Become an Epic Product Engineer

Kent C. Dodds

Become an Epic Product Engineer is Kent C. Dodds's interview podcast about skills that stay valuable as AI takes on more implementation: product engineering - blending technical depth with product judgment, user empathy, and problem clarity. Each episode is a long-form conversation with a guest who has shipped real software and cares about building the right thing before making it right. You get full audio, transcripts, structured show notes, homework (one concrete action to try), and links from the conversation. Canonical home for the show and every episode page: https://www.epicproduct.engineer/become-an-epic-product-engineer-podcast New episodes publish on Wednesdays (America/Denver). Video is added on Transistor for supported podcast apps when available. Complements Better with Kent - Kent's solo series on durable skills for people who ship software.

  1. 3 days ago ·  Video

    Use the product yourself - empathy, architecture, and PM partnership with Rita Kozlov

    If you ship a feature and never click through it yourself, this episode is for you. Kent talks with Rita Kozlov, VP of Product for Cloudflare's developer platform, about the line between product managers and product engineers, why ownership still matters when prototypes look real, and how far upstream an engineer should insert themselves. They cover holding the pager vs throwing away a prototype, sitting in customer calls until someone will not click the button, primitives vs paved paths, and what to do when your PM is running a feature factory. (00:00) - Meet Rita Kozlov (01:36) - Engineering taste in a PM role (04:05) - Where PM and product engineer blur (07:53) - You are not holding the pager (09:48) - What AI changed on both sides (13:40) - Sit in the user's seat (17:04) - The art of the possible (18:53) - Trade-offs and why not both (23:22) - Primitives vs paved cow paths (26:43) - Insert yourself upstream (29:40) - When the PM is a feature factory (33:17) - Deep-stack work still reaches users (37:58) - Homework: go use the product Rita Kozlov is VP of Product for Cloudflare's developer platform - Workers, KV, Pages, and the rest of the stack Kent uses constantly. She started as a software engineer, and that background shows up in the details: taste for developer experience, intuition for patterns that do not sit right, and a refusal to treat implementation as someone else's problem. A major theme is how AI blurred the PM and engineer line. Prototypes are worth a million words, and they create a temptation to ship the facade. Rita's reminder to her product team: you are not the one holding the pager. Accountability is not about having someone to call at 2 a.m. It is about living with the code for the next two years. Product engineers close that gap by translating implementation trade-offs, filling the holes a PRD will never list, and sitting in the user's seat - including the customer call where nobody clicks the button. They also get into Cloudflare-shaped product judgment: most doors swing both ways if you wait; early customers are worth delaying a launch for; primitives can serve many jobs, and sometimes you still pave a cow path. Rita wants PMs to define the problem, not the solution. Engineers should get closer to customers, challenge a feature-factory PM with why, and remember that even work deep in the stack - cache, TTL, the interface between systems - is user experience. Homework is basic on purpose: go use the product, including the feature you just shipped, and push it before you throw it over the fence. Homework Use the product you work on this week - not as a demo path, as a real user.After you ship a feature, try it in the different modalities and push the limits before you hand it off.Write down what you found that you would have missed from the ticket alone. Resources Rita KozlovRita on XRita on BlueskyRita on GitHubRita on LinkedInCloudflare WorkersCloudflare Guest: Rita Kozlov Company: CloudflareGitHub: @rita3ko𝕏: @ritakozlov_ Host: Kent C. Dodds Website: kentcdodds.com𝕏: @kentcdoddsGitHub: @kentcdoddsYouTube: kentcdodds-plusPodcast: epicproduct.engineer See on Epic Product Engineer

    Use the product yourself - empathy, architecture, and PM partnership with Rita Kozlov

  2. 9 Sept ·  Video

    Ask why in every PR - product engineering with Erin Fox

    If you are merging beautiful AI PRs without being able to say why the change exists, this episode is for you. Kent talks with Erin Fox about treating every feature like a new product, asking why before you write code, and rebuilding the trust contract that agents quietly broke. They cover circling back to metrics, using community Slack as a feedback loop, telling a stakeholder story that is not just a migration estimate, and going slower with agents so they do not rewrite your patterns. (00:00) - Meet Erin Fox (01:40) - A new feature is a new product (05:03) - Finding the why before you build (07:36) - AI PRs broke the trust contract (10:57) - Metrics, research, and circling back (14:25) - Community Slack as a feedback loop (16:17) - Tell the story stakeholders can hear (20:49) - Communications skills as an engineering edge (24:12) - Ask your boss their goals (27:22) - Go slower with your agents (37:50) - Homework: ask why on every PR Erin Fox is a full-stack engineer who has shipped a React Native MLS soccer app, creator-focused email tools, and plenty of features that felt like launching a product each time. In this conversation, she and Kent dig into what that framing changes: you do not just implement a ticket. You figure out the date, the why, and whether the real fix is a new feature or a two-hour margin change. A major theme is trust. Erin used to assume a teammate's PR already had the why baked in. AI-generated PRs look great and pass tests, but the why is often missing. Her red flag is simple: if you cannot explain why this change is needed, do not treat passing tests as permission. That same question belongs in the PR template, in stakeholder conversations, and in how you brief an agent - because "fix this bug" will happily change a million things. They also get practical about feedback loops. Look at the metrics you instrumented. Lurk in community Slack, including accessibility channels, until user pain is not abstract. Then tell the story in language stakeholders care about: not "this migration takes a quarter," but what it unlocks. Erin's communications master's degree shows up here. She asks her manager what their goals are this quarter and treats that as the job. Homework is small on purpose: on every PR you open or review, write why this change matters. Homework On the next PR you open, add a Why section that a teammate could understand without the ticket.On the next PR you review, ask why this change is needed - especially if it looks AI-generated.If you cannot answer why, stop and find out before you merge. Resources Erin Fox on XErin on BlueskyErin on GitHubErin on LinkedInKit Guest: Erin Fox GitHub: @erinfox𝕏: @erinfoox Host: Kent C. Dodds Website: kentcdodds.com𝕏: @kentcdoddsGitHub: @kentcdoddsYouTube: kentcdodds-plusPodcast: epicproduct.engineer See on Epic Product Engineer

    Ask why in every PR - product engineering with Erin Fox

  3. 2 Sept ·  Video

    AI is a tool, not a silver bullet - product discovery with Peppe Silletti

    If shipping got cheap and you are still not sure you are building the right thing, this episode is for you. Kent talks with Peppe Silletti, independent product engineer and host of The Product Engineers Podcast, about why customer discovery still comes first when AI can write the code in a day. They cover startup vs scale-up trade-offs, raising the MVP baseline without adding noise, how PostHog treats product engineers vs product managers, and the durable skills that stay valuable when agents take more of the implementation. (00:00) - Meet Peppe Silletti (01:13) - Startup exploration vs scale-up bottlenecks (04:04) - Trade-offs before you paint yourself into a corner (06:07) - AI raises the MVP baseline (09:47) - Do not add so much that the data gets noisy (11:13) - AI is a tool, not a silver bullet (13:47) - Product engineers are not just managers (16:06) - How you know you built too much (18:49) - Prioritizing after product-market fit (24:30) - PM as compass, engineer as slice owner (27:08) - What Peppe learned hosting a podcast (29:25) - Durable skills as agents take the code (33:06) - Product engineering for backend engineers (38:26) - Homework: ally with your PM Peppe Silletti is an independent product engineer and host of The Product Engineers Podcast. In this conversation, he and Kent dig into what changes when you move from a startup hunting for product-market fit to a scale-up fixing bottlenecks - and what AI does and does not change about that work. A major theme is that writing code got cheap, so the old lean-startup constraint loosened. You can ship more than a classic MVP, then sculpt features away like Instagram dropping everything but photos. The risk did not go away. It got worse. You can feel productive while running in the wrong direction, because AI will happily agree with you. Discovery, customer interviews, and a tight feedback loop still decide whether you are learning or just shipping. They also unpack the product manager vs product engineer split. Peppe points to PostHog: product engineers owned decisions for years before a PM showed up to hold the bigger picture. His model is a PM as compass, a product engineer owning one outcome end to end. For listeners who still take tickets over the wall, the durable skills are framing the problem, interviewing without jumping to solutions, and treating UX as more than pixels - including APIs and neighboring layers of the system. Peppe's homework is deliberately social: shadow customer interviews, watch session replays with your team, and get into discovery before the roadmap is locked. Homework Ask your PM if you can shadow customer interviews and listen for how people describe the pain.Set a weekly half hour to watch session replays with your team and name the friction you see.Once those two are happening, ask to join discovery earlier - when requirements and the roadmap are still being shaped. Resources Peppe SillettiThe Product Engineers PodcastPeppe on LinkedInPeppe on GitHubThe Product Engineers Podcast on YouTubeProduct management is broken. Engineers can fix it - PostHogContinuous Discovery Habits by Teresa TorresLaws of UX by Jon Yablonski Guest: Peppe Silletti Company: The Product Engineers PodcastGitHub: @peppesilletti𝕏: @peppesilletti Host: Kent C. Dodds Website: kentcdodds.com𝕏: @kentcdoddsGitHub: @kentcdoddsYouTube: kentcdodds-plusPodcast: epicproduct.engineer See on Epic Product Engineer

    AI is a tool, not a silver bullet - product discovery with Peppe Silletti

  4. 19 Aug ·  Video

    Curiosity, micro-sales, and AI as a supplement with Shaundai Person

    If you walk into cross-team asks with a prescription instead of curiosity, this episode is for you. Kent talks with Shaundai Person about privacy UX at Netflix, the micro-sales skills she brought from a decade in sales, and why AI should accelerate good engineering judgment instead of replacing it. They cover putting yourself in the user's seat before you push back, selling the conversation instead of the ticket, what happens when agents fill a repo with band-aids, and homework that gets you out of your usual domain: try a CSS animation course without AI. (00:00) - Meet Shaundai Person (00:51) - Privacy and consent at Netflix (04:30) - What privacy engineering actually involves (08:38) - Push back with user scenarios (11:10) - UX so intuitive a toddler can use it (13:43) - Working through technical constraints (18:45) - Micro-sales from a sales career (22:32) - Curiosity is not manipulation (25:47) - AI's impact on software engineering (29:42) - Agent band-aids and architecture gaps (35:40) - New criteria for senior engineers (37:35) - AI accelerates bad practices too (40:51) - AI as a supplement, not a replacement (45:09) - Homework: try animations without AI Shaundai Person is a senior software engineer at Netflix working full stack on privacy and consent for Netflix.com. In this conversation, she and Kent dig into what product engineering looks like when the work is mostly invisible when you do it right - and when your job is piping the right experience to the right person under different laws, profiles, and countries. A major theme is how she communicates across teams. After more than a decade in sales before engineering, Shaundai treats collaboration as a series of micro-sales: get someone into the conversation, then into a small piece of work, then into teaching you how they solved it. She argues smart people do not want prescriptions. They want curiosity, a clear goal, a map of where they fit, and an invitation to dissent. They also talk about AI's impact on software engineering. Shaundai sees AI elevating more engineers toward architecture and product thinking, while warning that unchecked agents create pattern-free codebases full of band-aids. Her take: humans stay in the loop because software is for humans, and AI is a supplement - not a replacement. Her homework is specific: try Josh Comeau's Whimsical Animations (or its CSS-based starter path) and do the first stretch without AI. Homework Start Josh Comeau's Whimsical Animations (or the free CSS-based starter path).Do the first stretch without AI - refresh your own problem-solving muscle.Notice how far you get on your own, then decide where a tool would actually help.Resources Shaundai PersonShaundai on BlueskyShaundai on XShaundai on GitHubShaundai on LinkedInTypeScript for JavaScript DevelopersWhimsical Animations by Josh ComeauNetflixGuest: Shaundai Person Company: NetflixGitHub: @shaundai𝕏: @shaundaiHost: Kent C. Dodds Website: kentcdodds.com𝕏: @kentcdoddsGitHub: @kentcdoddsYouTube: kentcdodds-plusPodcast: epicproduct.engineerSee on Epic Product Engineer

    Curiosity, micro-sales, and AI as a supplement with Shaundai Person

  5. 12 Aug ·  Video

    Talk to users, ship live demos, and build durable products with Michael Grinich

    If you are building something people want but still cannot grow it, this episode is for you. Kent talks with Michael Grinich, founder of WorkOS, about cold-emailing product managers, closing the feedback loop with real users, and why live demos beat polished decks. They cover the missing step after "make something people want," how durable problem spaces survive market shifts (including auth for agents), and why storytelling is part of the product. (00:00) - Meet Michael Grinich (02:00) - Choosing the enterprise-ready niche (04:31) - Building for problems that are not yours (06:34) - Cold-emailing PMs who already shipped enterprise (10:44) - Questions that get past compliments (12:52) - Patience and durable problem spaces (15:57) - Beyond make something people want (20:25) - Auth for agents and MCP (23:57) - Talk to users, not just customers (28:42) - Live demos as tech marketing (31:39) - Test your story like Comedy Cellar material (39:10) - Monkey see, monkey do and Julia Child (43:03) - Homework: build GPT from scratch (46:10) - Where to follow Michael Michael Grinich founded WorkOS to help software companies become enterprise-ready - SSO, directory sync, permissions, audit logging, and the rest of the stack that unlocks bigger customers. In this conversation, he and Kent dig into how that idea came from lived pain at a previous startup, and how he validated the market by cold-emailing and meeting PMs at companies like Dropbox, Slack, Asana, and Airtable. A major theme is that "make something people want" is incomplete. Michael argues you also need an economic engine: who pays, why they pay continuously, and how the business model stays in harmony with the product. He ties that to picking durable problem spaces - WorkOS started in classic B2B auth, and the same foundation now matters even more for agents, MCP, and agent registration via auth.md. They also get practical about product discovery. Talk to users, not only customers and dollar signs. Use live demos as the pinnacle of tech marketing. Treat small meetups like a Comedy Cellar set where you test material before the big stage. And when you show people how something works, you put yourself on the same side of the table - the Julia Child model of teaching by doing. Michael's homework is concrete: spend an afternoon with Andrej Karpathy's "Let's build GPT from scratch" video so you understand the underpinnings of the systems you are building on. Homework Watch Andrej Karpathy's "Let's build GPT from scratch" video (a few hours, one afternoon is enough).Hack along enough to rebuild a simple ChatGPT-like interface on top of a transformer you understand.Notice how that deeper mental model changes how you talk about agents, models, and product bets at work.Resources Michael Grinich on XMichael on GitHubMichael on LinkedInMichael on BlueskyWorkOSauth.mdauth.md on GitHubWorkOS events on LumaLet's build GPT from scratch (Andrej Karpathy)The Mom TestGuest: Michael Grinich Company: WorkOSGitHub: @grinich𝕏: @grinichHost: Kent C. Dodds Website: kentcdodds.com𝕏: @kentcdoddsGitHub: @kentcdoddsYouTube: kentcdodds-plusPodcast: epicproduct.engineerSee on Epic Product Engineer

    Talk to users, ship live demos, and build durable products with Michael Grinich

  6. 5 Aug ·  Video

    Write it down: process, benchmarking, and product judgment with Ronan Berder

    If you ship features before you can explain the process, this episode is for you. Kent talks with Ronan Berder about building consumer products at Nike, Hilton, and Burberry scale in China, why engineers need to leave the IDE, and why a process you have not written down is not a process. They cover aligning teams on product vision, benchmarking competitors before you invent, design boundaries that unlock creativity, consulting failures from expectation gaps, and the homework that sounds too simple: write down what you are struggling with. (00:00) - Meet Ronan Berder (01:53) - Shipping at China consumer scale (03:42) - Partner vs vendor: strategy before build (09:02) - Aligning engineers on product vision (15:56) - Benchmark competitors before you invent (17:35) - Design systems, boundaries, and process (22:42) - If it is not written down, you do not have a process (28:40) - Process scale: five people vs 160 (33:21) - Horizontal skills beyond the IDE (34:15) - Abstraction layers in the business (39:44) - Talking with VPs and C-suite (44:49) - Consulting failures and expectation gaps (50:48) - When clients insist on bad bets (53:39) - Large companies lack creativity (58:23) - Homework: write down your struggles Ronan Berder founded Wiredcraft in Shanghai, grew it past 160 people, and sold it after years of shipping localized consumer apps for brands like Nike, Hilton, Burberry, and Adidas - often to tens of millions of users on day one. In this conversation, he and Kent dig into what product engineering looks like when you are a partner to VPs and C-suite, not a ticket-taking vendor. A major theme is process as a creative constraint. Ronan argues designers and engineers need boundaries, shared definitions, and written playbooks - not because bureaucracy is fun, but because you cannot improve what you never articulated. He is blunt about engineers who never benchmark competitors, teams that chase cool campaigns over boring work that moves sales, and consulting failures that come from expectation gaps more often than from bad code. They also talk about AI making pure implementation more replaceable, why understanding one layer above and below your work still matters, and how large companies rarely invent the creative bets that startups do. Ronan's homework is simple: whatever you are struggling with right now, write it down and organize your thoughts. Homework Pick one thing you are struggling with in your work right now.Write it down and organize your thoughts until the gaps are visible.Share the written version with a teammate and use it to align on what 'done' means.Resources Ronan BerderRonan on XRonan on GitHubRonan on LinkedInRotsuWiredcraftGuest: Ronan Berder Company: RotsuGitHub: @hunvreus𝕏: @hunvreusHost: Kent C. Dodds Website: kentcdodds.com𝕏: @kentcdoddsGitHub: @kentcdoddsYouTube: kentcdodds-plusPodcast: epicproduct.engineerSee on Epic Product Engineer

    Write it down: process, benchmarking, and product judgment with Ronan Berder

  7. 29 Jul ·  Video

    Developer customers, AI skills, and durable product judgment with Ben Ilegbodu

    If you build internal tools, AI enablement, or platform work, this episode is for you. Kent talks with Ben Ilegbodu about treating developers as customers, measuring success without a checkout funnel, and the durable skills that still matter when agents write more of the code. They cover agentic workflows and skills at Netflix, closing the agent loop for TV UI development, verification and harness engineering, and why deciding what to build beats shipping three times more features. (00:00) - Meet Ben Ilegbodu (01:06) - From React speaking to Netflix AI enablement (02:56) - Training engineers for agentic workflows (04:17) - Skills, context, and insulating teams from churn (08:41) - Product engineering for internal tools (10:06) - How to measure success without a checkout funnel (12:07) - Closing the agent loop for TV UI (18:34) - Durable skills: what to build, specs, verification (23:45) - Harness builders and agent experience (26:33) - Agent-to-agent PR review (28:21) - Intent docs and harness engineering (29:36) - Do users want 3x more features? (32:00) - Retrospective skills that improve the system (36:56) - AI is here to stay (39:11) - Homework: turn repeated prompts into skills Ben Ilegbodu has spent years helping other engineers move faster - first through React education and UI tooling, and now on Netflix's TV UI productivity team focused on AI enablement. In this conversation, he and Kent talk about what product engineering looks like when your customers are other developers, not the people paying for Netflix. A major theme is that internal tooling still needs product judgment. Ben argues the product is what you deliver to developers, and that feedback can be even more direct than consumer product work because your users Slack you when something breaks. Measuring success means observability, usage, and silence that is not always golden. On the AI side, they dig into skills as reusable context for agents, the hard problem of closing agent loops for TV apps that are not web browsers, and why durable skills like deciding what to build, writing specs, and verification will outlast any particular harness. They also talk about agent-to-agent workflows, retrospective skills that improve the system from real usage, and the temptation to turn 3x throughput into 3x feature spam. Ben's homework is practical: notice the prompts and workflows you repeat while developing with an agent, and turn those into skills so you stop retyping the same guidance every session. Homework While you develop with an agent, notice the prompts or workflows you repeat over and over.Turn one of those repeated instructions into a skill (or part of a larger skill) so the agent can reuse it.Run with that skill on your next task and notice what details you can stop retyping every session.Resources Ben IlegboduBen on XBen on GitHubNetflixGuest: Ben Ilegbodu Company: NetflixGitHub: @benmvp𝕏: @benmvpHost: Kent C. Dodds Website: kentcdodds.com𝕏: @kentcdoddsGitHub: @kentcdoddsYouTube: kentcdodds-plusPodcast: epicproduct.engineerSee on Epic Product Engineer

    Developer customers, AI skills, and durable product judgment with Ben Ilegbodu

  8. 22 Jul ·  Video

    Architecture, AI agents, and product empathy with Robert C. Martin

    Kent talks with Robert C. Martin - Uncle Bob - about what AI agents change, what they do not change, and why software architecture, design sense, and customer empathy still matter. They cover why engineers may need to "walk away from the code" while still caring about structure, how agents can be guided with quality tools, why beginners still need to learn the material agents manipulate, and what product engineering looks like when implementation gets cheaper. (00:00) - Meet Robert C. Martin (02:53) - What has changed and what has not (05:41) - The rising abstraction line (08:00) - Walking away from the code (11:15) - Agents and larger systems (14:16) - Clean code when agents write code (20:09) - Design sense and agent judgment (22:36) - Why beginners still need code (34:57) - What product engineering means (41:18) - Homework: try SwarmForge Robert C. Martin has watched software move through layers of abstraction for decades: binary, assembly, high-level languages, frameworks, and now AI agents. In this conversation, he and Kent talk about the next layer up and the durable engineering judgment that still belongs to humans. A major theme is that the low-level work keeps changing while the high-level rules of design and architecture stay remarkably stable. Bob argues that if engineers want the real benefit of agents, they will eventually need to stop treating code as the primary surface and start reviewing module structure, dependencies, data flow, and system behavior. But that does not mean code quality stops mattering. It means humans need better feedback loops, better tools, and enough design sense to know what to ask the agents to improve. They also talk about new engineers, education, and the danger of skipping the code too early. Agents are power tools, and Bob's advice is that engineers still need to understand the material those tools are shaping. The episode lands on product engineering as the marriage of deep technical skill and deep customer understanding: the product engineer lives partly in the technology and partly in the customer's world. Homework Try Robert C. Martin's SwarmForge project locally and follow the setup instructions far enough to run it.Use it to experiment with coordinated agents passing tasks or information to each other.If you find a problem or a useful improvement, leave an issue on the GitHub repo so the product feedback loop closes.Resources Robert C. MartinClean CodersSwarmForgeAgile ManifestoClean CodeGuest: Robert C. Martin Company: Uncle Bob Consulting LLCGitHub: @unclebob𝕏: @unclebobmartinHost: Kent C. Dodds Website: kentcdodds.com𝕏: @kentcdoddsGitHub: @kentcdoddsYouTube: kentcdodds-plusPodcast: epicproduct.engineerSee on Epic Product Engineer

    Architecture, AI agents, and product empathy with Robert C. Martin
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About

Become an Epic Product Engineer is Kent C. Dodds's interview podcast about skills that stay valuable as AI takes on more implementation: product engineering - blending technical depth with product judgment, user empathy, and problem clarity. Each episode is a long-form conversation with a guest who has shipped real software and cares about building the right thing before making it right. You get full audio, transcripts, structured show notes, homework (one concrete action to try), and links from the conversation. Canonical home for the show and every episode page: https://www.epicproduct.engineer/become-an-epic-product-engineer-podcast New episodes publish on Wednesdays (America/Denver). Video is added on Transistor for supported podcast apps when available. Complements Better with Kent - Kent's solo series on durable skills for people who ship software.

Information

  • Creator
    Kent C. Dodds
  • Years Active
    2026
  • Episodes
    27
  • Rating
    Explicit
  • Copyright
    © 2026 Kent C. Dodds Tech LLC. All rights reserved.
  • Show Website
    Become an Epic Product Engineer