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Data Science & AI: Getting Buy-In and Demonstrating ROI | PagerDuty’s Sanghamitra Goswami

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Manage episode 424192068 series 2844204
Content provided by LinearB. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by LinearB or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In this episode of Dev Interrupted, Conor Bronsdon is joined by Sanghamitra Goswami, Senior Director of Data Science and Machine Learning at PagerDuty. Sanghamitra shares her expertise in AI and data science, including how engineering teams can effectively leverage both within their organizations. She also explores the history and significance of LLMs, strategies for measuring success and ROI, and the importance of foundational data work. The conversation ends with a discussion about practical applications of AI at PagerDuty, including features designed to reduce noise and improve incident resolution.
Episode Highlights:
00:56 Why are LLMs important for engineering teams to understand?
03:17 How should engineering leaders think about using AI in their products?
07:57 What sort of plan should engineering leaders have to get buy in for AI?
13:22 Are there ways to show ROI on an investment in AI?
15:08 How should we communicate with customers about AI in our products?
18:53 How can companies find a good use case for AI in their product?
Show Notes:

OFFERS

  • Start Free Trial: Get started with LinearB's AI productivity platform for free.
  • Book a Demo: Learn how you can ship faster, improve DevEx, and lead with confidence in the AI era.

LEARN ABOUT LINEARB

  • AI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production.
  • AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance.
  • AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil.
  • MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.
  continue reading

256 episodes

Artwork
iconShare
 
Manage episode 424192068 series 2844204
Content provided by LinearB. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by LinearB or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In this episode of Dev Interrupted, Conor Bronsdon is joined by Sanghamitra Goswami, Senior Director of Data Science and Machine Learning at PagerDuty. Sanghamitra shares her expertise in AI and data science, including how engineering teams can effectively leverage both within their organizations. She also explores the history and significance of LLMs, strategies for measuring success and ROI, and the importance of foundational data work. The conversation ends with a discussion about practical applications of AI at PagerDuty, including features designed to reduce noise and improve incident resolution.
Episode Highlights:
00:56 Why are LLMs important for engineering teams to understand?
03:17 How should engineering leaders think about using AI in their products?
07:57 What sort of plan should engineering leaders have to get buy in for AI?
13:22 Are there ways to show ROI on an investment in AI?
15:08 How should we communicate with customers about AI in our products?
18:53 How can companies find a good use case for AI in their product?
Show Notes:

OFFERS

  • Start Free Trial: Get started with LinearB's AI productivity platform for free.
  • Book a Demo: Learn how you can ship faster, improve DevEx, and lead with confidence in the AI era.

LEARN ABOUT LINEARB

  • AI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production.
  • AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance.
  • AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil.
  • MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.
  continue reading

256 episodes

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