How to Ship Fast and Drive Outcomes

Planview's CPO on Making Intelligent Bets When You Can Barely See Six Months Ahead

Too many companies are treating AI like a checkbox. Board pressure, competitive anxiety, and a fear of being left behind are driving product teams to ship AI features before they've defined the problem they're solving. Louise Allen, Chief Product Officer at Planview, [https://www.planview.com/] has seen this movie before and it ends the same way Agile did when it became the goal instead of the means. Recorded live at Pendomonium 2026, Louise joined Trisha Price to talk about what it actually looks like to lead product through transformation: reorganizing around a platform model, making intelligent bets with incomplete information, and building AI into your product in a way that delivers measurable business outcomes. In this episode, they dig into how Planview built Anvi, its agentic AI product, why governance isn't a dirty word, and how a novel integration with Pendo guides is bridging the gap between conversational AI and traditional SaaS interfaces. Here's what you'll discover: * Louise's hard call was restructuring her org around a platform model, which meant hard conversations with people who built the products that got Planview here. Being right about the future doesn't make it easier. * AI is not the goal and treating it like one is exactly why most AI initiatives fail. Louise draws a direct parallel to how Agile became the destination instead of the vehicle. * Product management is a business role, not a requirements role. As the CPO title expands across the Fortune 500, Louise makes the case for why product has to lead transformation, not support it. * Three-year roadmaps are gone. The job now is making an intelligent bet, shipping it, and being ready to pivot. Louise explains how her team operates with confidence inside that uncertainty. * Trust in AI agents comes from transparency and audit trails, not just performance. Louise breaks down how Planview thinks about governance, and why getting that right is what separates real enterprise AI adoption from a failed rollout. Episode Chapters * (00:00) Welcome and Introduction * (00:31) Recording Live at Pendomonium * (01:45) The Hard Call: Reorganizing Around a Platform Model * (03:30) When People Become Bigger Than Their Products * (04:45) Making Faster Bets with Less Information * (05:55) Why Three-Year Roadmaps Are Gone * (06:45) Product Management as a Business Role * (08:45) AI Accelerates the Need for True Product Leadership * (09:30) AI Is Not the Goal: Lessons from the Agile Era * (11:00) How Planview Built Envy and Got a Head Start * (13:00) The Hybrid World: Agents and Traditional Interfaces * (14:30) Managing Agents, Governance, and Who Gets to Push the Button * (16:00) Building Trust in AI Through Transparency and Audit Trails * (16:45) How Pendo Guides Bridge Envy and the SaaS Interface * (19:30) Paying It Forward: Women in Product and Technology Love the episode? Follow or subscribe to Hard Calls and share this episode with any product or business leader navigating AI strategy, org transformation, or both. Every subscription helps more product leaders find the show. Presented by Pendo. Discover more insights at https://www.pendo.io. [https://www.pendo.io/] Connect with Trisha Price [https://www.linkedin.com/in/trisha-price-3063081/] on LinkedIn Connect with Louise Allen [https://www.linkedin.com/in/louise-k-allen-5703861/] on LinkedIn

How a Designer Shipped a Year of Work in Two Months

A year-long project. Two months. A small team, a few back-end engineers, and a QA resource. Ed Case, Director of Product Design and UX at Vantaca, didn't set out to become an engineer. He set out to ship faster and figured out that the fastest path ran straight through the codebase. The shift happening in product teams right now isn't just that AI writes code. It's that the walls between design, product, and engineering are coming down - and the teams moving quickest are the ones who stopped caring which role owns what. In this episode, Trisha Price and Ed Case dig into what it actually looks like when a designer gets into the codebase, how that changes the relationship with engineering, and why velocity without the right feedback loop still gets you nowhere. Here's what you'll discover: * Ed's team had months of momentum behind a full application rewrite and had to kill it. What he learned about incremental value shaped everything that came after. * Moving designers into the actual codebase (not just prototyping tools) compressed a year-long project into two months and made engineering handoffs nearly disappear. * Fewer people, tighter communication, and shared ownership of outcomes removed the noise that slows most software teams down. * Shipping faster means shipping the wrong thing faster, too. Early access groups, feature flags, and real usage data keep the speed honest. * From learning version control to building a design OS, Ed's practical steps for any designer or PM ready to move beyond prototyping tools. Episode Chapters * (00:00) Welcome and Introduction * (01:34) Ed's Background: Fine Arts to Product Design * (02:04) The Hard Call: Killing a Full Application Rewrite * (05:09) What Incremental Value Actually Means * (05:36) How AI Is Compressing the Product Lifecycle * (06:32) From Figma Prototypes to the Real Codebase * (08:09) The Project: Rebuilding a Major Product in Two Months * (11:20) How This Changed the Relationship with Engineering * (13:10) Using AI for Analysis and Building Conviction * (14:19) Tools of the Trade: Cursor, Claude Code, and GPT * (16:49) UX Research in an AI-Accelerated World * (19:18) Why Production Is Where You Learn the Most * (22:00) Faster Velocity to Outcomes, Not Just to Ship * (22:29) Practical Advice: Getting Into the Codebase * (28:37) QA as a Critical Part of the AI Workflow Love the episode? Be sure to follow or subscribe to the Hard Calls podcast and share it with anyone navigating product transformation or working to build better product sense. Every subscription helps more product management leaders find Hard Calls. Presented by Pendo. Discover more insights at https://www.pendo.io [https://www.pendo.io/]. Connect with Trisha Price on LinkedIn at https://www.linkedin.com/in/trisha-price-3063081/ [https://www.linkedin.com/in/trisha-price-3063081/]. Connect with Ed Case on LinkedIn at https://www.linkedin.com/in/edward-case/ [https://www.linkedin.com/in/edward-case/]

How to Ship Fast and Drive Outcomes

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. Hard 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. Here's what you'll discover: * Why shipping features quickly isn't the same as driving business outcomes * How to transition your team to operate like a research lab with continuous experimentation * The difference between lagging indicators like ARR and true North Star metrics * Why evaluating AI-native products means analyzing conversations, not click paths * How AI is changing the PM-to-engineer ratio and what that means for your team * Strategies to ensure your best product decisions ship instead of rotting in a backlog Episode 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 Relentlessly Love the episode? Be sure to follow or subscribe to the Hard Calls podcast and share it with anyone navigating product transformation or working to build better product sense. Every subscription helps more product management leaders find Hard Calls. Presented by Pendo. Discover more insights at https://www.pendo.io. [https://www.pendo.io] Connect with Trisha Price on LinkedIn at https://www.linkedin.com/in/trisha-price-3063081/. [https://www.linkedin.com/in/trisha-price-3063081/] Connect with Chirag Mehta on LinkedIn at https://www.linkedin.com/in/mehtachirag/ [https://www.linkedin.com/in/mehtachirag/]

AI Isn't Helping Us Learn Faster; We Are Still Human After All

Leyla Seka is a product and tech legend; as a former Salesforce leader, she built and scaled Salesforce's AppExchange and led the company through one of its most pivotal moments. In this episode of Hard Calls, Leyla describes the similarities between adopting Salesforce’s AppExchange and the adoption challenges companies face when shipping AI tools and features today. The adoption curves are identical because human dynamics haven't changed. AI may be bringing us information faster, but the pace at which we consume and learn remains largely unchanged, and product leaders need to understand this. Here's more of what you'll discover in this episode: * Leyla’s hard call: Supporting a manager’s decision to build a new product, even when you don’t believe in it * Why building ecosystems and communities breaks all the normal product rules * Why experienced executives are your real advantage in any transformation, including AI * How to stay grounded and remember that your success doesn't make you more important Episode Chapters * (00:00) Introduction: How Leyla Changed Trisha's Career * (03:17) The Hard Call: Scrapping a Release for Chatter * (06:00) Building a Product No One Asked For * (07:00) Leading When You Don't Believe * (09:00) How Chatter Transformed Salesforce * (10:00) From Pull to Push: The Platform Shift * (11:00) AI as the Next Platform Shift * (14:00) Why Seasoned Execs Matter Most * (19:00) The Complexity of Building Ecosystems * (20:00) Leading Across Generations * (22:00) Keeping Your Ego in Check * (27:00) Staying Grounded Through Success * (29:30) The Relentless Pressure of Product Leadership * (31:00) Build Community With Other Leaders * (33:00) Closing: What's Next Love the episode? Be sure to follow or subscribe to the Hard Calls podcast and share it with anyone navigating product transformation or working to build better product sense. Every subscription helps more product management leaders find Hard Calls. Presented by Pendo. Discover more insights at https://www.pendo.io. [https://www.pendo.io.] Connect with Trisha Price on LinkedIn at https://www.linkedin.com/in/trisha-price-3063081/ [https://www.linkedin.com/in/trisha-price-3063081/] Connect with Leyla Seka on LinkedIn at https://www.linkedin.com/in/lseka/ [https://www.linkedin.com/in/lseka/]

This Decision Framework Leads to Better Product Experiments

In this episode of Hard Calls, Jeff Lash, VP of Product Management at Insperity, joins Trisha Price to explore the framework separating good product managers from great ones. He calls it thinking in one-way doors versus two-way doors: reversible decisions versus irreversible ones. But here's what matters: in an era where AI can vibe-code anything in minutes, product sense and customer judgment matter more than ever. Here's what you'll discover: Why shipping a feature no one wants actually erodes trust. A feature was being built for a nursing audience, and since it was on the same platform, Jeff’s team thought it was a good idea to offer that feature to their physician audience, too. The issue is that the physicians didn't ask for that feature, nor did they really need it. So Jeff asked, “What gets harmed if we launch this feature to the physicians?” A lot, actually. Jeff said no to adding the feature to the physicians' interface because it would have added unnecessary complexity and eroded user trust. His hard call set the tone for his entire leadership approach. A decision framework that leads to better experimentation. Jeff approaches decision-making with the lens of reversibility: he asks, ‘How hard would it be to undo this if, say, the decision proves to be wrong or the strategy changes?’ This framework leads his team to experiment in a structured way that allows pivoting with minimal disruption. Experimentation becomes even more impactful as he involves internal stakeholders along the way. Building AI into your product isn’t the savior. AI can help you build features faster, but that means it can also help you build the wrong features faster, too. Jeff is emphatic about knowing if the new AI feature or product will actually solve a problem users have. He frames it this way: people don't buy your product; they buy the outcome that your product promises to deliver. If your product can solve a problem without AI, your customer will not care. The Goldilocks of balancing the pressures of short-and long-term demands. Jeff doesn't use rigid formulas to balance short-term demands with long-term strategy. What prevents disconnect isn’t the framework; it’s alignment. Frameworks help create guardrails and allocate budgets, but it's context and conversation that clarify prioritization. When internal stakeholders understand the why behind the demands, short-term concessions feel intentional without losing sight of long-term objectives. Episode Chapters * (00:00) Introduction: From Medical Publishing to Insperity * (02:00) The Hard Call: Saying No to a Feature You Can Ship * (05:00) Why Good Product Managers Celebrate Fewer Features * (06:24) A Decision Framework That Leads to Better Experimentation * (09:00) Experimentation in B2B: It's More Complicated * (10:00) The Stakeholder Web: Sales, Support, Legal, Finance * (12:27) AI as a Tool, Not the Goal * (14:00) Building AI Into Your Product Isn’t The Savior. * (18:00) Formulas Don't Replace Judgment * (20:00) Context Matters More Than Rules * (24:15) Language Shapes Understanding: Simplify to Clarify * (29:00) Bringing Product Mindset to Traditional Industries * (35:50) Stakeholder Ecosystems: Your Competitive Advantage * (38:00) Closing: Whole Product Thinking Love the episode? Be sure to follow or subscribe to the Hard Calls podcast and share it with anyone navigating product transformation or working to build better product sense. Every subscription helps more product management leaders find Hard Calls. Presented by Pendo. Discover more insights at https://www.pendo.io. [https://www.pendo.io/] Connect with Trisha Price on LinkedIn at https://www.linkedin.com/in/trisha-price-3063081/. [https://www.linkedin.com/in/trisha-price-3063081/] Connect with Jeff Lash on LinkedIn at linkedin.com/in/jefflash [https://www.linkedin.com/in/jefflash/]