/in/shomik-ghosh-a5a71319/

* Newsletter: https://www.shomik.substack.com

* Podcast: Apple Podcasts, Spotify, YouTube.

In this episode, we cover:

(01:35) - Utkarsh’s Journey to Becoming Director of AI at Thoughtspot

(03:14) - Learning AI/ML on the Job

(05:08) - Emergent Capabilities of LLMs Leading to Experimentation