『Just Now Possible』のカバーアート

Just Now Possible

Just Now Possible

著者： Teresa Torres
無料で聴く

このコンテンツについて

 How AI products come to life—straight from the builders themselves. In each episode, we dive deep into how teams spotted a customer problem, experimented with AI, prototyped solutions, and shipped real features. We dig into everything from workflows and agents to RAG and evaluation strategies, and explore how their products keep evolving. If you’re building with AI, these are the stories for you.All Rights Reserved | Product Talk マネジメント・リーダーシップ リーダーシップ 経済学
エピソード
  • When AI Becomes Your SRE: How Incident.io Is Automating Incident Response

    When AI Becomes Your SRE: How Incident.io Is Automating Incident Response
    2025/11/06
    When your site goes down, every second counts. For years, Incident.io has helped engineering teams coordinate through chaos—getting the right people in the room, keeping stakeholders informed, and restoring order fast. Now, they’re building something new: an AI SRE that can actually help diagnose and respond to incidents. In this episode, Teresa Torres talks with Lawrence Jones (Founding Engineer) and Ed Dean (Product Lead for AI) about how their team is teaching AI to think like a site reliability engineer. They share how they went from simple prototypes that summarized incidents to a multi-agent system that forms hypotheses, tests them, and even drafts fixes—all from within Slack. You’ll hear how they: - Identify which parts of debugging can safely be automated - Combine retrieval, tagging, and re-ranking to find relevant context fast - Use post-incident “time travel” evals to measure how well their AI performed - Balance human trust and AI confidence inside high-stakes workflows This is a masterclass in designing AI systems that think, reason, and collaborate like expert teammates.
    続きを読む 一部表示
    1 時間 8 分
  • Building Trainline’s AI Travel Assistant: How a 25-Year-Old Company Went Agentic

    Building Trainline’s AI Travel Assistant: How a 25-Year-Old Company Went Agentic
    2025/10/30
    Trainline—the world’s leading rail and coach platform—helps millions of travelers get from point A to point B. Now, they’re using AI to make every step of the journey smoother. In this episode, Teresa Torres talks with David Eason (Principal Product Manager) Billie Bradley (Product Manager), and Matt Farrelly (Head of AI and Machine Learning) from Trainline about how they built Travel Assistant, an AI-powered travel companion that helps customers navigate disruptions, find real-time answers, and travel with confidence. They share how they: - Identified underserved traveler needs beyond ticketing - Built a fully agentic system from day one, combining orchestration, tools, and reasoning loops - Designed layered guardrails for safety, grounding, and human handoff - Expanded from 450 to 700,000 curated pages of information for retrieval - Developed LLM-as-judge evals and a custom user context simulator to measure quality in real-time - Balanced latency, UX, and reliability to make AI assistance feel trustworthy on the go It’s a behind-the-scenes look at how an established company is embracing new AI architectures to serve customers at scale.
    続きを読む 一部表示
    1 時間 9 分
  • Powering Government with Community Voices: How ZenCity Built an AI That Listens

    Powering Government with Community Voices: How ZenCity Built an AI That Listens
    2025/10/23
    How do you use AI to help city leaders truly hear their residents? In this episode, Teresa Torres talks with Noa Reikhav (SVP of Product), Andrew Therriault (VP of Data Science), and Shota Papiashvili (SVP of R&D) from Zencity, a company that powers government decision-making with community voices. They share how Zencity brings together survey data, 311 calls, social media, and local news into a unified platform that helps cities understand what people care about—and act on it. You’ll hear how the team built their AI assistant and workflow engine by being thoughtful about their data layers, how they combined deterministic systems with LLM-driven synthesis, and how they keep accuracy and trust at the core of every AI decision. It’s a fascinating look at how modern AI infrastructure can turn noisy, messy civic data into clear, actionable insight.
    続きを読む 一部表示
    1 時間 8 分
まだレビューはありません