The Product Engineers Podcast

Your Hourly Rate Is Broken (Here's What AI Changed) | With Judith Bohlert

If you're freelancing as a software engineer, you've probably noticed something a bit weird: your freelance pricing is now working against you. The faster you go, the less you bill. This episode is a conversation with Judith Bohlert — a freelance software engineer based in Germany, self-employed for 3 years, building greenfield MVPs and prototypes for early-stage startups — about how freelancing with AI tools affects the job, pricing, and the identity of an independent engineer. We get into the case for moving from time-seller to product engineer-consultant, why a productized service or a value-based offer is now the obvious response to AI freelancing economics, and why your personal brand — not your stack — is the only moat left when average code becomes a commodity. TIMESTAMP 0:00 — How AI changed a Monday morning for a freelance dev 4:15 — Tools that actually work: Claude Code, Cursor, GitHub Copilot 5:41 — Repricing your work: hourly vs fixed vs productized vs value-based 17:46 — Use AI to work less, not more: the case for the four-day week 22:04 — Personal brand as the only moat when code is a commodity 35:00 — The freelancer label is dying, the consultant role is rising 38:54 — Advice if you want to start freelancing now GUEST Judith Bohlert is a freelance software engineer based in Germany, with around 3 years of self-employment experience, focused on greenfield MVPs and prototypes for early-stage startups. She writes the low noise newsletter — a calmer take on working in tech, without hustle culture or the productivity-hack treadmill. Website:https://www.judithboehlert.com/ [https://www.judithboehlert.com/] Newsletter (low noise newsletter):https://www.lownoiseclub.com/ [https://www.lownoiseclub.com/] LinkedIn:https://www.linkedin.com/in/jboehlert/ [https://www.linkedin.com/in/jboehlert/] CONNECT WITH PRODUCT ENGINEERS Host: Peppe Silletti LinkedIn:https://www.linkedin.com/in/peppesilletti/ [https://www.linkedin.com/in/peppesilletti/] Peppe's website:https://peppesilletti.io [https://peppesilletti.io] Product Engineers Community:https://discord.gg/4sMtRNSgU4 [https://discord.gg/4sMtRNSgU4] Share this episode with a freelance developer friend who's billing hourly and starting to feel it. To hear more, visit podcast.productengineers.com [https://podcast.productengineers.com?utm_medium=podcast&utm_campaign=show-notes-spotify-open-access]

Meeting Notes That Ship Code | With Earmark founders

If you’re a product engineer, engineering manager or PM, we all know how it goes: you go through tons of meetings every day, and only when they end is when real work starts. PRDs, tickets, specs, follow-ups — all the artefact work nobody sees you do. And by the time you’re done, the next meeting is already starting. One of today’s guests has a name for it: the infinite workday. And that’s exactly the problem today’s guests set out to fix. Mark Barbir and Sanden Gocka are the founders of Earmark — an AI meeting note taker that turns live conversations into shippable work in real time. We get into how they actually use it day to day, how it helps product teams, where the new bottleneck of product work has moved, and what it looks like when an idea you just said out loud turns into a working prototype before the call ends. If you’ve been hunting for AI tools for product managers that go beyond generic summaries, I’m walking you through them, and you can decide if it’s worth trying. GUESTS Mark Barbir and Sanden Gocka are the co-founders of Earmark. They previously worked together at Mindbody, a large enterprise SaaS company with a 400-person delivery organisation, and later crossed paths again at ProductPlan, where Sanden was an engineering manager and director. After years of watching product and engineering leaders drown in meetings and artefact work, they set out to build the tool they wished they had: an AI meeting assistant that generates the artefacts a conversation implies, in real time, while the meeting is still happening. Mark’s LinkedIn: https://www.linkedin.com/in/markbarbir/ [https://www.linkedin.com/in/markbarbir/]Sanden LinkedIn: https://www.linkedin.com/in/sandengocka [https://www.linkedin.com/in/sandengocka] Earmark: https://www.tryearmark.com TIMESTAMPS 00:00 The Invisible Second Shift: PM Meetings Problem 01:49 The Infinite Workday: Why PMs Work After Hours 07:49 Vision Pro Pivot: From Presentation Coach to Meeting AI 11:35 Why Vision Pro Failed (and What They Learned) 14:13 Engineering Translator Card: Understanding Technical Talk 16:00 Specs, PRDs & Code in Real-Time During Meetings 19:00 Make Me Look Smart: AI for Shy PMs 28:32 PMs Are Now The New Bottleneck 31:56 Dog Food Success: How Earmark Built Earmark 40:09 How to Get Started with Earmark REFERENCES Cursor: https://cursor.com Linear: https://linear.app MacWhisper — the local speech-to-text tool Sanden used in his early hacked workflow AssemblyAI (referenced in the co-marketing case study story): https://www.assemblyai.com CONNECT WITH PRODUCT ENGINEERS Host: Peppe Silletti LinkedIn: https://www.linkedin.com/in/peppesilletti/ [https://www.linkedin.com/in/peppesilletti/] Product Engineers: Website: https://productengineers.com Discord Channel: https://discord.gg/4sMtRNSgU4 [https://discord.gg/4sMtRNSgU4] Share this episode with a teammate who is still writing their PRDs at 10pm. To hear more, visit podcast.productengineers.com [https://podcast.productengineers.com?utm_medium=podcast&utm_campaign=show-notes-spotify-open-access]

The Agile Dream Finally Came True | AI Made It Happen

AI is reshaping product development and the future of work for every role in the tech industry. Every product team used to work the same way: slow discovery, designers as bottlenecks, agile scrum ceremonies that meant nothing because the rest of the company was still doing waterfall, and a measurement phase everyone skipped. The result was feature factories everywhere. In this episode, I break down what product development looked like before AI and what it looks like now — based on my own experience and conversations with founders and engineers building AI-native companies. --- TIMESTAMPS 00:00 How Product Development Worked Before AI 01:06 Discovery: Slow Data, Slow Analysis 02:17 Design: Always a Bottleneck 03:43 Delivery: Scrum in a Waterfall Company 06:36 Measurement: The Phase Everyone Skipped 07:00 The Feature Factory Problem 07:43 How AI Changed Discovery 09:06 The New PM: Full-Stack Product Builders 12:00 How AI Changed Design: Three Approaches 15:44 How AI Changed Delivery: Four Levels of AI Collaboration 20:00 Tools: Cursor, Claude Code, Codex, Superpowers, nWave 22:22 How AI Changed Measurement 24:16 AI-Native Startups Are Finally Agile 25:37 Daily Sprints and Same-Day Feedback (Andsend) 26:39 The Convergence of Product and Engineering Roles 28:39 What This Means for Your Career --- RESOURCES MENTIONED - PostHog — product analytics platform with AI-powered insights - Andsend — AI-native startup with daily sprints - Cursor — AI-powered IDE - Claude Code — AI coding agent by Anthropic - Codex — AI coding agent by OpenAI - Superpowers — AI agent framework for software development - nWave — multi-agent framework for the full product development lifecycle - Lovable, V0, Bolt, Stitch, Replit — AI prototyping tools - Figma MCP — integration between AI agents and Figma - MCP Protocol — Model Context Protocol for tool integration --- CONNECT WITH PRODUCT ENGINEERS Host: Peppe Silletti LinkedIn: https://www.linkedin.com/in/peppesilletti/ [https://www.linkedin.com/in/peppesilletti/] Website: https://peppesilletti.io [https://peppesilletti.io] Product Engineers Website: https://productengineers.com [https://productengineers.com] Newsletter: https://newsletter.productengineers.com [https://newsletter.productengineers.com] Community: https://discord.gg/4sMtRNSgU4 [https://discord.gg/4sMtRNSgU4] --- SUPPORT THE SHOW If you've seen AI change how your team builds products — or you're still stuck in the old way — share this episode with your team. Drop a comment with what phase AI impacted most for you: discovery, design, delivery, or measurement. To hear more, visit podcast.productengineers.com [https://podcast.productengineers.com?utm_medium=podcast&utm_campaign=show-notes-spotify-open-access]

60+ Years of Engineering Built Into One AI Framework

AI software development is changing software engineering forever, but most AI tools produce code that drifts, hallucinates, and needs constant rework. What if test-driven development, refactoring, and product engineering discipline could be baked into every AI-generated line of code? Michele Brissoni, Alessandro Di Gioia, and Marco Consolaro have a combined 60+ years of experience — from Ferrari Formula One to Fortune 500 DevOps transformations to writing the award-winning book on TDD. They built nWave to answer that question. --- GUESTS Michele Brissoni - Founder of BrickX Consulting, Fractional CTO, Host of Forge of Unicorns Podcast Michele has 20+ years in software engineering, starting with behavioural engineering at Ferrari F1 during the Schumacher era. He invented the Software Craftsmanship Dojo, led a DevOps transformation at IBM across 15,000 people, and has hosted 80+ episodes interviewing the people behind 52 unicorn companies. Alessandro Di Gioia - Software Craftsman, Technical Coach, Co-founder of Alcor Academy Alessandro co-authored "Agile Technical Practices Distilled" with Marco and Pedro Santos, a multi-award-winning book on TDD, refactoring, and software design. He's been teaching outside-in development at conferences like NDC, DDD Europe, and DevOps Days for years. He's the primary builder behind nWave's deterministic execution system. Marco Consolaro - Software Craftsman, Technical Coach, Co-founder of Alcor Academy Marco co-authored "Agile Technical Practices Distilled" and has spent years teaching software craftsmanship and TDD. He brings a focus on the human side of engineering — sustainable pace, team dynamics, and the importance of trust in building quality software. Find them: - nWave GitHub: https://github.com/nWave-ai [https://github.com/nWave-ai] - Michele's LinkedIn: https://www.linkedin.com/in/michelebrissoni [https://www.linkedin.com/in/michelebrissoni] - Alessandro's LinkedIn: https://www.linkedin.com/in/alessandro-di-gioia/ [https://www.linkedin.com/in/alessandro-di-gioia/] - Marco's LinkedIn: https://www.linkedin.com/in/consolaro/ [https://www.linkedin.com/in/consolaro/] --- TIMESTAMPS 00:00 Introduction and Guest Welcome 03:00 The Origin Story: From Early AI Tools to nWave 08:03 The Career Lesson Behind nWave 10:17 Discuss nWave: Understanding What to Build and For Whom 26:16 Design nWave: Architecture with Adversarial Reviews 38:41 DevOps and Distill nWaves: CI/CD and Acceptance Tests Before Code 41:42 Deliver nWave: Outside-In TDD with Fresh Context Every Step 52:51 "Doesn't This Make You Slower?" — The Rework Argument 01:02:25 What Do You Do While nWave Is Working? 01:05:34 Closing and How to Contribute --- RESOURCES MENTIONED Link with all research material used to build nWave: https://drive.google.com/file/d/1yvSDNwj-F1amEavoX3Qz4oRZfw-9XKF9/view [https://drive.google.com/file/d/1yvSDNwj-F1amEavoX3Qz4oRZfw-9XKF9/view] --- CONNECT WITH PRODUCT ENGINEERS Host: Peppe Silletti LinkedIn: https://www.linkedin.com/in/peppesilletti/ [https://www.linkedin.com/in/peppesilletti/] Product Engineers Community: Website: https://productengineers.com [https://productengineers.com] Discord Channel: https://discord.gg/4sMtRNSgU4 [https://discord.gg/4sMtRNSgU4] --- SUPPORT THE SHOW If this episode changed how you think about AI-assisted development, share it with an engineer or team lead who's struggling with AI code quality. Drop a comment below with your biggest takeaway. To hear more, visit podcast.productengineers.com [https://podcast.productengineers.com?utm_medium=podcast&utm_campaign=show-notes-spotify-open-access]

Thinking in Product Outcomes | The Shift Every Engineer Needs to Make

You shipped the feature, closed the ticket, merged the PR — but do you have any idea if it actually mattered? If you want to know how to be a better product engineer, this episode is for you. In this episode, I explain why business outcomes are lagging indicators you can't directly control, while product outcomes are leading indicators tied to user behaviour that your team can actually influence. I walk through the Cynefin Framework, how to test if a product outcome is any good, what a feature factory looks like, and practical things you can start doing right now to speak the language of outcomes. TIMESTAMPS 00:00 Why Engineers Never See the Feedback Loop 03:00 Business Outcomes vs Product Outcomes — The Definitions 07:00 Why Product Development Lives in the Complex Domain (Cynefin Framework) 09:00 How Business Outcomes Get Translated into Product Outcomes 12:00 The Four Tests of a Good Product Outcome 15:00 From Features to Experiments — Redefining “Done” 18:00 The Feature Factory and Vanity Metrics 21:00 What You Can Do as an Engineer Right Now 25:00 The One Question That Separates Product Engineers from Software Engineers RESOURCES MENTIONED * Cynefin Framework by Dave Snowden CONNECT WITH PRODUCT ENGINEERS Host: Peppe SillettiLinkedIn: https://www.linkedin.com/in/peppesilletti/ [https://www.linkedin.com/in/peppesilletti/]Website: https://peppesilletti.io Product Engineers Community:Website: https://productengineers.comLinkedIn: https://www.linkedin.com/company/product-engineers [https://www.linkedin.com/company/product-engineers] SUPPORT THE SHOW If you’re an engineer who’s tired of just closing tickets without knowing if any of it mattered — share this episode with your team. Drop a comment with your biggest takeaway. To hear more, visit podcast.productengineers.com [https://podcast.productengineers.com?utm_medium=podcast&utm_campaign=show-notes-spotify-open-access]