{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Hard Calls with Trisha Price","title":"How to Ship Fast and Drive Outcomes","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/eaa32aeb\"></iframe>","width":"100%","height":180,"duration":2183,"description":"Many product teams still prioritize shipping features rather than driving outcomes. They've become feature factories, run by what amounts to a ‘Chief Backlog Officer’. That approach worked when cycles were long and mistakes were expensive to fix. However, with AI compressing the product lifecycle, it’s possible to ship software the same day it's built. But speed creates a new danger: it’s also possible to ship the wrong thing faster than ever before.\nHard Calls host Trisha Price and Chirag Mehta, VP and Principal Analyst at Constellation Research, explore what it takes to shift from features to outcomes. They discuss how to avoid good product decisions from getting buried in backlogs, how to run a team like a research lab instead of a factory, and why the traditional PM-to-engineer ratio is becoming obsolete.\nHere's what you'll discover:Why shipping features quickly isn't the same as driving business outcomesHow to transition your team to operate like a research lab with continuous experimentationThe difference between lagging indicators like ARR and true North Star metricsWhy evaluating AI-native products means analyzing conversations, not click pathsHow AI is changing the PM-to-engineer ratio and what that means for your teamStrategies to ensure your best product decisions ship instead of rotting in a backlogEpisode Chapters:(00:00) Welcome & Introductions(02:05) From Feature Factories to Outcome-Driven Products(05:40) Inside-Out vs. Outside-In Thinking(08:00) How AI Accelerates Feedback Loops(11:10) Balancing Experimentation with ROI(14:25) Running Your Product Team Like a Research Lab(16:15) Lagging Indicators vs. North Star Metrics(19:20) How AI Smashes the Traditional Product Lifecycle(22:40) C-Suite Accountability and Retention Budgets(26:25) Analytics for AI Agents: Conversations vs. Clicks(30:00) The New PM-to-Engineer Ratio(35:20) Final Takeaway: Build Strong Metrics and Experiment RelentlesslyLove the episode?\nBe sure to follow or subscribe to the Hard...","thumbnail_url":"https://img.transistorcdn.com/OKZmuLUgyp77MHiBQmuatW5RonRxZB-86CA-xhQKOaw/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS85YmQ2/ZDIxNTU3ODkxZjUz/ZmY0YjIzNTAwOWIx/NjgwNy5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}