Discover how to transition from legacy, siloed systems to a unified, scalable, and insights-driven data platform on GCP. This session will cover best practices for data migration, overcoming common challenges, and integrating SaaS and third-party solutions using key Google Cloud services like BigQuery, Data Fusion, Cloud Storage, Application Integration, Cloud Run, Cloud Build, and Artifact Registry.

This Session is hosted by a Google Cloud Next Sponsor.
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This session provides a Google thought-leadership perspective on the importance of product-led growth for all organizations and how it can complement and accelerate sales-driven strategies. We’ll explain how we’ve scaled software-as-a-service (SaaS) product-led growth principles to Google Cloud, and we’ll illustrate how Google Cloud can be the ideal partner for creating, analyzing, and optimizing product-led growth efforts to drive incremental revenue without increasing sales head count.

Is your business ready to embrace the software as a service (SaaS) revolution? Discover how Google Cloud can fast-track your SaaS journey. This session reveals how Google Cloud empowers you to scale your SaaS offerings, reduce time to market, and deliver exceptional customer experiences using a comprehensive toolbox with per-tenant controls, feature rollout management, and insightful monitoring. You’ll also learn from Avathon’s success story: how they leveraged these capabilities to conquer the complexities of SaaS management, automate tenant onboarding, and centralize operations.

Tired of building the same old software as a service (SaaS) features? AI and data agents are revolutionizing the SaaS landscape, and developers are at the forefront of this exciting shift. Imagine building applications that can autonomously learn, adapt, and execute complex tasks, all while providing a personalized user experience. This session equips you with the knowledge and tools to build the next generation of intelligent SaaS applications. Learn how leading companies are leveraging AI agents to automate workflows, personalize user interactions, and boost operational efficiency. Discover the latest trends in agent development, best practices for building agent-first applications, and the secrets to successful implementation. And leave with practical insights and a clear roadmap for harnessing the power of agentic AI to create truly innovative SaaS products.

A best-in-class collaboration suite, Google Workspace provides a platform that allows your employees to work across your tech stack to do their best work. Join this session to learn best practices from customers and get inspiration on fostering a culture of innovation and positioning your organization for growth.

The explosion of content in market research has created a paradox - more information but less time to consume it. Companies are now turning to AI chatbots to solve this problem, transforming how professionals interact with research data. Instead of expecting teams to read everything, these tools allow users to extract precisely what they need when they need it. This approach is proving not just more efficient but actually increases engagement with underlying content. How might your organization benefit from more targeted access to insights? What valuable information might be buried in your existing research that AI could help surface? With over 30 years of experience in marketing, media, and technology, Dan Coates is the President and co-founder of YPulse, the leading authority on Gen Z and Millennials. YPulse helps brands like Apple, Netflix, and Xbox understand and communicate with consumers aged 13–39, using data and insights from over 400,000 interviews conducted annually across seven countries. Prior to founding YPulse, Dan co-founded SurveyU, an online community and insights platform targeting youth, which merged with YPulse in 2009. He also led the introduction of Globalpark’s SAAS platform into the North American market, until its acquisition by QuestBack in 2011. In addition, Dan has held senior roles at Polimetrix, SPSS, PlanetFeedback, and Burke, where he developed cutting-edge practices and products for online marketing insights and transitioned several ventures from early stages to high-value acquisitions. In the episode, Richie and Dan explore the creation of an AI chatbot for market research, addressing customer engagement challenges, the integration of AI in content consumption, the impact of AI on business strategies, and the future of AI in market research, and much more. Links Mentioned in the Show: YPulseConnect with DanHaystack by DeepsetUnmanaged: Master the Magic of Creating Empowered and Happy Organizations by Jack SkeelsSkill Track: AI FundamentalsRelated Episode: Can You Use AI-Driven Pricing Ethically? with Jose Mendoza, Academic Director & Clinical Associate Professor at NYURewatch sessions from RADAR: Skills Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Supported by Our Partners • WorkOS — The modern identity platform for B2B SaaS. • Vanta — Automate compliance and simplify security with Vanta. — Linux is the most widespread operating system, globally – but how is it built? Few people are better to answer this than Greg Kroah-Hartman: a Linux kernel maintainer for 25 years, and one of the 3 Linux Kernel Foundation Fellows (the other two are Linus Torvalds and Shuah Khan). Greg manages the Linux kernel’s stable releases, and is a maintainer of multiple kernel subsystems. We cover the inner workings of Linux kernel development, exploring everything from how changes get implemented to why its community-driven approach produces such reliable software. Greg shares insights about the kernel's unique trust model and makes a case for why engineers should contribute to open-source projects. We go into: • How widespread is Linux? • What is the Linux kernel responsible for – and why is it a monolith? • How does a kernel change get merged? A walkthrough • The 9-week development cycle for the Linux kernel • Testing the Linux kernel • Why is Linux so widespread? • The career benefits of open-source contribution • And much more! — Timestamps (00:00) Intro (02:23) How widespread is Linux? (06:00) The difference in complexity in different devices powered by Linux  (09:20) What is the Linux kernel? (14:00) Why trust is so important with the Linux kernel development (16:02) A walk-through of a kernel change (23:20) How Linux kernel development cycles work (29:55) The testing process at Kernel and Kernel CI  (31:55) A case for the open source development process (35:44) Linux kernel branches: Stable vs. development (38:32) Challenges of maintaining older Linux code  (40:30) How Linux handles bug fixes (44:40) The range of work Linux kernel engineers do  (48:33) Greg’s review process and its parallels with Uber’s RFC process (51:48) Linux kernel within companies like IBM (53:52) Why Linux is so widespread  (56:50) How Linux Kernel Institute runs without product managers  (1:02:01) The pros and cons of using Rust in Linux kernel  (1:09:55) How LLMs are utilized in bug fixes and coding in Linux  (1:12:13) The value of contributing to the Linux kernel or any open-source project  (1:16:40) Rapid fire round — The Pragmatic Engineer deepdives relevant for this episode: What TPMs do and what software engineers can learn from them The past and future of modern backend practices Backstage: an open-source developer portal — See the transcript and other references from the episode at ⁠⁠https://newsletter.pragmaticengineer.com/podcast⁠⁠ — Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected].

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Today, we’re joined by Rahul Pangam, Co-Founder & CEO of RapidCanvas, a leader in delivering transformative AI-powered solutions that empower businesses to achieve faster and more impactful outcomes. We talk about: How to make GenAI more reliable: Understanding your business context & knowing why something is happeningMoving from planning based on the human gut to an AI-based setupThe coming paradigm shift from SaaS to service as a softwareInteracting with apps in plain language vs. remembering which of 56 dashboards to view

The integration of speech AI into everyday business operations is reshaping how we communicate and process information. With applications ranging from customer service to quality control, understanding the nuances of speech AI is crucial for professionals. How do you tackle the complexities of different languages and accents? What are the best practices for implementing speech AI in your organization? Explore the transformative power of speech AI and learn how to overcome the challenges it presents in your professional landscape. Alon Peleg serves as the Chief Operating Officer (COO) at aiOla, a position he assumed in May 2024. With over two decades of leadership experience at renowned companies like Wix, Cisco, and Intel, he is widely recognized in the tech industry for his expertise, dynamic leadership, and unwavering dedication. At aiOla, Alon plays a key role in driving innovation and strategic growth, contributing to the company’s mission of developing cutting-edge solutions in the tech space. His appointment is regarded as a pivotal step in aiOla’s expansion and continued success. Gill Hetz is the VP of AI at aiOla where he leverages his expertise in data integration and modeling. Gill was previously active in the oil and gas industry since 2009, holding roles in engineering, research, and data science. From 2018 to 2021, Gill held key positions at QRI, including Project Manager and SaaS Product Manager. In the episode, Richie, Alon, and Gill explore the intricacies of speech AI, its components like ASR, NLU, and TTS, real-world applications in industries such as retail and pharmaceuticals, challenges like accents and background noise, and the future of voice interfaces in technology, and much more. Links Mentioned in the Show: aiOlaConnect with Alon and GillCourse: Spoken Language Processing in PythonRelated Episode: Building Multi-Modal AI Applications with Russ d'Sa, CEO & Co-founder of LiveKitSign up to attend RADAR: Skills Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

The rise of A-B testing has transformed decision-making in tech, yet its application isn't without challenges. As professionals, how do you navigate the balance between short-term gains and long-term sustainability? What strategies can you employ to ensure your testing methods enhance rather than hinder user experience? And how do you effectively communicate the insights gained from testing to drive meaningful change within your organization? Vanessa Larco is a former partner at NEA where she led Series A and Series B investment rounds and worked with major consumer companies like DTC jewelry giant Mejuri, menopause symptom relief treatment Evernow, and home-swapping platform Kindred as well as major enterprise SaaS companies like Assembled, Orby AI, Granica AI, EvidentID, Rocket.Chat, Forethought AI. She is also a board observer at Forethought, SafeBase, Orby AI, Granica, Modyfi, and HEAVY.AI. She was a board observer at Robinhood until its IPO in 2021. Before she became an investor, she built consumer and enterprise tech herself at Microsoft, Disney, Twilio, and Box as a product leader. In the episode, Richie and Vanessa explore the evolution of A-B testing in gaming, the balance between data-driven decisions and user experience, the challenges of scaling experimentation, the pitfalls of misaligned metrics, the importance of understanding user behavior, and much more. Links Mentioned in the Show: New Enterprise AssociatesConnect with VanessaCourse: Customer Analytics and A/B Testing in PythonRelated Episode: Make Your A/B Testing More Effective and EfficientSign up to attend RADAR: Skills Edition - Vanessa will be speaking! New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Supported by Our Partners • WorkOS — The modern identity platform for B2B SaaS. • The Software Engineer’s Guidebook: Written by me (Gergely) – now out in audio form as well • Augment Code — AI coding assistant that pro engineering teams love — Not many people know that I have a brother: Balint Orosz. Balint is also in tech, but in many ways, is the opposite of me. While I prefer working on backend and business logic, he always thrived in designing and building UIs. While I opted to work at more established companies, he struck out on his own and started his startup, Distinction. And yet, our professional paths have crossed several times: at one point in time I accepted an offer to join Skyscanner as a Principal iOS Engineer – and as part of the negotiation, I added a clause to my contrac that I will not report directly or indirectly to the Head of Mobile: who happened to be my brother, thanks to Skyscanner acquiring his startup the same month that Skyscanner made an offer to hire me. Today, Balint is the founder and CEO of Craft, a beloved text editor known for its user-friendly interface and sleek design – an app that Apple awarded the prestigious Mac App of the Year in 2021. In our conversation, we explore how Balint approaches building opinionated software with an intense focus on user experience. We discuss the lessons he learned from his time building Distinction and working at Skyscanner that have shaped his approach to Craft and its development. In this episode, we discuss: • Balint’s first startup, Distinction, and his time working for Skyscanner after they acquired it • A case for a balanced engineering culture with both backend and frontend priorities  • Why Balint doesn’t use iOS Auto Layout • The impact of Craft being personal software on front-end and back-end development • The balance between customization and engineering fear in frontend work • The resurgence of local-first software and its role in modern computing • The value of building a physical prototype  • How Balint uses GenAI to assist with complicated coding projects  • And much more! — Timestamps (00:00) Intro (02:13) What it’s like being a UX-focused founder  (09:00) Why it was hard to gain recognition at Skyscanner  (13:12) Takeaways from Skyscanner that Balint brought to Craft  (16:50) How frameworks work and why they aren’t always a good fit (20:35) An explanation of iOS Auto Layout and its pros and cons  (23:13) Why Balint doesn’t use Auto Layout  (24:23) Why Craft has one code base  (27:46) Craft’s unique toolbar features and a behind the scenes peek at the code  (33:15) Why frontend engineers have fear around customization  (37:11) How Craft’s design system differs from most companies  (42:33) Behaviors and elements Craft uses rather than having a system for everything  (44:12) The back and frontend architecture in building personal software  (48:11) Shifting beliefs in personal computing  (50:15) The challenges faced with operating system updates  (50:48) The resurgence of local-first software (52:31) The value of opinionated software for consumers  (55:30) Why Craft’s focus is on the user’s emotional experience (56:50) The size of Craft’s engineering department and platform teams (59:20) Why Craft moves faster with smaller teams (1:01:26) Balint’s advice for frontend engineers looking to demonstrate value  (1:04:35) Balint’s breakthroughs using GenAI (1:07:50) Why Balint still writes code (1:09:44) Rapid fire round — The Pragmatic Engineer deepdives relevant for this episode: • The AI hackathon at Craft Docs • Engineering career paths at Big Tech and scaleups • Thriving as a Founding Engineer: lessons from the trenches • The past and future of modern backend practices — See the transcript and other references from the episode at ⁠⁠https://newsletter.pragmaticengineer.com/podcast⁠⁠ — Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected].

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Today, we’re joined by Srikrishnan Ganesan, Co-Founder & CEO of Rocketlane, the #1 customer onboarding, PSA, and project delivery software. We talk about:  Launching an incomplete product vs. going to market too late Determining the scope of an MVP & a full-featured, differentiated productUnique approaches to “Design Partners” during product development Best ways to build a communityMaintaining a sense of urgency once established & not getting too comfortable

Supported by Our Partners • WorkOS — The modern identity platform for B2B SaaS. • Graphite — The AI developer productivity platform.  • Formation — Level up your career and compensation with Formation. — In today’s episode of The Pragmatic Engineer, I am joined by a senior software engineer and cartoonist, Manu Cornet. Manu spent over a decade at Google, doing both backend and frontend development. He also spent a year and a half at Twitter before Elon Musk purchased it and rebranded it to X. But what Manu is most known for are his hilarious internet comics about the tech world, including his famous org chart comic from 2011 about Facebook, Apple, Amazon, and Microsoft. In today’s conversation, we explore many of his comics, discuss the meaning behind them, and talk about the following topics:  • The viral org chart comic that captured the structure of Big Tech companies • Why Google is notorious for confusing product names • The comic that ended up on every door at Google • How Google’s 20% time fostered innovation—and what projects came from it • How one of Manu’s comics predicted Google Stadia’s failure—and the reasons behind it • The value of connecting to users directly  • Twitter’s climate before and after Elon Musk’s acquisition and the mass layoffs that followed • And more! — Timestamps (00:00) Intro (02:01) Manu’s org structure comic  (07:10) Manu’s “Who Sues Who” comic (09:15) Google vs. Amazon comic (14:10) Confusing names at Google (20:00) Different approaches to sharing information within companies (22:20) The two ways of doing things at Google (25:15) Manu’s code reviews comic (27:45) The comic that was printed on every single door of Google (30:55) An explanation of 20% at Google (36:00) Gmail Labs and Google Stadia (41:36) Manu’s time at Twitter and the threat of Elon Musk buying (47:07) How Manu helped Gergely with a bug on Twitter (49:05) Musk’s acquirement of Twitter and the resulting layoffs (59:00) Manu’s comic about his disillusionment with Twitter and Google (1:02:37) Rapid fire round — The Pragmatic Engineer deepdives relevant for this episode: • How Manu creates comics • Consolidating technologies • Is Big Tech becoming more cutthroat? — See the transcript and other references from the episode at ⁠⁠https://newsletter.pragmaticengineer.com/podcast⁠⁠ — Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected].

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S1 Ep#33 Bridging Business and Data: The Art of Data Product Management The Data Product Management In Action podcast, brought to you by executive producer Scott Hirleman, is a platform for data product management practitioners to share insights and experiences. 

In Season 01, Episode 33, Amritha, our newest host, chats with Sagar Nikam, Head of Product at CK Delta. Sagar shares his journey from finance to data product management, highlighting the art of translating complex AI/ML models into actionable business strategies. He discusses the challenges of defining data products, the importance of clear communication, and why adoption often outweighs accuracy. Sagar also offers insights on handling uncertainty, setting success metrics, and the cross-industry applicability of data product management skills. Tune in for a deep dive into making data-driven decisions that drive real business impact.

About our host Amritha Arun Babu: Amritha is an accomplished Product Leader with over a decade of experience building and scaling products across AI platforms, supply chain systems, and enterprise workflows in industries such as e-commerce, AI/ML, and marketing automation. At Amazon, she led machine learning platform products powering recommendation and personalization engines, building tools for model experimentation, deployment, and monitoring that improved efficiency for 1,500+ ML scientists. At Wayfair, she managed international supply chain systems, overseeing contracts, billing, product catalogs, and vendor operations, delivering cost savings and optimizing large-scale workflows. At Klaviyo, she drives both AI infrastructure and customer-facing AI tools, including recommendation engines, content generation assistants, and workflow automation agents, enabling scalable and personalized marketing workflows. Earlier, she worked on enterprise systems and revenue operations workflows, focusing on cost optimization and process improvements in complex technical environments. Amritha excels at bridging technical depth with strategic clarity, leading cross-functional teams, and delivering measurable business outcomes across diverse domains. Connect with Amritha on LinkedIn.
About our guest Sagar Nikam: Sagar is the Head of Products at CKDelta, leading the development of AI-driven solutions, AI Agents, and intelligent applications that enhance decision-making and automation across industries. With experience in banking, utilities, and SaaS, he has successfully launched and scaled AI-powered products that drive real business impact. Sagar helps product teams seamlessly integrate AI, navigate challenges, and build solutions that are user-centric, explainable, and trusted. Connect with Sagar on LinkedIn.  

All views and opinions expressed are those of the individuals and do not necessarily reflect their employers or anyone else. 

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Apply to be a guest or nominate someone that you know. 

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Supported by Our Partners • WorkOS — The modern identity platform for B2B SaaS • CodeRabbit — Cut code review time and bugs in half • Augment Code — AI coding assistant that pro engineering teams love — How do you architect a live streaming system to deal with more load than it’s ever been done before? Today, we hear from an architect of such a system: Ashutosh Agrawal, formerly Chief Architect of JioCinema (and currently Staff Software Engineer at Google DeepMind.) We take a deep dive into video streaming architecture, tackling the complexities of live streaming at scale (at tens of millions of parallel streams) and the challenges engineers face in delivering seamless experiences. We talk about the following topics:  • How large-scale live streaming architectures are designed • Tradeoffs in optimizing performance • Early warning signs of streaming failures and how to detect them • Why capacity planning for streaming is SO difficult • The technical hurdles of streaming in APAC regions • Why Ashutosh hates APMs (Application Performance Management systems) • Ashutosh’s advice for those looking to improve their systems design expertise • And much more! — Timestamps (00:00) Intro (01:28) The world record-breaking live stream and how support works with live events (05:57) An overview of streaming architecture (21:48) The differences between internet streaming and traditional television.l (22:26) How adaptive bitrate streaming works (25:30) How throttling works on the mobile tower side  (27:46) Leading indicators of streaming problems and the data visualization needed (31:03) How metrics are set  (33:38) Best practices for capacity planning  (35:50) Which resources are planned for in capacity planning  (37:10) How streaming services plan for future live events with vendors (41:01) APAC specific challenges (44:48) Horizontal scaling vs. vertical scaling  (46:10) Why auto-scaling doesn’t work (47:30) Concurrency: the golden metric to scale against (48:17) User journeys that cause problems  (49:59) Recommendations for learning more about video streaming  (51:11) How Ashutosh learned on the job (55:21) Advice for engineers who would like to get better at systems (1:00:10) Rapid fire round — The Pragmatic Engineer deepdives relevant for this episode: • Software architect archetypes https://newsletter.pragmaticengineer.com/p/software-architect-archetypes  • Engineering leadership skill set overlaps https://newsletter.pragmaticengineer.com/p/engineering-leadership-skillset-overlaps  • Software architecture with Grady Booch https://newsletter.pragmaticengineer.com/p/software-architecture-with-grady-booch — See the transcript and other references from the episode at ⁠⁠https://newsletter.pragmaticengineer.com/podcast⁠⁠ — Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected].

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Supported by Our Partners • WorkOS — The modern identity platform for B2B SaaS • CodeRabbit — Cut code review time and bugs in half • Augment Code — AI coding assistant that pro engineering teams love — How do you architect a live streaming system to deal with more load than it’s ever been done before? Today, we hear from an architect of such a system: Ashutosh Agrawal, formerly Chief Architect of JioCinema (and currently Staff Software Engineer at Google DeepMind.) We take a deep dive into video streaming architecture, tackling the complexities of live streaming at scale (at tens of millions of parallel streams) and the challenges engineers face in delivering seamless experiences. We talk about the following topics:  • How large-scale live streaming architectures are designed • Tradeoffs in optimizing performance • Early warning signs of streaming failures and how to detect them • Why capacity planning for streaming is SO difficult • The technical hurdles of streaming in APAC regions • Why Ashutosh hates APMs (Application Performance Management systems) • Ashutosh’s advice for those looking to improve their systems design expertise • And much more! — Timestamps (00:00) Intro (01:28) The world record-breaking live stream and how support works with live events (05:57) An overview of streaming architecture (21:48) The differences between internet streaming and traditional television.l (22:26) How adaptive bitrate streaming works (25:30) How throttling works on the mobile tower side  (27:46) Leading indicators of streaming problems and the data visualization needed (31:03) How metrics are set  (33:38) Best practices for capacity planning  (35:50) Which resources are planned for in capacity planning  (37:10) How streaming services plan for future live events with vendors (41:01) APAC specific challenges (44:48) Horizontal scaling vs. vertical scaling  (46:10) Why auto-scaling doesn’t work (47:30) Concurrency: the golden metric to scale against (48:17) User journeys that cause problems  (49:59) Recommendations for learning more about video streaming  (51:11) How Ashutosh learned on the job (55:21) Advice for engineers who would like to get better at systems (1:00:10) Rapid fire round — The Pragmatic Engineer deepdives relevant for this episode: • Software architect archetypes https://newsletter.pragmaticengineer.com/p/software-architect-archetypes  • Engineering leadership skill set overlaps https://newsletter.pragmaticengineer.com/p/engineering-leadership-skillset-overlaps  • Software architecture with Grady Booch https://newsletter.pragmaticengineer.com/p/software-architecture-with-grady-booch — See the transcript and other references from the episode at ⁠⁠https://newsletter.pragmaticengineer.com/podcast⁠⁠ — Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected].

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Today, we’re joined by Luis Garcia, President of PETE, an Orlando-based tech startup that offers a suite of cost-effective and customizable solutions that enable organizations to deliver personalized workforce learning at scale. We talk about:

Tackling the challenges of digital learning: content development & learning assessmentThe role of AI in scaling workforce development & engaging learners one-on-oneCalculating the ROI of a learning management systemFlipping the normal training paradigm of fixed time with variable learningTraining topics that SaaS companies are most interested in

With the proliferation of SaaS ELT tools many organizations don't realize that Google BigQuery offers many ways to ingest data from different platforms for free. This presentation will walk through the most important native export and data transfer mechanisms and will show how data from these platforms can be integrated to enable a comprehensive view on digital marketing efforts for an organization. Various use cases will be presented as well to generate tangible insights from this integrated data that help increase the bottom line.

Supported by Our Partners • Formation — Level up your career and compensation with Formation.  • WorkOS — The modern identity platform for B2B SaaS • Vanta — Automate compliance and simplify security with Vanta. — In today’s episode of The Pragmatic Engineer, I’m joined by Jonas Tyroller, one of the developers behind Thronefall, a minimalist indie strategy game that blends tower defense and kingdom-building, now available on Steam. Jonas takes us through the journey of creating Thronefall from start to finish, offering insights into the world of indie game development. We explore: • Why indie developers often skip traditional testing and how they find bugs • The developer workflow using Unity, C# and Blender • The two types of prototypes game developers build  • Why Jonas spent months building game prototypes in 1-2 days • How Jonas uses ChatGPT to build games • Jonas’s tips on making games that sell • And more! — Timestamps (00:00) Intro (02:07) Building in Unity (04:05) What the shader tool is used for  (08:44) How a Unity build is structured (11:01) How game developers write and debug code  (16:21) Jonas’s Unity workflow (18:13) Importing assets from Blender (21:06) The size of Thronefall and how it can be so small (24:04) Jonas’s thoughts on code review (26:42) Why practices like code review and source control might not be relevant for all contexts (30:40) How Jonas and Paul ensure the game is fun  (32:25) How Jonas and Paul used beta testing feedback to improve their game (35:14) The mini-games in Thronefall and why they are so difficult (38:14) The struggle to find the right level of difficulty for the game (41:43) Porting to Nintendo Switch (45:11) The prototypes Jonas and Paul made to get to Thronefall (46:59) The challenge of finding something you want to build that will sell (47:20) Jonas’s ideation process and how they figure out what to build  (49:35) How Thronefall evolved from a mini-game prototype (51:50) How long you spend on prototyping  (52:30) A lesson in failing fast (53:50) The gameplay prototype vs. the art prototype (55:53) How Jonas and Paul distribute work  (57:35) Next steps after having the play prototype and art prototype (59:36) How a launch on Steam works  (1:01:18) Why pathfinding was the most challenging part of building Thronefall (1:08:40) Gen AI tools for building indie games  (1:09:50) How Jonas uses ChatGPT for editing code and as a translator  (1:13:25) The pros and cons of being an indie developer  (1:15:32) Jonas’s advice for software engineers looking to get into indie game development (1:19:32) What to look for in a game design school (1:22:46) How luck figures into success and Jonas’s tips for building a game that sells (1:26:32) Rapid fire round — The Pragmatic Engineer deepdives relevant for this episode: • Game development basics https://newsletter.pragmaticengineer.com/p/game-development-basics  • Building a simple game using Unity https://newsletter.pragmaticengineer.com/p/building-a-simple-game — See the transcript and other references from the episode at ⁠⁠https://newsletter.pragmaticengineer.com/podcast⁠⁠ — Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected].

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Season 1 Episode 29: Navigating Trade-Offs and Balancing Priorities The Data Product Management In Action podcast, brought to you by executive producer Scott Hirleman, is a platform for data product management practitioners to share insights and experiences. In this episode of Data Product Management in Action, host Alexa Westlake talks with Anita Chen, diving into the complexities of managing data products. Anita, a product manager at PagerDuty, shares her approach to defining data products, prioritizing work, and balancing project work with interrupt-driven tasks. They discuss the critical roles of governance, security, and user enablement while emphasizing the importance of transparency and communication. The conversation also explores the transformative potential of generative AI in data product interactions and the build-vs-buy decision-making process. Gain insights into how data product management uniquely differs from traditional software product management and learn actionable strategies for success. Meet our Host Alexa Westlake: Alexa is a Data Analytics Leader in the Identity and Access Management space with a proven track record scaling high-growth SaaS companies. As a Staff Data Analyst at Okta, she brings a wealth of expertise in enterprise data, business intelligence, and strategic decision-making from the various industries she's worked in including telecommunications, strategy execution, and cloud computing. With a passion for harnessing the power of data for actionable insights, Alexa plays a crucial role in driving Okta's security, growth, and scale, helping the organization leverage data to execute on their market opportunity. Connect with Alexa on LinkedIn.

Meet our guest Anita Chen:  Anita is a Data Product Manager at PagerDuty, a digital operations company helping teams resolve issues faster, eliminate alert fatigue, and build more reliable services! Her background is mainly in the People Analytics space which has now expanded to data at scale with our Enterprise Data Team. She currently helps build data products that enable our teams to deliver the best possible customer experience. Anita is most passionate about how data can impact someone's lived experience and endeavor to democratize data in everything she builds. Connect with Anita on LinkedIn. All views and opinions expressed are those of the individuals and do not necessarily reflect their employers or anyone else.  Join the conversation on LinkedIn.  Apply to be a guest or nominate someone that you know.  Do you love what you're listening to? Please rate and review the podcast, and share it with fellow practitioners you know. Your support helps us reach more listeners and continue providing valuable insights!