Quality during Design

Fear is one reason teams jump from an idea to a solution before they understand the problem. It does not always look like panic. It can look like adding another inspection, building a feature that can be placed on a chart, accepting the answer from the person with the most authority, or avoiding a decision altogether. In this solo compilation episode, Dianna Deeney asks four contributors how fear...

Ashley Phillips joins Dianna to discuss how customer discovery changes across startups, hypergrowth teams, and established products. Customers may surprise a team with new ways to use a product, while the environment around a long-standing product can change enough to make old assumptions stale. Ashley shares examples from Venmo, Groupon, and Aura Frames, and explains why direct customer contact,...

In this solo episode of Quality during Design, Dianna looks at two reasons product development teams jump from a partial understanding of a problem to a committed solution: speed and certainty.  Fast prototyping, generative AI, and 3D printing can make building feel harmless, but activity only creates value when it answers a specific question and informs a decision.  Certainty can create the same...

Fast prototyping changes the constraint. When software, AI tools, and other rapid-prototyping methods make it inexpensive to turn an idea into something testable, the challenge is no longer only Can we build it? The harder questions become: What should we build? Who is it for? What evidence do we need? When should we stop tweaking and get it in front of people? Which decisions are reversible—and w...

When a project goes off track, we usually look back and say, “We didn’t define the problem, and we jumped.” That sounds like a process breakdown, as if one good checklist or gate approval would have prevented it. But design fog runs deeper than missing process. It’s what’s happening in us. Over the next few episodes on Quality During Design, we’re exploring a quieter question: When we jump to a so...

Why do well-designed initiatives keep coming apart when they reach reality?  Mike Fedorov , who spent 26 years in supply chain and operations at Mars and Accenture and now co-leads Applied AI Labs , explains that the failure usually isn’t a bad call inside a single design. It’s the coordination layer: the seams between teams, systems, and the data that no one remembers how to work.  He walks throu...

A cross-functional team can make what seems like a solid Friday decision, captured in minutes and agreed to in the room. Only then nothing moves on Monday.  Drawing on Agnes Carroll’s observation that “no one is carrying it,” the episode argues this decision room carry problem isn’t solved by better documentation or tools like Jira and decision matrices, because an assigned decision is not an auth...

In this milestone episode, Dianna reflects on how the thinking evolved from quality methods to product development processes, to team dynamics, and ultimately to one central idea: Quality during Design happens when teams align early and think together intentionally. In this episode  The question that has guided all 200 episodes   Why good engineering teams still build products that miss the mark ...

Why do product teams stay misaligned? Jenny Wanger explains the structural problems: efficiency-focused handoff workflows, unclear strategy, and people left cleaning up decisions they didn't help make. She shares tested practices for influencing upstream decisions without formal authority: clarifying strategy through curiosity, bringing the right people in early (pre-mortems work), and public...

The episode features Chad Schneider, CEO and founder of Root3 Labs , discussing prototyping as a discipline focused on answering specific questions to reduce technical, schedule, and market risk.  He explains that prototypes need not resemble the final product, citing examples like using a cardboard mockup to verify hand access for connectors and 3D-printed sizing models to understand surgical con...

Engineering rework often comes from unasked questions or using the wrong tool at the wrong fidelity.  Dianna outlines three common prototyping traps:  the “ta-da” trap, where teams build polished prototypes to impress stakeholders before the concept is stable, anchoring the team to an early solution the “I’m smarter than cardboard” trap, where engineers skip low-fidelity physical models in favor o...

Most of the social conversation around AI is aimed at business owners and programmers, but if you’re an engineer or quality professional, you might be wondering how to actually use these tools to help with your own work processes or information pools . While many people are waiting for their company to provide an AI strategy, there is a way to start building your own private "AI intern"...

Late-breaking insights in product development aren’t caused by negligence but by a lack of structure that pulls existing team knowledge into concept discussions early, when changes are cheaper.  Dianna describes an experiment running three product briefs (solar post-installation support, a portable oxygen concentrator, and a field lettuce harvester module) through traditional versus structured con...

The episode features Cassie Leonard—former aerospace technical leader, executive coach, and author of STEM Moms and Beyond the Pipeline —explaining why the traditional linear “pipeline” model of engineering careers is constricting and mislabels non-linear moves as failure.  Drawing on expectancy-value theory, she presents an ROI-style equation for decisions: attainment, intrinsic, and utility valu...

Your team keeps solving the exact same problems project after project. What if the issue isn't careless execution, but a reactive system designed to hide failures rather than learn from them?  In this episode: • Discover how protective, reactive systems create "quiet" organizations where vital failure data gets buried instead of shared. • Learn the three essential shifts high-perfor...

Your team keeps building the wrong thing, despite great effort. What if the problem isn’t execution. It’s the fog you’re navigating in? We speak with Shannon Cummings , a seasoned product and marketing strategist who’s spent his career bridging the gap between Marketing, Product, and Engineering. He’s launched life-changing medical devices, cut development time in half, and done it all by bringing...

Have you ever walked into a meeting (design review, planning session, phase gate) only to realize the decision was already made? That the discussion was just theater, not dialogue? You weren’t there to shape the outcome. You were there to witness it.  If that’s happened to you, you’re not alone. In this episode, Dianna explores why this happens, why it feels so frustrating, and most importantly ho...

In this episode of 'Quality during Design', we delve into how engineers can avoid mistakes and oversights by managing stress and enhancing performance.  Host Dianna Deeney interviews Karli Auble, an engineering leader at a global firm in the defense industry. She has unique expertise in systems engineering and positive psychology, with a master's degree in both disciplines. Karli sh...

Your team keeps brainstorming into a void, producing “meh” ideas that never stick. What if the problem isn’t a lack of creativity but the absence of the right constraints ? In this episode: • The Goldilocks principle of team creativity – why no guardrails and too‑many guardrails both kill innovation. • Frameworks unlock, don’t limit, creativity – using the drummers‑without‑drums analogy to show ho...

Early concept development often fails because teams lack clarity and alignment, leading to wasted time and resources. Discover the structured approach needed to cut through the "design fog" and ensure your team is building the right product from the start. In this episode: • The Concept Space Model defines the fundamental questions teams must align on before diving into technical details...

Your team spent six weeks on a feature that got rejected in the demo. Your engineers built a prototype that totally missed the mark. This misalignment is the design fog , and it’s where most product failures are born in the uncomfortable space of the fuzzy front end. In this episode: • Learn why jumping to prototypes introduces fixedness , robbing your team of the chance to define true user requir...

Ever face a late-stage design decision where your gut says “maybe,” finance says “no,” and the schedule says “hurry”?  We unpack a simple way to make those calls with more clarity: using expected value to connect confidence, upside, and downside into one sober view of net benefit. No jargon, no spreadsheets required—just a clear framework that helps you see when a $50,000 test buys real certainty,...

When pursuing aggressive benchmarks, engineers must employ portfolio thinking , running multiple design projects simultaneously. But choosing winners requires a decisive way to eliminate projects that are not feasible to continue innovating, often referred to as a "project killer".  In this episode, we analyze Tesla's battery development as a case study. We delve into their use of f...

We turn late-stage design surprises into a strategic plan by assigning explicit confidence levels, stacking evidence, and using the three-dial model of time, cost, and confidence boost. We show how to work backward from a system test to cheaper steps that drive faster, clearer decisions. • applying the three dials of time, cost, confidence • sequencing with the work-backwards strategy • avoiding o...

Late-stage design just hit a snag—now comes the moment that separates guesswork from great engineering. We walk through a clear, repeatable method to investigate unexpected failures and make high-impact decisions with confidence. Instead of hunting for a perfect test, we set a confidence target and stack multiple forms of imperfect evidence until we close the gap. If you’re navigating late-stage p...