Just Now Possible

Building Trainline’s AI Travel Assistant: How a 25-Year-Old Company Went Agentic

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Guests

  • David Eason, Principal Product Manager at Trainline
  • Billie Bradley, Product Manager, Travel Assistant at Trainline
  • Matt Farrelly, Head of AI and Machine Learning at Trainline

    • Key Takeaways

    • AI assistants need both scalable reasoning and deep domain context to be useful.
    • Tool design and guardrails are as critical as prompt design in agent systems.
    • LLM-as-judge evals make it possible to measure open-ended systems without massive labeling costs.
    • Even legacy companies can move fast when they embrace experimentation and tight PM–engineering collaboration.

      • Chapters:

      00:00 Introduction and Team Introductions
      00:51 Overview of Trainline's Mission and History
      02:30 AI Integration in Trainline's Services
      05:08 Challenges and Solutions in AI Implementation
      06:52 Building and Iterating the AI Travel Assistant
      14:58 User Experience and Guardrails
      22:26 Technical Challenges and Solutions
      34:29 The Challenge for Product Managers in AI
      34:55 Billy's Background in AI
      35:42 The Rapid Evolution of AI Technology
      37:14 Managing Information Overload
      37:58 Collaboration Between Product Managers and Engineers
      38:42 Trainline's Approach to Machine Learning
      39:36 Scaling Up: From 450 to 700,000 Pages
      40:21 Challenges in Data Retrieval and Processing
      45:55 Evaluating AI Assistants
      48:22 The Role of LLM as Judges
      50:19 User Context Simulation for Real-Time Evaluation
      01:06:56 Future Directions for Trainline's AI Assistant

      ...more
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      Just Now PossibleBy Teresa Torres