Decisions in Uncertainty (Part 2): How to Make the Call

Decisions in Uncertainty (Part 2): How to Make the Call

So now you have defined the starting point and the ending point. Check out Part 1, “Decisions in Uncertainty (Part 1): When ‘Go Build This’ Is All You Get.” What do you do next? In part two of this conversation, Todd Blaquiere and Ryan Cantwell define the messy middle and give you the playbook for making the call when certainty is still out of reach. They walk through how to use a decision-making rubric, identify the highest-risk assumption, and test what matters most before a team sinks too much time into the wrong thing. They also dig into one of the hardest parts of product work: how to read unclear signals, weigh imperfect evidence, and know when you have enough confidence to stop researching and start recommending. If part one was about slowing down long enough to get clear, this episode is about what it takes to move forward anyway. Pull up a chair on the porch and know how to make the call. TIME STAMPED NOTES: What should a product manager do after getting clear on the outcome? [00:00] Part two setup - Episode moves from clarity to decision-making [01:01] Why this still feels hard - Clear requests can still hide unclear success [02:19] What defines the target - Business outcomes and customer outcomes shape the call [04:05] Why success must be defined - Better decisions start with clear success criteria How can a product manager make a better decision when the answer is not obvious? [05:13] Why a rubric helps - Shared criteria make hard calls easier [06:04] What goes into a rubric - Value, demand, fit, timing, and right to win [07:50] Why weighting matters - Some criteria matter more than others [08:08] Why confidence matters too - Weak evidence should not count the same as strong evidence [11:43] What a rubric is really for - Alignment matters more than fake objectivity How can a product manager figure out what to test first? [13:07] What the “monkey” means - The highest-risk assumption can kill the idea [13:32] How to move faster - Tiny Acts of Discovery focus on the biggest risk first [14:27] Example: missing data - No data can mean no product [15:31] Example: willingness to pay - Real pain does not always lead to real revenue How can a product manager test assumptions without fooling the team? [19:32] Say versus do - Real behavior matters more than polite feedback [19:54] Why direct asks work - Simple requests can reveal the truth faster [20:33] What commitment looks like - Pre-orders, signups, and emails show stronger intent [21:02] What to avoid - Friendly audiences can give false confidence [22:12] Why the answer stays messy - Evidence is rarely perfect or complete How does a product manager know when it is time to make the call? [23:04] How to use the evidence - Outcomes, rubrics, assumptions, and tests work together [24:07] Why a second lens helps - Another prioritization method can expose weak thinking [25:01] What “enough confidence” looks like - Full certainty usually never comes [25:27] When the job changes - Research mode must turn into recommendation mode [29:06] How to present the call - Start with the ask, the risk, the test, and the recommendation [30:22] What leaders want first - Executive audiences want the answer up front [36:00] Who owns the decision - Judgment cannot be handed to someone else Help keep the Product Porch lights on by giving at https://www.patreon.com/TheProductPorch Join our email list and never miss an episode at theproductporch.com [https://www.theproductporch.com/email-signup]

Decisions in Uncertainty (Part 1): When “Go Build This” Is All You Get

Have you ever been told to “go build this” and felt that little pit in your stomach because you were not totally sure what success even meant? In this episode, Todd Blaquiere and Ryan Cantwell dig into one of the most uncomfortable parts of product management: making decisions when the path is unclear and the pressure to move is high. They talk through why vague direction creates misaligned expectations, how product managers get trapped into building motion instead of outcomes, and what it takes to slow down long enough to clarify business outcome, customer value, and the real risk underneath the request. Along the way, they share stories of getting it wrong, and dig into why so many product managers freeze or default to the safest path, and offer a more practical way forward.  _If you have ever felt stuck between vague direction and the pressure to act, pull up a chair on the porch, rethink how you make decisions under uncertainty, and start building the judgment that sets great product managers apart.__ TIME STAMPED NOTES What should a product manager do when the direction is vague but action is expected? [00:00] Episode framing - Uncertainty and pressure to act set up the core problem [00:57] Why this feels hard - Product managers feel overwhelmed when the path is unclear [02:50] Two kinds of uncertainty - Empowered decision-making versus unclear direction with no real guidance Why is “just go build it” such a dangerous trap? [03:11] Blind execution trap - Following the request without understanding the outcome creates risk [04:04] LA Times example - Building the thing without asking why leads to misalignment [05:27] Hardware example - Big expectations show up before customer, problem, or business context is clear [06:29] False progress - Busy work, polished decks, and shallow analysis can hide the real problem How should a product manager clarify what success actually means? [09:33] Start with why - Better decisions begin with understanding the outcome behind the request [10:34] Curiosity over confrontation - Better questions create alignment without triggering defensiveness [13:06] Outcome alignment - Business goals and stakeholder goals need to be made explicit [15:55] Playback and check-ins - Repeating understanding and revisiting direction reduces drift What makes a good decision framework when certainty is impossible? [18:43] Business outcome and customer value - Both sides are needed to make strong product decisions [20:26] Specific customer definition - Clear value starts with identifying the exact customer [23:27] Business context - Portfolio gaps, business risk, and cost of inaction sharpen the goal [24:20] Partial certainty - Strong product decisions often happen before perfect clarity exists [26:12] Working rubric - Outcomes and value become a hypothesis for what to test How should a product manager reduce risk before committing to a path? [28:09] Monkey on the pedestal - The riskiest assumption should be tackled first [29:35] Hard thing first - Early validation reduces waste and improves confidence [32:53] AI feature scenario - Sales pressure becomes a practical example of reframing a request into assumptions and tests [38:19] Discovery patterns - Lost deals, customer segments, and recurring signals help focus investigation [41:15] Closing takeaway - Simple mental models help product managers move forward under uncertainty Help keep the Product Porch lights on by giving at https://www.patreon.com/TheProductPorch Join our email list and never miss an episode at theproductporch.com [https://www.theproductporch.com/email-signup]

AI Overload: The Pressure on PMs to Keep Up

Why does it feel like every time product managers start to catch up on AI, three new tools, five new hot takes, and twelve new newsletters show up? In this episode, Joe Ghali and Ryan Cantwell sit down with Dean Peters to talk about AI overload in product management and how to separate useful signal from all the tool-chasing noise. They discuss the thought leaders in the PM community who keep telling product managers they’re already behind, mostly to sell their content, framework, or “must-use” tool that has nothing to do with solving real customer problems. Dean breaks down why tool fluency is not the same thing as impact, how AI can amplify bad product habits, and why the fundamentals still matter: understanding the customer problem, choosing the right approach, and knowing when AI is not the answer. They also talk about practical ways to start small, build useful AI techniques, and use AI as augmented intelligence instead of treating it like a magic product brain. If AI has you feeling behind, overwhelmed, or unsure what’s worth paying attention to, pull up a chair on the porch. We will help you slow down, focus on the problem, and use AI without letting the hype use you. TIME STAMPED NOTES: Introduction and AI Overload [00:39] AI overload – Why PMs feel buried by constant AI noise. [00:59] Meet Dean Peters – Dean joins to talk AI, product strategy, and tool fatigue. [02:45] Too many tools – Why the pace of AI change feels impossible to track. [03:59] Fear-based AI advice – How thought leaders turn AI anxiety into content and courses. [04:58] What to trust – Why useful AI guidance is hard to separate from snake oil. AI Hype, Anxiety, and Bad Habits [05:37] Feeling stuck – Why many PMs are experimenting but still lack confidence. [06:21] Career pressure – How AI hype makes PMs worry about falling behind. [06:38] AI maturity stages – Dean’s path from confident nonsense to real AI impact. [08:05] Bad discovery, faster – Why AI can make weak product habits worse. [09:57] Beyond tool fluency – How AI should connect to workflow and business outcomes. Start With the Problem, Not the Tool [10:25] Test on yourself – Why personal AI experiments are a smart place to start. [11:02] Stop chasing tools – Why AI tools change too fast to build your identity around them. [12:23] Start with user pain – Why the better question is not “what can AI do?” [12:44] AI as an assistant – How AI can support decisions without replacing judgment. [14:28] Fundamentals still matter – Why AI magnifies whatever product skills you already have. Using AI Without Losing Product Judgment [15:10] Pick one real problem – How to start learning AI without getting overwhelmed. [16:20] Get a first win – Why small useful wins build confidence and momentum. [18:41] Bolted-on AI – What happens when leaders say, “go add AI.” [19:25] The tool-first trap – Why starting with AI usually leads to bad product decisions. [23:29] Not a source of truth – Why AI output should start the conversation, not end it. Practical Next Steps and Final Takeaways [24:44] Simple personal use cases – How everyday AI experiments build comfort. [26:23] Automating busywork – Where AI can take mundane tasks off your plate. [27:34] Avoid obvious gimmicks – Why “just add a chatbot” usually misses the point. [31:05] Build transferable skills – Why prompting, context, and judgment matter across tools. [34:16] What AI reveals – Why AI will amplify strong PMs and expose weak habits. Help keep the Product Porch lights on by giving at https://www.patreon.com/TheProductPorch Join our email list and never miss an episode at theproductporch.com [https://www.theproductporch.com/email-signup]

Product Culture for PMs Tired of Useless Frameworks

Have you ever tried a new framework, only to find the meetings changed, but the results didn’t? In this episode, Todd Blaquiere, Joe Ghali, and Ryan Cantwell dig into product culture and why it shapes roadmap decisions, product discovery, experimentation, and the way cross-functional teams work day to day. They break down the difference between culture and practice, talk through what product managers can influence on their own teams, and share practical ways to build better norms without wasting energy trying to fix the whole company. If you’ve ever felt like the unwritten rules in your organization were blocking good product work, pull up a chair on the porch, listen for the small moves that can shift a team, try one in your next meeting, and see what changes. TIME STAMPED NOTES: Intro [00:53] Light banter - A playful start before the main discussion. [01:17] Why culture matters - Good tools and smart teams still fail when culture is off. Defining Culture & The Backyard / System Analogy [02:21] Defining culture - The unwritten rules behind how teams work together. [03:10] Backyard analogy - Culture grows whether you manage it or not. [03:47] Systems drive results - Teams get the outcomes their systems are built for. Who Owns Culture? Leaders, PMs & Product Culture vs Practices [04:43] Who shapes culture - Leaders set the tone, including product managers. [06:29] Team culture matters - Companies are really made up of many team cultures. [08:58] Types of product culture - Outcome vs output, learning vs delivery pressure. [10:56] Culture vs practice - Norms and beliefs are different from process and rituals. Mini-Game: Practice vs Culture & Learning Culture Limits [11:12] Practice or culture - A quick game to separate the two. [11:32] Safe pushback - Psychological safety is culture, not process. [12:43] Saying “I was wrong” - Humility is a sign of a healthy culture. [13:14] Learning culture - Experiments fail when teams are not safe to learn. Culture vs System & The “Red Pill” Realization [13:45] Why teams cannot say no - Culture can drive idea overload. [15:21] What culture allows - Revisiting decisions and changing course when needed. [17:11] Culture inside the system - Culture works alongside people, tools, and process. [18:03] Red pill moment - Culture outweighs frameworks more than most PMs realize. Can Product Managers Influence Culture? Scope, Influence & Tactics [18:44] Can PMs shape culture - The practical question at the center of the episode. [19:30] Scope matters - Focus on your team, not fixing the whole company. [20:26] Team culture examples - How behavior from a PM changes team dynamics. [23:25] Reward the behavior - Reinforce the norms you want more of. [24:54] Model the behavior - Small day-to-day actions shape culture over time. Making Culture Visible & Sussing It Out in Interviews [25:29] Can culture be stated - Whether values on the wall really matter. [26:17] Repeating values - Culture needs to be stated and reinforced. [27:20] Time and trust - Clarifying what matters helps shape team norms. [29:10] Interview the company - Candidates should test for culture fit too. [29:42] Roadmap decisions - A simple question that reveals a lot about culture. Culture Fit: Candidate Signals, Hiring Signals & Misalignment [30:58] Know your values - Start with what matters to you. [32:18] Be yourself - Authenticity makes culture fit easier to spot. [33:04] Watch for defensiveness - Reactions in interviews reveal a lot. [35:09] Hire through stories - Listen for values in how people talk about work. [36:19] Misfits stand out - Strong cultures make bad fits easier to spot. Key Takeaways: PM Influence, Small Moments & Don’t Change Yourself [38:16] You have more influence - PMs can shape more than they think. [38:44] Small moments matter - Culture is built in meetings, decisions, and conflict. [39:46] Do not change yourself - Do not bend yourself to fit a bad culture. [40:09] Find the right fit - Learn what you can, then move toward a better environment. Closing & Credits [40:34] Closing remarks - Final thoughts and sign-off. Help keep the Product Porch lights on by giving at https://www.patreon.com/TheProductPorch Join our email list and never miss an episode at theproductporch.com [https://www.theproductporch.com/email-signup]

The AI Question Product Teams Aren’t Asking: What Happens to PMs and POs?

AI is accelerating product development faster than ever—but product roles haven’t caught up. Todd Blaquiere, Ryan Cantwell, and Joe Ghali tackle the question teams are avoiding: what happens to product managers and product owners in an AI-driven world? The conversation draws a line between execution and real product thinking. Tasks like writing tickets, acceptance criteria, and documentation are increasingly handled by AI, putting pressure on roles built around those activities. But roles don’t disappear—they evolve. Product managers must shift from managing delivery to owning decisions, understanding the business, and driving real value. The team also debates the future of the product owner. While the “ticket writer” fades, a clarity owner remains—connecting strategy to execution and keeping teams aligned as complexity grows. From there, the focus turns to what stays human: customer understanding, real discovery, and emotional intelligence—things AI can support, but not replace. At the center is one idea: the real moat isn’t execution—it’s business understanding. If you’re trying to figure out where you fit in an AI-driven product world, this episode will challenge how you think about your role. Pull up a chair and join the conversation on the porch. TIME STAMPED NOTES:  **Introduction and Setting the Stage** [00:00] AI vs roles – AI is accelerating delivery faster than roles can evolve. [00:45] The core question – What happens to PMs and POs in this shift? [01:30] From fear to focus – Moving from “who loses jobs” to “what skills matter.” **Shifting Product Roles** [02:30] Execution work fades – Tickets, ACs, and docs increasingly handled by AI. [03:45] Role pressure – Execution-heavy roles begin to lose relevance. [05:00] PM evolution – Shift from delivery management to decision ownership. **The Future of the Product Owner** [06:15] Ticket writer decline – Traditional PO work becomes automated. [07:30] Clarity owner – Need for sequencing, alignment, and readiness remains. [08:45] Enterprise complexity – Dependencies and coordination still require humans. **AI Agents and Product Work** [10:00] AI in practice – Agents generating requirements and product artifacts. [11:30] Lower barrier – Less-experienced team members can produce quality output. [12:45] New role – PMs begin coordinating and leveraging AI agents. **What Stays Human** [14:00] Customer understanding – Real conversations drive better insight. [15:30] Limits of AI – AI can replicate patterns, not authentic empathy. [17:00] Emotional intelligence – Influence, trust, and buy-in remain human skills. **The PM’s Moat: Business Understanding** [18:30] Business context – Understanding value flow and market matters most. [20:00] Decision-making – PMs must own trade-offs, not defer to AI. [21:30] Systems thinking – Seeing the full business and product ecosystem. **The Future Product Team** [23:00] Agent orchestration – PMs manage systems of humans and AI. [24:30] Role convergence – PM, UX, and engineering boundaries blur. [26:00] Changing ratios – Fewer engineers per PM as AI increases leverage. **Closing Thoughts** [28:00] Are we ready? – Many PMs aren’t set up for this shift yet. [29:30] How to prepare – Focus on business, customers, and systems. [31:00] Optimistic future – Strategy and product thinking matter more than ever. Help keep the Product Porch lights on by giving at https://www.patreon.com/TheProductPorch Join our email list and never miss an episode at theproductporch.com [https://www.theproductporch.com/email-signup]