ConTejas Code is a podcast in the web engineering space that has deep dives on various topics between frontend engineering with React, TypeScript, Next.js, and backend engineering with Kafka, Postgres, and more. The series is a mix of long-form content and guest episodes with industry leaders in the web engineering space.
From the podcast, listeners will take away actionable best practices that you can integrate into your workflows as well as valuable insights from prominent people in the industry.
Hosted on Acast. See acast.com/privacy for more information.
ConTejas Code is a podcast in the web engineering space that has deep dives on various topics between frontend engineering with React, TypeScript, Next.js, and backend engineering with Kafka, Postgres, and more. The series is a mix of long-form content and guest episodes with industry leaders in the web engineering space.
From the podcast, listeners will take away actionable best practices that you can integrate into your workflows as well as valuable insights from prominent people in the industry.
Hosted on Acast. See acast.com/privacy for more information.
Links
- Codecrafters (sponsor): https://tej.as/codecrafters
- Feedback Intelligence: https://www.feedbackintelligence.ai/
- Chinar on X: https://x.com/movsisyanchinar
Summary
In this podcast episode, we talk to Chinar Movsisyan, the CEO and founder of Feedback Intelligence. They discuss Chinar's extensive background in AI, including her experience in machine learning and computer vision. We discuss the challenges faced in bridging the gap between technical and non-technical stakeholders, the practical applications of feedback intelligence in enhancing user experience, and the importance of identifying failure modes. The discussion also covers the role of LLMs in the architecture of Feedback Intelligence, the company's current stage, and how it aims to make feedback actionable for businesses.
Chapters
00:00 Chinar Movsisyan
02:08 Introduction to Feedback Intelligence
03:23 Chinar Movsisyan's Background and Expertise
06:33 Understanding AI Engineer vs. GenAI Engineer
09:08 The Lifecycle of Building an AI Application
13:27 Data Collection and Cleaning Challenges
16:20 Training the AI Model: Process and Techniques
24:48 Deploying and Monitoring AI Models in Production
27:55 The Birth of Feedback Intelligence
31:58 Understanding Feedback Intelligence
33:26 Practical Applications of Feedback Intelligence
42:13 Identifying Failure Modes
45:58 The Role of LLMs in Feedback Intelligence
51:25 Company Stage and Future Directions
57:24 Making Feedback Actionable
01:01:30 Streamlining Processes with Automation
01:03:18 The Journey of a First-Time Founder
01:05:48 Wearing Many Hats: The Founder Experience
01:08:22 Prioritizing Features in Early Startups
01:13:09 Learning from Customer Interactions
01:16:38 The Importance of Problem-Solving
01:21:51 Handling Rejection and Staying Motivated
01:27:43 Marketing Challenges for Founders
01:29:23 Future Plans and Scaling Strategies
Hosted on Acast. See acast.com/privacy for more information.
