27 Oct 2026 Defining What Good Looks Like
"Explores AI product development challenges, emphasizing measurable outcomes, customer-centric evaluation, cross-functional collaboration, and real-world impact over technical metrics."
More All Things Product episodes

Published 22 Sept 2026
Recommended: What you throw away shows you what you value.
Duration: 00:20:02
"Trash can tracking measures product feature success by analyzing discarded ideas, emphasizing early experimentation, clear decision-making, and leadership's role in fostering a culture that discards misaligned or low-value solutions."
What if the ideas you throw away tell you more about the health of your product process than the ones you ship? In this episode of All Things Product,...
The podcast discusses the concept of "trash can tracking" as a way to measure the effectiveness of product discovery and innovation. This metaphor represents features or ideas that are discarded either because they address non-strategic problems or fail in solution validation. The distinction is made between early-stage discards - problems deemed irrelevant or low-impact - and later-stage discards, where valid problems are paired with ineffective solutions. These "trash cans" serve as indicators of a healthy discovery process, reflecting a team's ability to filter ideas, experiment, and make intentional decisions.
A key focus is on creating systems and visibility around discovery work, such as using dedicated task boards for research and experimentation, similar to those used in product delivery. The discussion emphasizes the importance of psychological safety, strategic clarity, and organizational culture in enabling teams to say "no" to certain customer problems. An empty or overused trash can can signal underlying issues - such as lack of innovation, poor prioritization, or hierarchical pressure - requiring experienced judgment to interpret. Ultimately, discarding ideas is framed not as failure but as evidence of learning, progress, and disciplined innovation.
What if you implemented a personal "trash can" system to track discarded features and problems in your solo software business?
What if you made your discovery work as visible as your code commits?
What if you institutionalized saying "no" to customer feature requests using a trash can ritual?
Use a "Golden Trash Can" or "Dump Truck" to track features that were built, released, and later discarded due to failure in discovery or execution.
Maintain a discovery board with columns for understanding the problem space, defining context, and running experiments to assess focus.
Add early-stage trash cans in the problem space to discard irrelevant or non-strategic problems before solution work begins.
Add later-stage trash cans in the solution space to discard prototypes or solutions that fail user validation, even if the problem was valid.
If few ideas are discarded in the problem space, it may indicate insufficient innovation or strategic focus; investigate and adjust.
If few solutions are discarded in the solution space, it suggests a lack of experimentation or option exploration; encourage multiple iterations.
Use a structured framework to assess customer problems against product vision, strategy, and goals before deciding to solve them.
Foster psychological safety so teams feel empowered to push back on low-value problems, avoiding command-and-control hierarchy.
Make discovery work as visible as delivery work by using task boards for both discovery and delivery.
Create a ritual of moving discarded problems to a "trash can" to prevent "zombie opportunities" from being repeatedly discussed without resolution.
Interpret an empty trash can with caution: it may signal strong strategic alignment or a lack of innovation - analyze the root cause.
Senior product leaders should help teams interpret whether empty or full trash cans indicate innovation gaps, hierarchy issues, or effective strategy.
27 Oct 2026 Defining What Good Looks Like
"Explores AI product development challenges, emphasizing measurable outcomes, customer-centric evaluation, cross-functional collaboration, and real-world impact over technical metrics."
13 Oct 2026 Training Expectations
"Continuous product discovery training requires habit-building and practice, not just short sessions, as teams often underestimate the depth of skill development needed for mastery."
6 Oct 2026 Recorded Conversations
"AI and technology's role in recording conversations raises ethical, psychological, and social challenges, including trust, evolving opinions, memory inaccuracies, and the impact of transcripts on relationships and accountability."
29 Sept 2026 Unpacking Innovation
"Innovation in product development prioritizes solving user problems through simplicity and usability, balancing novel solutions with proven methods to avoid unnecessary complexity, driven by cross-functional collaboration and real user needs."
15 Sept 2026 Delivery Isn't Free
"AI cuts software costs but demands skilled engineering for maintenance, security, and scaling, with rapid feature expansion risking spaghetti code and inefficiency - production-grade AI products require traditional best practices and significant refinement."