Kent talks with Alex Hillman of Stacking the Bricks about customer research, product fit, and the kind of product engineering that starts before implementation: understanding who you are serving, what they already believe, and how to make people feel understood instead of sold to.

They cover audience selection, observational research, helping in public, aligning your work with customer and business priorities, and why AI makes human judgment, trust, and synthesis more important rather than less.

Alex brings a product and marketing lens that fits this season perfectly: great products do not just solve technical problems, they help the right people recognize that you understand their world. The conversation starts with finding an audience and quickly turns into a practical way to build product sense inside a company: learn how customers describe themselves, observe where they gather, listen for the language they use, and speak from their priorities instead of your own taste.

The second half gets into Sales Safari, Stacking the Bricks' observational research practice. Alex explains why surveys and interviews can miss important signal, what to look for in real conversations, and how notes on jargon, pain, worldview, and recommendations can turn scattered internet conversations into useful product understanding. The through-line is simple and demanding: reduce the distance between you and the people you serve so your software, messaging, and decisions feel anticipated rather than manipulative.

Homework

• The next time coworkers or product teammates disagree about direction, step back and observe the conversation.
• Ask: who is this disagreement in service of? Is it serving the customer, the decision maker, the loudest person, or someone else?
• Practice this once a day or once a week, then use the patterns you notice to decide what you should contribute.

Resources

• Stacking the Bricks
• 30x500
• The Tiny MBA
• The Mom Test
• Alex Hillman on X

Guest: Alex Hillman

• Company: Stacking the Bricks
• GitHub: @alexknowshtml
• 𝕏: @alexhillman

Host: Kent C. Dodds

• Website: kentcdodds.com
• 𝕏: @kentcdodds
• GitHub: @kentcdodds
• YouTube: Kent C. Dodds
• Podcast: epicproduct.engineer

Video

Watch this episode

Kent talks with Julius Marminge about building T3 Code in the agent-orchestrator wave: why speed still matters, why fast shipping does not mean shipping every possible feature, and how product judgment becomes more important as parallel AI workflows make implementation cheap.

They dig into dogfooding, core-product trade-offs, monetization pressure, customization vs defaults, and how to keep agent-built software maintainable over time.

Julius is building right in the middle of one of the fastest-moving product categories in software, and that gives this episode a useful tension: everything feels possible, but that does not mean everything belongs in the product. The conversation covers the shift from one-agent-at-a-time coding to orchestration, why T3 Code focuses so much on a fast app layer, and how Julius thinks about what should live in the core product versus forks, plugins, or future work.

The deeper lesson is about judgment under speed. Julius and Kent keep returning to the same idea from different angles: when agents can generate a lot of implementation quickly, the real work is deciding what is worth building, what will age well, and what future decisions you might accidentally box yourself out of.

Homework

• Take a step back and look at your product from the whole picture, not just the slice you currently touch.
• Before prioritizing a feature, ask whether it keeps the product maintainable long-term and whether it fits the job to be done for your users.

Resources

• T3 Code
• T3 Chat
• Julius Marminge — GitHub
• OpenCode

Guest: Julius Marminge

• GitHub: @juliusmarminge
• 𝕏: @jullerino

Host: Kent C. Dodds

• Website: kentcdodds.com
• 𝕏: @kentcdodds
• GitHub: @kentcdodds
• YouTube: Kent C. Dodds
• Podcast: epicproduct.engineer

Video

Watch this episode

Kent talks with Jamon Holmgren about product engineering from a long-running consultancy lens: how working with clients, stakeholders, and non-technical users sharpens your product sense, and why those skills matter even more as implementation gets cheaper with AI.

They cover React Native, consulting, game design, stakeholder failures, feedback loops, and what software builders need to keep learning as the job shifts up the stack.

Jamon brings a useful mix to this conversation: founder of Infinite Red, longtime consultant, React Native specialist, and now indie game developer. That perspective makes the episode unusually practical. He has spent years watching where projects go wrong when product thinking is weak: bad requirements, unclear stakeholder alignment, UX details nobody owned, and engineers optimizing the wrong thing too early.

The thread through the whole episode is durability. Product engineering is not just about shipping faster with agents or getting better at a specific tool. It is about understanding people, shaping better requirements, recognizing when the human side of the workflow matters more than the code, and making decisions that keep paying off as the technology changes around you.

Homework

• Sit down with a non-technical person and watch them try to use a feature you built.
• Write down every hesitation, workaround, double-click, or confusing step you notice, then use that list to reprioritize what you fix next.

Resources

• Infinite Red
• Jamon Holmgren — site
• Night Shift Agentic Workflow
• Gunship Origins on Steam

Guest: Jamon Holmgren

• Company: Infinite Red
• GitHub: @jamonholmgren
• 𝕏: @jamonholmgren

Host: Kent C. Dodds

• Website: kentcdodds.com
• 𝕏: @kentcdodds
• GitHub: @kentcdodds
• YouTube: Kent C. Dodds
• Podcast: epicproduct.engineer

Video

Watch this episode

Kent talks with Don Norman about why the core work of product engineering has not changed: watch people work, treat so-called user error as a design problem, and fix root causes instead of blaming symptoms.

Don walks through a remarkable arc from electrical engineering and cognitive psychology to Three Mile Island, Xerox PARC, Apple, and the first use of user experience in a job title. They talk about timing and failed products, cross-functional product teams, what AI changes for software builders, and why Don now cares most about designing for humanity, not only usability.

Don's career makes this episode unusually wide-ranging: early computing, human error, aviation safety, Unix, Apple product decisions, digital cameras, color TV, and the long arc from usable products to systems that shape society. The through-line is straightforward but demanding: if you want better products, watch what people actually do, notice the workarounds they no longer complain about, and treat clusters of small usability problems like real product debt.

The second half brings that thinking into the present. Don and Kent talk about AI coding tools as force multipliers that still need direction, architecture, and supervision, then zoom out to Design for a Better World and the Don Norman Design Award. The result is a conversation about product sense that spans decades without feeling dated: the tools change, but the responsibility to understand people, systems, and consequences does not.

Homework

• Spend time watching people do real work before you ask them for solutions; observation reveals the hidden setup, workarounds, and friction they now assume are just "how it works."
• After a release, step back and fix clusters of small usability issues as a system instead of waiting for one confusing bug to become catastrophic.
• Treat AI as a force multiplier you must instruct and supervise; stay responsible for the problem definition, architecture, and review.

Resources

• Don Norman Design Award (DNDA)
• Design for a Better World
• The Design of Everyday Things
• Nielsen Norman Group — Don Norman
• United Nations Sustainable Development Goals

Guest: Don Norman

• Company: Don Norman Design Award (DNDA)

Host: Kent C. Dodds

• Website: kentcdodds.com
• 𝕏: @kentcdodds
• GitHub: @kentcdodds
• YouTube: Kent C. Dodds
• Podcast: epicproduct.engineer

Video

Watch this episode

Kent talks with Will King about bringing an industrial design mindset into software: human factors, observing real users, and why good product engineering starts with caring enough to notice what frustrates people.

They dig into product debt, support as a product superpower, pruning features without breaking trust, and how to use AI agents for exploration and critique instead of only faster implementation.

Will's path runs from designing bucket trucks to self-taught software engineering, education products, and database tooling, and that background gives this episode a distinctive lens: software is still a product people use with bodies, habits, emotions, and mental models. The conversation makes product sense concrete through examples like onboarding timing, course complexity, support workflows, and the small confidence signals that separate stable-feeling products from merely functional ones.

You'll hear why watching users work keeps surfacing across this series, how to tell broken experiences from merely unpopular ones, why user feedback usually improves polish more than strategy, and how product engineers can stay valuable in an agent-heavy future by understanding both the user and the constraints of the software medium.

Homework

• Use AI agents more for gathering than executing: explore multiple solution paths, adjacent domains, and missing context before you ship.
• Give agents richer context like user demographics, constraints, and likely mental models, then use your own judgment to evaluate what comes back.
• Slow down long enough to question assumptions before implementation; use AI as a creativity and critique tool, not just a code accelerator.

Resources

• Will King - site
• Deploy Empathy (Michele Hansen)
• The Mom Test (Rob Fitzpatrick)
• Interface Craft (Josh Puckett)

Guest: Will King

• Company: Crunchy Data
• GitHub: @wking-io
• 𝕏: @willking

Host: Kent C. Dodds

• Website: kentcdodds.com
• 𝕏: @kentcdodds
• GitHub: @kentcdodds
• YouTube: Kent C. Dodds
• Podcast: epicproduct.engineer

Video

Watch this episode