Episode Summary: In this episode, Mukundan simplifies the concept of Dynamic Topic Modeling (DTM) for listeners and discusses its transformative impact on businesses. DTM is a machine learning method used to track the evolution of themes in text data over time. It helps companies to make smarter decisions by staying in tune with customer needs and market trends. Key Topics Covered: Introduction to Dynamic Topic ModelingWhat it is and why it matters for businesses.Real-world examples like customer reviews and social media trends.How Dynamic Topic Modeling WorksOver time, analyze text data (e.g., reviews, surveys, reports).Groups words into topics such as price, quality, or features.Applications of Dynamic Topic ModelingAdjusting marketing strategies to customer priorities.Enhancing product features based on evolving feedback.Predicting and responding to trends like sustainability in physical products.Tracking employee feedback to refine HR strategies and reduce churn.Step-by-Step Guide to Implementing DTMCollecting text data (e.g., reviews, surveys).Using tools like Python or pre-built software for analysis.Generating clear visuals and actionable insights.Benefits for BusinessesUnderstanding customer and employee feedback more effectively.Staying ahead of competitors.Saving time while making informed, data-driven decisions.Call to ActionEncourage listeners to explore DTM to gain a competitive edge.Mukundan invites questions and collaboration via email: mukundansankar.substack.com.Memorable Quotes: "Dynamic Topic Modeling helps businesses turn text data into actionable business strategies.""With DTM, you can stay ahead of competitors by understanding what customers truly care about over time.""It's not just about making decisions but smarter decisions driven by data."Real-Life Examples: Amazon Reviews: How DTM categorizes feedback into price, durability, and other topics.Marketing Adjustments: Shifting focus to features customers prioritize.Trend Analysis: Tracking the rise of sustainability in customer demands.Employee Insights: Using DTM to predict trends in employee satisfaction and churn.Resources Mentioned: Dynamic Topic Modeling Tools: Python and other software solutions for beginners and professionals.Email for Guidance: mukundansankar.substack.com

Supported by Our Partner DX⁠ → DX is an engineering intelligence platform designed by leading researchers — In today’s exciting episode of The Pragmatic Engineer, I am joined by two members of the Notion mobile apps team, Austin Louden and Karn Saheb. Austin and Karn joined Notion in 2019 when Notion was revamping its mobile apps.  Notion is a versatile productivity and collaboration platform that combines note-taking, task management, and knowledge organization into a single workspace. It is available as a web app, as well as iOS and Android apps for mobile use. In our conversation today, we take a deep dive into how the Notion mobile team operates and discuss the following:  • What the engineering culture is like at Notion  • Why the mobile team focuses so much on app performance • The incremental shift from Cordova to Native  • Notion’s tech stack and frameworks they rely on  • How the mobile team maintains consistency across iOS and Android • Unique features of the development process, including a public beta, using modules, and practices around feature flags • … and much more! — Timestamps (00:00) Intro (02:03) The RFC process at Notion  (06:00) How Notion uses internal channels to share RFCs (07:57) Some of the unique ways the mobile team works (11:07) Why they don’t do sprint planning at Notion—and what they do instead (12:57) An overview of the size of Notion and teams at Notion (13:15) The beginning of mobile at Notion (14:40) A simple explanation of Cordova (15:40) Why Notion decided to revamp mobile in 2019 and shift to Native (18:30) How the mobile team evaluated performance as they made the shift to Native (22:00) Scaling mobile and iterations of moving to Native  (26:04) Why the home tab project was so complex (30:59) Why the mobile team saved the editor for last and other future problems (34:35) How mobile works with other teams  (36:50) How iOS and Android teams work together  (38:28) The tech stack at Notion (39:30) How frameworks are used (41:57) Pros and cons of different frameworks and why Swift was the right choice (45:16) How code reviews work at Notion (48:23) Notion’s mobile team’s testing philosophy (50:18) How the mobile team keeps compile time so fast (52:36) Modules in the iOS app (54:50) Modules in the Android app (56:44) Behind the scenes of an app release and the public beta (1:00:34) Practices around feature flags (1:03:00) The four dev environments at Notion (1:04:48) How development apps work  (1:07:40) How and why you can work offline in Notion mobile  (1:10:24) Austin and Karn’s thoughts on the future of mobile engineering  (1:12:47) Advice for junior engineers (1:16:29) Rapid fire round — The Pragmatic Engineer deepdives relevant for this episode:

— Where to find Austin Louden: • GitHub: https://github.com/austinlouden • LinkedIn: https://www.linkedin.com/in/austinlouden • Website: https://austinlouden.com/ Where to find Karn Saheb: • GitHub: https://github.com/Karn • LinkedIn: https://github.com/Karn • Website: https://karn.io Where to find Gergely: • Newsletter: https://www.pragmaticengineer.com/ • YouTube: https://www.youtube.com/c/mrgergelyorosz • LinkedIn: https://www.linkedin.com/in/gergelyorosz/ • X: https://x.com/GergelyOrosz — References and Transcripts: 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 Carlos Gonzalez de Villaumbrosia, Founder and CEO of Product School, the global leader in product management training with a community of over two million product professionals. We talk about:

The evolution of the product management functionProduct-led growth: pros & cons, plus where it fits bestProduct management reporting to the CEO vs. marketing or engineeringDrawing lines between product strategy, product marketing, and product managementThink your product isn’t ready for AI? Think again.

🌟 Session Overview 🌟

Session Name: Marketing Mastery, Systems & Processes, 10X Sales Process Speaker: Niks Jansons

🚀 About Big Data and RPA 2024 🚀

Unlock the future of innovation and automation at Big Data & RPA Conference Europe 2024! 🌟 This unique event brings together the brightest minds in big data, machine learning, AI, and robotic process automation to explore cutting-edge solutions and trends shaping the tech landscape. Perfect for data engineers, analysts, RPA developers, and business leaders, the conference offers dual insights into the power of data-driven strategies and intelligent automation. 🚀 Gain practical knowledge on topics like hyperautomation, AI integration, advanced analytics, and workflow optimization while networking with global experts. Don’t miss this exclusive opportunity to expand your expertise and revolutionize your processes—all from the comfort of your home! 📊🤖✨

📅 Yearly Conferences: Curious about the evolution of QA? Check out our archive of past Big Data & RPA sessions. Watch the strategies and technologies evolve in our videos! 🚀 🔗 Find Other Years' Videos: 2023 Big Data Conference Europe https://www.youtube.com/playlist?list=PLqYhGsQ9iSEpb_oyAsg67PhpbrkCC59_g 2022 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEryAOjmvdiaXTfjCg5j3HhT 2021 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEqHwbQoWEXEJALFLKVDRXiP

💡 Stay Connected & Updated 💡

Don’t miss out on any updates or upcoming event information from Big Data & RPA Conference Europe. Follow us on our social media channels and visit our website to stay in the loop!

🌐 Website: https://bigdataconference.eu/, https://rpaconference.eu/ 👤 Facebook: https://www.facebook.com/bigdataconf, https://www.facebook.com/rpaeurope/ 🐦 Twitter: @BigDataConfEU, @europe_rpa 🔗 LinkedIn: https://www.linkedin.com/company/73234449/admin/dashboard/, https://www.linkedin.com/company/75464753/admin/dashboard/ 🎥 YouTube: http://www.youtube.com/@DATAMINERLT

🌟 Session Overview 🌟

Session Name: Unlocking Profit: How AI-Driven Budget Optimization Elevates Marketing Performance Speaker: Mauro Fusco Session Description: The rise of AI has revolutionized ROMI/ROAS optimization, introducing a new level of precision in marketing performance. Through the use of hierarchical machine learning models, the ability to maximize sales from advertising has significantly increased, offering near real-time feedback and enabling more accurate budget sizing and allocation.

This session will demonstrate how incremental machine learning optimization algorithms can drive greater sales and profits compared to traditional budget allocation methods. Attendees will gain insights into how these advanced AI techniques are reshaping marketing strategies for sharper, more effective outcomes.

🚀 About Big Data and RPA 2024 🚀

Unlock the future of innovation and automation at Big Data & RPA Conference Europe 2024! 🌟 This unique event brings together the brightest minds in big data, machine learning, AI, and robotic process automation to explore cutting-edge solutions and trends shaping the tech landscape. Perfect for data engineers, analysts, RPA developers, and business leaders, the conference offers dual insights into the power of data-driven strategies and intelligent automation. 🚀 Gain practical knowledge on topics like hyperautomation, AI integration, advanced analytics, and workflow optimization while networking with global experts. Don’t miss this exclusive opportunity to expand your expertise and revolutionize your processes—all from the comfort of your home! 📊🤖✨

📅 Yearly Conferences: Curious about the evolution of QA? Check out our archive of past Big Data & RPA sessions. Watch the strategies and technologies evolve in our videos! 🚀 🔗 Find Other Years' Videos: 2023 Big Data Conference Europe https://www.youtube.com/playlist?list=PLqYhGsQ9iSEpb_oyAsg67PhpbrkCC59_g 2022 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEryAOjmvdiaXTfjCg5j3HhT 2021 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEqHwbQoWEXEJALFLKVDRXiP

💡 Stay Connected & Updated 💡

Don’t miss out on any updates or upcoming event information from Big Data & RPA Conference Europe. Follow us on our social media channels and visit our website to stay in the loop!

🌐 Website: https://bigdataconference.eu/, https://rpaconference.eu/ 👤 Facebook: https://www.facebook.com/bigdataconf, https://www.facebook.com/rpaeurope/ 🐦 Twitter: @BigDataConfEU, @europe_rpa 🔗 LinkedIn: https://www.linkedin.com/company/73234449/admin/dashboard/, https://www.linkedin.com/company/75464753/admin/dashboard/ 🎥 YouTube: http://www.youtube.com/@DATAMINERLT

🌟 Session Overview 🌟

Session Name: Antonio Zarauz Moreno Speaker: Transforming Financial Services with Generative AI at Credicorp Session Description: The aim of this talk is to showcase recent advancements in Generative AI, including Retrieval-Augmented Generation (RAG) systems, hyper-personalized marketing campaigns through text and image generation, agent performance metrics, and speech analytics systems. This presentation will highlight the scalability, information safety, and tailored efficiency of these solutions, addressing the deployment challenges that have been overcome. Attendees will gain insights into the practical applications, ethical considerations, and best practices for integrating Generative AI into industrial applications.

🚀 About Big Data and RPA 2024 🚀

Unlock the future of innovation and automation at Big Data & RPA Conference Europe 2024! 🌟 This unique event brings together the brightest minds in big data, machine learning, AI, and robotic process automation to explore cutting-edge solutions and trends shaping the tech landscape. Perfect for data engineers, analysts, RPA developers, and business leaders, the conference offers dual insights into the power of data-driven strategies and intelligent automation. 🚀 Gain practical knowledge on topics like hyperautomation, AI integration, advanced analytics, and workflow optimization while networking with global experts. Don’t miss this exclusive opportunity to expand your expertise and revolutionize your processes—all from the comfort of your home! 📊🤖✨

📅 Yearly Conferences: Curious about the evolution of QA? Check out our archive of past Big Data & RPA sessions. Watch the strategies and technologies evolve in our videos! 🚀 🔗 Find Other Years' Videos: 2023 Big Data Conference Europe https://www.youtube.com/playlist?list=PLqYhGsQ9iSEpb_oyAsg67PhpbrkCC59_g 2022 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEryAOjmvdiaXTfjCg5j3HhT 2021 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEqHwbQoWEXEJALFLKVDRXiP

💡 Stay Connected & Updated 💡

Don’t miss out on any updates or upcoming event information from Big Data & RPA Conference Europe. Follow us on our social media channels and visit our website to stay in the loop!

🌐 Website: https://bigdataconference.eu/, https://rpaconference.eu/ 👤 Facebook: https://www.facebook.com/bigdataconf, https://www.facebook.com/rpaeurope/ 🐦 Twitter: @BigDataConfEU, @europe_rpa 🔗 LinkedIn: https://www.linkedin.com/company/73234449/admin/dashboard/, https://www.linkedin.com/company/75464753/admin/dashboard/ 🎥 YouTube: http://www.youtube.com/@DATAMINERLT

🌟 Session Overview 🌟

Session Name: Open Source Entity Resolution - Needs and Challenges Speaker: Sonal Goyal Session Description: Real world data contains multiple records belonging to the same customer. These records can be in single or multiple systems and they have variations across fields, which makes it hard to combine them together, especially with growing data volumes. This hurts customer analytics - establishing lifetime value, loyalty programs, or marketing channels is impossible when the base data is not linked. No AI algorithm for segmentation can produce the right results when there are multiple copies of the same customer lurking in the data. No warehouse can live up to its promise if the dimension tables have duplicates.

With a modern data stack and DataOps, we have established patterns for E and L in ELT for building data warehouses, datalakes and deltalakes. However, the T - getting data ready for analytics still needs a lot of effort. Modern tools like dbt are actively and successfully addressing this. What is also needed is a quick and scalable way to resolve entities to build the single source of truth of core business entities post Extraction and pre or post Loading.

This session would cover the problem of Entity Resolution, its practical applications and challenges in building an entity resolution system. It will also cover Zingg - an Open Source Framework for building Entity Resolution systems. (https://github.com/zinggAI/zingg/) 🚀 About Big Data and RPA 2024 🚀

Unlock the future of innovation and automation at Big Data & RPA Conference Europe 2024! 🌟 This unique event brings together the brightest minds in big data, machine learning, AI, and robotic process automation to explore cutting-edge solutions and trends shaping the tech landscape. Perfect for data engineers, analysts, RPA developers, and business leaders, the conference offers dual insights into the power of data-driven strategies and intelligent automation. 🚀 Gain practical knowledge on topics like hyperautomation, AI integration, advanced analytics, and workflow optimization while networking with global experts. Don’t miss this exclusive opportunity to expand your expertise and revolutionize your processes—all from the comfort of your home! 📊🤖✨

📅 Yearly Conferences: Curious about the evolution of QA? Check out our archive of past Big Data & RPA sessions. Watch the strategies and technologies evolve in our videos! 🚀 🔗 Find Other Years' Videos: 2023 Big Data Conference Europe https://www.youtube.com/playlist?list=PLqYhGsQ9iSEpb_oyAsg67PhpbrkCC59_g 2022 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEryAOjmvdiaXTfjCg5j3HhT 2021 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEqHwbQoWEXEJALFLKVDRXiP

💡 Stay Connected & Updated 💡

Don’t miss out on any updates or upcoming event information from Big Data & RPA Conference Europe. Follow us on our social media channels and visit our website to stay in the loop!

🌐 Website: https://bigdataconference.eu/, https://rpaconference.eu/ 👤 Facebook: https://www.facebook.com/bigdataconf, https://www.facebook.com/rpaeurope/ 🐦 Twitter: @BigDataConfEU, @europe_rpa 🔗 LinkedIn: https://www.linkedin.com/company/73234449/admin/dashboard/, https://www.linkedin.com/company/75464753/admin/dashboard/ 🎥 YouTube: http://www.youtube.com/@DATAMINERLT

Brought to you by: • WorkOS — The modern identity platform for B2B SaaS. • Sevalla — Deploy anything from preview environments to Docker images. • Chronosphere — The observability platform built for control. — Welcome to The Pragmatic Engineer! Today, I’m thrilled to be joined by Grady Booch, a true legend in software development. Grady is the Chief Scientist for Software Engineering at IBM, where he leads groundbreaking research in embodied cognition. He’s the mind behind several object-oriented design concepts, a co-author of the Unified Modeling Language, and a founding member of the Agile Alliance and the Hillside Group. Grady has authored six books, hundreds of articles, and holds prestigious titles as an IBM, ACM, and IEEE Fellow, as well as a recipient of the Lovelace Medal (an award for those with outstanding contributions to the advancement of computing). In this episode, we discuss: • What it means to be an IBM Fellow • The evolution of the field of software development • How UML was created, what its goals were, and why Grady disagrees with the direction of later versions of UML • Pivotal moments in software development history • How the software architect role changed over the last 50 years • Why Grady declined to be the Chief Architect of Microsoft – saying no to Bill Gates! • Grady’s take on large language models (LLMs) • Advice to less experienced software engineers • … and much more! — Timestamps (00:00) Intro (01:56) What it means to be a Fellow at IBM (03:27) Grady’s work with legacy systems (09:25) Some examples of domains Grady has contributed to (11:27) The evolution of the field of software development (16:23) An overview of the Booch method (20:00) Software development prior to the Booch method (22:40) Forming Rational Machines with Paul and Mike (25:35) Grady’s work with Bjarne Stroustrup (26:41) ROSE and working with the commercial sector (30:19) How Grady built UML with Ibar Jacobson and James Rumbaugh (36:08) An explanation of UML and why it was a mistake to turn it into a programming language (40:25) The IBM acquisition and why Grady declined Bill Gates’s job offer  (43:38) Why UML is no longer used in industry  (52:04) Grady’s thoughts on formal methods (53:33) How the software architect role changed over time (1:01:46) Disruptive changes and major leaps in software development (1:07:26) Grady’s early work in AI (1:12:47) Grady’s work with Johnson Space Center (1:16:41) Grady’s thoughts on LLMs  (1:19:47) Why Grady thinks we are a long way off from sentient AI  (1:25:18) Grady’s advice to less experienced software engineers (1:27:20) What’s next for Grady (1:29:39) Rapid fire round — The Pragmatic Engineer deepdives relevant for this episode: • The Past and Future of Modern Backend Practices https://newsletter.pragmaticengineer.com/p/the-past-and-future-of-backend-practices  • What Changed in 50 Years of Computing https://newsletter.pragmaticengineer.com/p/what-changed-in-50-years-of-computing  • AI Tooling for Software Engineers: Reality Check https://newsletter.pragmaticengineer.com/p/ai-tooling-2024 — Where to find Grady Booch: • X: https://x.com/grady_booch • LinkedIn: https://www.linkedin.com/in/gradybooch • Website: https://computingthehumanexperience.com Where to find Gergely: • Newsletter: https://www.pragmaticengineer.com/ • YouTube: https://www.youtube.com/c/mrgergelyorosz • LinkedIn: https://www.linkedin.com/in/gergelyorosz/ • X: https://x.com/GergelyOrosz — References and Transcripts: 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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We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here. Edge computing is poised to transform industries by bringing computation and data storage closer to the source of data generation. This shift unlocks new types of value creation with data & AI and allows for a privacy-first and deeply personalized use of AI on our devices. What will the edge computing transition look like? How do you ensure applications are edge-ready, and what is the role of AI in the transition?  Derek Collison is the founder and CEO at Synadia. He is an industry veteran, entrepreneur and pioneer in large-scale distributed systems and cloud computing. Derek founded Synadia Communications and Apcera, and has held executive positions at Google, VMware, and TIBCO Software. He is also an active angel investor and a technology futurist around Artificial Intelligence, Machine Learning, IOT and Cloud Computing. Justyna Bak is VP of Marketing at Synadia. Justyna is a versatile executive bridging Marketing, Sales and Product, a spark-plug for innovation at startups and Fortune 100 and a tech expert in Data Analytics and AI, AppDev and Networking. She is an astute influencer, panelist and presenter (Google, HBR) and a respected leader in Silicon Valley and Europe. In the episode, Richie, Derek, and Justyna explore the transition from cloud to edge computing, the benefits of reduced latency, real-time decision-making in industries like manufacturing and retail, the role of AI at the edge, and the future of edge-native applications, and much more. Links Mentioned in the Show: SynadiaConnect with Derek and JustynaCourse: Understanding Cloud ComputingRelated Episode: The Database is the Operating System with Mike Stonebraker, CTO & Co-Founder At DBOSRewatch sessions from RADAR: Forward 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

Episode Description: Welcome to a world where technology works smarter, not harder. In this episode, we dive deep into the world of AI agents—autonomous systems designed to take on tasks, make decisions, and even generate creative ideas with minimal human intervention. Think of them as your digital teammates, always ready to help without needing a lunch break. Here’s what we explore: What Are AI Agents? Learn the basics of these advanced systems, how they work, and why they’re more than just another AI tool.Challenges They Solve: From automating repetitive tasks like customer support to analyzing data for better decisions, AI agents can handle the heavy lifting while you focus on growth.Why They Matter for Solopreneurs and Small Teams: Discover how startups and creators are using AI agents to scale their operations without the costs of hiring more people.Real-Life Examples: Hear how an AI agent can streamline marketing efforts, boost customer engagement, and even help overcome creative blocks.How to Set Up Your Own AI Agent: Step-by-step guidance to get started, whether you’re a tech novice or a seasoned pro.We provide tips and tricks to get your agent up and running without needing a tech background.

Episode Overview In this fascinating episode, we explore Multimodal AI—the cutting-edge technology that's reshaping how businesses solve complex problems. Think of it as a brilliant detective, piecing together clues from text, images, audio, and video to solve mysteries that would otherwise go unnoticed. Whether it's improving customer satisfaction, boosting team performance, or outsmarting competitors, Multimodal AI has the answers. Let’s dive into the details and discover how this incredible tool can transform the way you work. What Is Multimodal AI? Multimodal AI is like a detective for businesses. Instead of relying on just one type of information, it gathers and analyzes data from multiple sources: Text: Emails, reports, and customer feedback.Images: Product photos, website heatmaps, and ads.Audio: Recorded conversations and customer support calls.Video: Marketing content, training sessions, and competitor campaigns.By combining all these clues, Multimodal AI provides a full picture of what’s really happening in your business. How It Solves Problems Imagine running a company where data is scattered everywhere. Multimodal AI connects the dots to find hidden solutions. For example: Sales Drop Mystery: It reads sales reports (text), analyzes fewer clicks on your website (image), listens to customer complaints (audio), and reviews competitor ads (video). The answer? Your competitor’s design is outperforming yours.Employee Training Issues: By scanning training videos and listening to feedback, it uncovers why new hires are struggling and suggests solutions.Customer Dissatisfaction: It pieces together product reviews, social media chatter, and customer service calls to highlight what your audience really wants.The Detective’s Toolkit Multimodal AI has a wide range of tools that can help your business: Competitor Analysis: Tracks trends from competitor ads and online content to refine your strategy.Pattern Recognition: Finds inefficiencies in processes, helping you unlock hidden opportunities.Customer Insights: Decodes reviews, photos, and social media to tell you exactly what your customers desire.Employee Feedback: Helps improve team performance by analyzing onboarding videos and feedback sessions.Why It Matters With Multimodal AI, you don’t just respond to problems—you prevent them. Whether it’s a struggling campaign or unhappy customers, this tool can solve the issue before it escalates into a crisis. It’s like having a corporate Sherlock Holmes by your side, ensuring your business stays one step ahead. Final Thoughts Multimodal AI is more than just technology—it’s your secret weapon for success. Tune in to this episode to learn how it works, why it’s essential, and how it can take your business to the next level. Listen now and solve your toughest challenges with Multimodal AI!

Brought to you by: • Launch Darkly — a platform for high-velocity engineering teams to release, monitor, and optimize great software.  • Sevalla — Deploy anything from preview environments to Docker images. • WorkOS — The modern identity platform for B2B SaaS. — On today’s episode of The Pragmatic Engineer, I’m joined by fellow Uber alum, Sabin Roman, now the first Engineering Manager at Linear. Linear, known for its powerful project and issue-tracking system, streamlines workflows throughout the product development process. In our conversation today, Sabin and I compare building projects at Linear versus our experiences at Uber. He shares insights into Linear’s unique approaches, including: • How Linear handles internal communications • The “goalie” program to address customer concerns and Linear’s zero bug policy • How Linear keeps teams connected despite working entirely remotely • An in-depth, step-by-step walkthrough of a project at Linear • Linear’s focus on quality and creativity over fash shipping  • Titles at Linear, Sabin’s learnings from Uber, and much more! Timestamps (00:00) Intro (01:41) Sabin’s background (02:45) Why Linear rarely uses e-mail internally (07:32) An overview of Linear's company profile (08:03) Linear’s tech stack (08:20) How Linear operated without product people (09:40) How Linear stays close to customers (11:27) The shortcomings of Support Engineers at Uber and why Linear’s “goalies” work better (16:35) Focusing on bugs vs. new features (18:55) Linear’s hiring process (21:57) An overview of a typical call with a hiring manager at Linear (24:13) The pros and cons of Linear’s remote work culture (29:30) The challenge of managing teams remotely (31:44) A step-by-step walkthrough of how Sabin built a project at Linear  (45:47) Why Linear’s unique working process works  (49:57) The Helix project at Uber and differences in operations working at a large company (57:47) How senior engineers operate at Linear vs. at a large company (1:01:30) Why Linear has no levels for engineers  (1:07:13) Less experienced engineers at Linear (1:08:56) Sabin’s big learnings from Uber (1:09:47) Rapid fire round — The Pragmatic Engineer deepdives relevant for this episode: • The story of Linear, as told by its CTO • An update on Linear, after their $35M fundraise • Software engineers leading projects • Netflix’s historic introduction of levels for software engineers — Where to find Sabin Roman: • X: https://x.com/sabin_roman • LinkedIn: https://www.linkedin.com/in/sabinroman/ Where to find Gergely: • Newsletter: https://www.pragmaticengineer.com/ • YouTube: https://www.youtube.com/c/mrgergelyorosz • LinkedIn: https://www.linkedin.com/in/gergelyorosz/ • X: https://x.com/GergelyOrosz — References and Transcripts: 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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Tanya Bragin and I have a wide-ranging chat about the tension of open source and commercial products, Clickhouse, aligning marketing and product, and how she manages her time.

Power BI is one of the hottest data analysis tools in today's job market. In this episode, Aaron Parry will talk about why Power BI is in such high demand, the things companies are hiring Power BI experts for, and where you should focus if you want to add Power BI to your bag of tricks.  You'll leave the show with a deeper understanding of why Power BI is so valuable, what it can do, and where you should focus if you want to build Power BI skills that will advance your career. What You'll Learn: What makes Power BI such a valuable skill set for so many roles Some of the most valuable ways you can use Power BI on the job Where you should focus if you want to build job-ready Power BI skills   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   About our guests: Aaron is a professional analytics consultant and Microsoft Power BI expert, with 10+ years working in business intelligence and marketing analytics. He's an instructor, coach and mentor for aspiring analysts, and has deep experience helping companies develop and implement full-stack BI solutions. Follow Aaron on LinkedIn

Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

Keynote talk

Episode Overview: In this episode, we dive into how AI is transforming Customer Lifetime Value (CLV) prediction, a crucial metric for marketers aiming to understand and enhance customer relationships. We discuss why traditional CLV models fall short, how AI provides more accurate, real-time insights, and why this shift is vital for modern marketing strategies. Key Takeaways: Importance of CLV: CLV helps identify high-value customers, guiding where to focus marketing efforts for long-term success.Limitations of Traditional CLV Models: Outdated methods rely on static data and often miss dynamic changes in customer behavior.AI-Powered CLV Prediction:Real-time data processing enables timely responses to shifts in customer activity.Enhanced segmentation allows marketers to understand not just who their customers are, but how they engage.Predictive capabilities help foresee customer behavior, enabling proactive marketing strategies.Practical Insights:AI tools like Google AutoML and Salesforce Einstein offer accessible ways to integrate AI into marketing without needing extensive technical expertise.Start by organizing and cleaning customer data to ensure accuracy and effectiveness in AI analysis. Chapter-wise Breakdown Introduction & Topic Overview (00:00 - 00:10)Simplifying CLV & Its Traditional Challenges (00:10 - 02:00)The Power of AI for CLV (02:00 - 05:00)AI-Driven Benefits & Customer Insights (05:00 - 09:16)Case Study: Starbucks' Success with AI (09:16 - 12:45)Practical Steps & Final Takeaways (12:45 - End) Real-Life Example: We highlight how Starbucks uses AI to track customer interactions and adapt their marketing efforts based on real-time insights, showcasing the tangible benefits of adopting AI for CLV prediction. Why It Matters: AI-driven CLV prediction isn’t just a trend; it’s a strategic shift that allows marketers to build stronger, data-backed relationships with their customers and stay ahead in an ever-competitive landscape. Final Thought: If you’re not using AI for CLV yet, now is the time to start. Small, data-driven steps can lead to significant improvements in customer retention and business growth.

We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here. Understanding where the data you use comes from, how to use it responsibly, and how to maximize its value has become essential. But as data sources multiply, so do the complexities around data privacy, customization, and ownership. How can companies capture and leverage the right data to create meaningful customer experiences while respecting privacy? And as data drives more personalized interactions, what steps can businesses take to protect sensitive information and navigate the increasingly complex regulatory picture?  Jonathan Bloch is CEO at Exchange Data International (EDI) and a seasoned businessman with 40 years experience in information provision. He started work in the newsletter industry and ran the US subsidiary of a UK public company before joining its main board as head of its publishing division. He has been a director and/or chair of several companies and is currently a non executive director of an FCA registered investment bank. In 1994 he founded Exchange Data International (EDI) a London based financial data provider. EDI now has over 450 clients across three continents and is based in the UK, USA, India and Morocco employing 500 people. Scott Voigt is CEO and co-founder at Fullstory. Scott has enjoyed helping early-stage software businesses grow since the mid 90s, when he helped launch and take public nFront—one of the world's first Internet banking service providers. Prior to co-founding Fullstory, Voigt led marketing at Silverpop before the company was acquired by IBM. Previously, he worked at Noro-Moseley Partners, the Southeast's largest Venture firm, and also served as COO at Innuvo, which was acquired by Google. Scott teamed up with two former Innuvo colleagues, and the group developed the earliest iterations of Fullstory to understand how an existing product was performing. It was quickly apparent that this new platform provided the greatest value—and the rest is history. In the episode, Richie, Jonathan and Scott explore first-party vs third-party data, protecting corporate data, behavioral data, personalization, data sourcing strategies, platforms for storage and sourcing, data privacy, synthetic data, regulations and compliance, the future of data collection and storage, and much more.  Links Mentioned in the Show: FullstoryExchange Data InternationalConnect with Jonathan and ScottCourse: Understanding GDPRRelated Episode: How Data and AI are Changing Data Management with Jamie Lerner, CEO, President, and Chairman at QuantumSign up to RADAR: Forward Edition New to DataCamp? Learn on the go using the DataCamp mobile...

Brought to you by: • WorkOS — The modern identity platform for B2B SaaS. • Sonar —  Trust your developers – verify your AI-generated code. — In today’s episode of The Pragmatic Engineer, I’m joined by Irina Stanescu, a seasoned engineer with over 14 years in software engineering and engineering leadership roles at tech companies like Google and Uber. Now an engineering leadership coach, Irina helps tech professionals build impactful careers, teaches a course on influence, and shares insights through her newsletter, The Caring Techie. In our conversation today, Irina shares her journey of rising through the ranks at Google and Uber. We dive into the following topics:  • An inside look at Google’s unique working processes • How to build credibility as a new engineer • Tactical tips for getting promoted  • The importance of having a career plan and guidance in designing one • Having influence vs. influencing—and how to become more influential  • Essential leadership skills to develop • And so much more — In this episode, we cover: (01:34) Irina’s time at Google (03:10) An overview of ‘design docs’ at Google (08:27) The readiness review at Google (10:40) Why Irina uses spreadsheets (11:44) Irina’s favorite tools and how she uses them (13:46) How Google certifies readability (15:40) Google’s meme generator  (17:36) Advice for engineers thinking about working for an organization like Google (20:14) How promotions work at Google (23:15) How Irina worked towards getting promoted  (27:50) How Irina got her first mentor  (30:44) Organizational shifts at Uber while Irina and Gergely were there (35:50) Why you should prioritize growth over promotion (36:50) What a career plan is and how to build one (40:40) Irina’s current role coaching engineers  (42:23) A simple explanation of influence and influencing  (51:54) Why saying no is necessary at times (54:30) The importance of building leadership skills — The Pragmatic Engineer deepdives relevant for this episode: • Preparing for promotions ahead of time: https://newsletter.pragmaticengineer.com/p/preparing-for-promotions  • Engineering career paths at Big Tech and scaleups: https://newsletter.pragmaticengineer.com/p/engineering-career-paths  • Getting an Engineering Executive Job: https://newsletter.pragmaticengineer.com/p/getting-an-engineering-executive  • The Seniority Rollercoaster: https://newsletter.pragmaticengineer.com/p/the-seniority-rollercoaster — Where to find Irina Stanescu: • X: https://x.com/thecaringtechie • LinkedIn: https://www.linkedin.com/in/irinastanescu/ • Website: https://www.thecaringtechie.com/ • Maven course: Impact through Influence in Engineering Teams: https://maven.com/irina-stanescu/influence-swe Where to find Gergely: • Newsletter: https://www.pragmaticengineer.com/ • YouTube: https://www.youtube.com/c/mrgergelyorosz • LinkedIn: https://www.linkedin.com/in/gergelyorosz/ • X: https://x.com/GergelyOrosz — References and Transcripts: 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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As AI continually changes how businesses operate, new questions emerge around ethics and privacy. Nowadays, algorithms can set prices and personalize offers, but how do companies ensure they’re doing this responsibly? What does it mean to be transparent with customers about data use, and how can businesses avoid unintended bias? Balancing innovation with trust is key, but achieving this balance isn’t always straightforward. Dr. Jose Mendoza is Academic Director and Clinical Associate Professor in Integrated Marketing at NYU, and was formerly an Associate Professor of Practice at The University of Arizona in Tucson, Arizona. His focus is on consumer pricing, digital retailing, intelligent retail stores, neuromarketing, big data, artificial intelligence, and machine learning. Previously, he taught marketing courses at Sacred Heart University and Western Michigan University. He is also an experienced senior global marketing executive with over 18 years of experience in global marketing alone and a career as an Engineer in Information Sciences. Dr. Mendoza is also a Doctoral Researcher in Strategic and Global pricing, Consumer Behavior, and Pricing Research methodologies. He had international roles in Latin America, Europe, and the USA with scope in over 50 countries.  In the episode, Richie and Jose explore AI-driven pricing, consumer perceptions and ethical pricing, the complexity of dynamic pricing models, explainable AI, data privacy and customer trust, legal and ethical guardrails, innovations in dynamic pricing and much more.  Links Mentioned in the Show: NYUConnect with JoseAmazon Dynamic Pricing Strategy in 2024Course: AI EthicsRelated Episode: The Future of Marketing Analytics with Cory Munchbach, CEO at BlueConicSign up to RADAR: Forward 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