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| Title & Speakers | Event |
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How AI will change software engineering – with Martin Fowler
2025-11-19 · 17:09
Gergely Orosz
– host
,
Martin Fowler
– Chief Scientist
@ Thoughtworks
Brought to You By: • Statsig — The unified platform for flags, analytics, experiments, and more. AI-accelerated development isn’t just about shipping faster: it’s about measuring whether, what you ship, actually delivers value. This is where modern experimentation with Statsig comes in. Check it out. • Linear — The system for modern product development. I had a jaw-dropping experience when I dropped in for the weekly “Quality Wednesdays” meeting at Linear. Every week, every dev fixes at least one quality isse, large or small. Even if it’s one pixel misalignment, like this one. I’ve yet to see a team obsess this much about quality. Read more about how Linear does Quality Wednesdays – it’s fascinating! — Martin Fowler is one of the most influential people within software architecture, and the broader tech industry. He is the Chief Scientist at Thoughtworks and the author of Refactoring and Patterns of Enterprise Application Architecture, and several other books. He has spent decades shaping how engineers think about design, architecture, and process, and regularly publishes on his blog, MartinFowler.com. In this episode, we discuss how AI is changing software development: the shift from deterministic to non-deterministic coding; where generative models help with legacy code; and the narrow but useful cases for vibe coding. Martin explains why LLM output must be tested rigorously, why refactoring is more important than ever, and how combining AI tools with deterministic techniques may be what engineering teams need. We also revisit the origins of the Agile Manifesto and talk about why, despite rapid changes in tooling and workflows, the skills that make a great engineer remain largely unchanged. — Timestamps (00:00) Intro (01:50) How Martin got into software engineering (07:48) Joining Thoughtworks (10:07) The Thoughtworks Technology Radar (16:45) From Assembly to high-level languages (25:08) Non-determinism (33:38) Vibe coding (39:22) StackOverflow vs. coding with AI (43:25) Importance of testing with LLMs (50:45) LLMs for enterprise software (56:38) Why Martin wrote Refactoring (1:02:15) Why refactoring is so relevant today (1:06:10) Using LLMs with deterministic tools (1:07:36) Patterns of Enterprise Application Architecture (1:18:26) The Agile Manifesto (1:28:35) How Martin learns about AI (1:34:58) Advice for junior engineers (1:37:44) The state of the tech industry today (1:42:40) Rapid fire round — The Pragmatic Engineer deepdives relevant for this episode: • Vibe coding as a software engineer • The AI Engineering stack • AI Engineering in the real world • What changed in 50 years of computing — Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected]. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe |
The Pragmatic Engineer |
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Bitemporality and the Art of Maintaining Accurate Databases
2023-08-10 · 16:00
Our friends from Juxt are presenting the following webinar: Title: Bitemporality and the Art of Maintaining Accurate Databases Speaker: Jeremy Taylor & James Handerson This is an online event hosted on GoToWebinar — in order to attend it, please register via this link (and not by clicking "attend"): https://attendee.gotowebinar.com/register/2960607012900067930?source=lnd-clojurians-meetup Recently, various industry luminaries — including Kent Beck, Martin Fowler, Ben Stopford, and Kris Jenkins — have been talking about bitemporality. But what does bitemporality really mean for you, your team, and your business? How might it impact your work over the next 12 months? In my upcoming webinar, I will attempt to demystify bitemporality — join me to discover the most common use cases for bitemporal modeling, and learn how it impacts application design and maintenance.
Register here: https://attendee.gotowebinar.com/register/2960607012900067930?source=lnd-clojurians-meetup |
Bitemporality and the Art of Maintaining Accurate Databases
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Database Refactoring Patterns with Pramod Sadalage - Episode 22
2018-03-12 · 04:00
Pramod Sadalage
– guest
,
Tobias Macey
– host
Summary As software lifecycles move faster, the database needs to be able to keep up. Practices such as version controlled migration scripts and iterative schema evolution provide the necessary mechanisms to ensure that your data layer is as agile as your application. Pramod Sadalage saw the need for these capabilities during the early days of the introduction of modern development practices and co-authored a book to codify a large number of patterns to aid practitioners, and in this episode he reflects on the current state of affairs and how things have changed over the past 12 years. Preamble Hello and welcome to the Data Engineering Podcast, the show about modern data infrastructure When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at dataengineeringpodcast.com/linode and get a $20 credit to try out their fast and reliable Linux virtual servers for running your data pipelines or trying out the tools you hear about on the show. Go to dataengineeringpodcast.com to subscribe to the show, sign up for the newsletter, read the show notes, and get in touch. You can help support the show by checking out the Patreon page which is linked from the site. To help other people find the show you can leave a review on iTunes, or Google Play Music, and tell your friends and co-workers Your host is Tobias Macey and today I’m interviewing Pramod Sadalage about refactoring databases and integrating database design into an iterative development workflow Interview Introduction How did you get involved in the area of data management? You first co-authored Refactoring Databases in 2006. What was the state of software and database system development at the time and why did you find it necessary to write a book on this subject? What are the characteristics of a database that make them more difficult to manage in an iterative context? How does the practice of refactoring in the context of a database compare to that of software? How has the prevalence of data abstractions such as ORMs or ODMs impacted the practice of schema design and evolution? Is there a difference in strategy when refactoring the data layer of a system when using a non-relational storage system? How has the DevOps movement and the increased focus on automation affected the state of the art in database versioning and evolution? What have you found to be the most problematic aspects of databases when trying to evolve the functionality of a system? Looking back over the past 12 years, what has changed in the areas of database design and evolution? How has the landscape of tooling for managing and applying database versioning changed since you first wrote Refactoring Databases? What do you see as the biggest challenges facing us over the next few years? Contact Info Website pramodsadalage on GitHub @pramodsadalage on Twitter Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Links Database Refactoring Website Book Thoughtworks Martin Fowler Agile Software Development XP (Extreme Programming) Continuous Integration The Book Wikipedia Test First Development DDL (Data Definition Language) DML (Data Modification Language) DevOps Flyway Liquibase DBMaintain Hibernate SQLAlchemy ORM (Object Relational Mapper) ODM (Object Document Mapper) NoSQL Document Database MongoDB OrientDB CouchBase CassandraDB Neo4j ArangoDB Unit Testing Integration Testing OLAP (On-Line Analytical Processing) OLTP (On-Line Transaction Processing) Data Warehouse Docker QA==Quality Assurance HIPAA (Health Insurance Portability and Accountability Act) PCI DSS (Payment Card Industry Data Security Standard) Polyglot Persistence Toplink Java ORM Ruby on Rails ActiveRecord Gem The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA Support Data Engineering Podcast |
Data Engineering Podcast |
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Analysis Patterns: Reusable Object Models
2015-05-21
Martin Fowler
– author
This innovative book recognizes the need within the object-oriented community for a book that goes beyond the tools and techniques of the typical methodology book. In Analysis Patterns: Reusable Object Models, Martin Fowler focuses on the end result of object-oriented analysis and design—the models themselves. He shares with you his wealth of object modeling experience and his keen eye for identifying repeating problems and transforming them into reusable models. Analysis Patterns provides a catalogue of patterns that have emerged in a wide range of domains including trading, measurement, accounting and organizational relationships. Recognizing that conceptual patterns cannot exist in isolation, the author also presents a series of "support patterns" that discuss how to turn conceptual models into software that in turn fits into an architecture for a large information system. Included in each pattern is the reasoning behind their design, rules for when they should and should not be used, and tips for implementation. The examples presented in this book comprise a cookbook of useful models and insight into the skill of reuse that will improve analysis, modeling and implementation. |
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Martin Fowler
– author
,
Pramod J. Sadalage
– author
The need to handle increasingly larger data volumes is one factor driving the adoption of a new class of nonrelational “NoSQL” databases. Advocates of NoSQL databases claim they can be used to build systems that are more performant, scale better, and are easier to program. NoSQL Distilled is a concise but thorough introduction to this rapidly emerging technology. Pramod J. Sadalage and Martin Fowler explain how NoSQL databases work and the ways that they may be a superior alternative to a traditional RDBMS. The authors provide a fast-paced guide to the concepts you need to know in order to evaluate whether NoSQL databases are right for your needs and, if so, which technologies you should explore further. The first part of the book concentrates on core concepts, including schemaless data models, aggregates, new distribution models, the CAP theorem, and map-reduce. In the second part, the authors explore architectural and design issues associated with implementing NoSQL. They also present realistic use cases that demonstrate NoSQL databases at work and feature representative examples using Riak, MongoDB, Cassandra, and Neo4j. In addition, by drawing on Pramod Sadalage’s pioneering work, NoSQL Distilled shows how to implement evolutionary design with schema migration: an essential technique for applying NoSQL databases. The book concludes by describing how NoSQL is ushering in a new age of Polyglot Persistence, where multiple data-storage worlds coexist, and architects can choose the technology best optimized for each type of data access. |
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