The Marco Show

Axel Fontaine, creator of Flyway, one of the most popular database migration tools, joins Marco to share how he built a global open source project, turned it into a profitable business, and sold it to Redgate. From bootstrapping alone to making millions without investors, Axel’s story is a deep dive into the business side of coding.💡 Topics in this episode:How Flyway grew from a side project to an acquisitionThe power of simplicity and zero dependenciesTurning open source into a sustainable businessBootstrapping vs venture capitalLife after selling your company⏱️ Timestamps:(00:00) Intro(00:54) Guest introduction(01:18) What is Flyway?(02:16) Evolution of databases and CI/CD(07:37) The idea and first version of Flyway(10:41) Competitors and why Axel built his own tool(13:27) Building Flyway’s simplicity and focus(17:30) Design principles: zero dependencies and reliability(20:18) Learning user focus through onboarding docs(23:31) How Flyway’s roadmap evolved(27:00) Handling bugs, testing challenges, and quality(31:27) Marketing and early promotion(33:49) The Maven Release Plugin blog post(36:07) Technical mistakes and lessons learned(38:28) Managing contributors and open-source community(44:44) Burnout and balancing workload(50:43) Turning Flyway into a business(52:20) Failed monetization attempts(01:09:11) Licensing, IP cleanup, and CLA process(01:30:02) First commercial release and first sale(01:31:56) Rapid revenue growth(01:39:07) Leaving consulting and going full-time on Flyway(01:44:30) Negotiating with enterprise customers(01:46:55) Acquisition interest and decision process(01:52:46) Decision to sell(02:04:57) Life after the sale and reflection(02:07:38) Key lessons for founders(02:09:50) Giveaway(02:10:47) Rapid-fire questions(02:13:18) OutroNew episodes every other Wednesday. Subscribe for more deep, developer-focused conversations.📺 Watch the episodes on YouTube: https://youtu.be/lwF2fg1fOHk 

📺 Note: This episode contains screensharing and live coding examples that work best visually. If you’d like to follow along, check out the full video version on YouTube: https://youtu.be/Qvh3VFlvJnE.Gavin King (creator of Hibernate) joins Marco to cut through the myths of Java persistence. When should you skip layers of repositories and just write SQL, or even model database views? What actually causes lazy-loading pain, and how do stateless sessions help? We cover Hibernate, JPA, and where Jakarta Data is headed, plus pragmatic advice for legacy schemas, performance, and keeping your code DRY.💡 Topics in this episode:• SQL vs repositories (and why views can be your adapter layer)• The three inheritance strategies, and the trap of table-per-class• Stateless sessions vs stateful persistence contexts• LazyInitializationException explained (and avoided)• DRY first: let architecture emerge via refactoring• Jakarta Data 1.0/1.1: annotation processing, stateful repos, dynamic queries• Performance rule-of-thumb: minimize round-trips⏱️ Timestamps(00:00) Teaser(01:00) Gavin King intro and early Hibernate motivation(03:59) Old-school open-source culture and discovery(08:39) SQL isn’t hard: minimize DB round-trips(10:03) “Leaky abstractions are good” (and why)(12:04) Architecture should emerge from code(15:44) DRY as commandment #1(22:05) Reviewing a typical Spring Data setup (and pitfalls)(25:39) Inheritance strategies: joined vs single table vs table-per-class(30:06) One screen? Just write a SQL query (pragmatism)(33:08) When ORM shines: operations over graphs(35:22) Use views to adapt messy legacy schemas(43:18) Jakarta Data repos: annotation-driven, step-into-able(44:59) Stateless Session: less magic, explicit updates(48:51) Jakarta Data 1.1: stateful repos, dynamic queries, reactive(01:24:22) Rapid fire questions(01:33:15) Features Gavin would delete and lessons learned(01:42:30) GiveawayNew episodes every other Wednesday. Subscribe for deep, developer-focused conversations.

Casey Muratori, a programmer and performance advocate with a background in game development, joins for a compelling discussion on software performance issues. He delves into the frustrations surrounding slow software despite powerful hardware, sharing insights into the notorious Windows Terminal controversy. Casey emphasizes avoiding 'ridiculously slow' code and practical strategies for performance gains, such as parallel processing in Java. He also tackles the ethical implications of AI, advocating for respectful use of data in technology.

Jodie Burchell (Data Scientist) joins Marco to cut through the hype around large language models. From GPT and Gemini to Claude and beyond — how do you really choose the right one? Benchmarks, context length, hallucinations, ethics, and AGI predictions — all on the table.If you’ve ever asked yourself, “Which LLM should I use for my work?” — this conversation will help you see past the hype.💡 Topics in this episode:How to compare LLMs for different developer tasksEnhanced vs adaptive thinking (is it just branding?)Corporate considerations: cost, privacy, and hostingThe ethics and lawsuits shaping AI’s futurePredictions for AGI⏱️Timestamps:(00:00:00) Teaser(00:00:37) Intro(00:01:08) From PhD and academia to data science at JetBrains(00:02:31) Early NLP versus modern LLMs(00:04:46) From LSTMs to Transformers (BERT and GPT)(00:08:49) The DeepSeek surprise and model scaling limits(00:12:25) Benchmarks, assessments, and confusion for end users(00:17:18) Choosing models in practice(00:21:10) “Thinking” models and reasoning limits(00:23:48) Do you really need the newest model?(00:25:58) Hallucinations and how to handle them(00:28:30) Agents and RAG: real-world applications(00:32:55) Vibe coding: hype versus reality(00:37:46) What are AI agents? Tools, MCP, and multi-agent apps(00:43:01) Self-hosting versus proprietary models(00:45:20) Fine-tuning explained and Hugging Face(00:50:17) Building reliable AI apps (tests, A/B, traces)(00:55:33) Privacy, company data, and self-hosting concerns(00:58:37) Ethical issues: data sourcing and labor(01:04:23) Environmental costs and the push for smaller models(01:06:26) Juniors, skills, and the future of coding with AI(01:09:15) Learning fundamentals in the age of LLMs(01:13:24) AGI: definitions, timelines, and Jodie’s twenty euro bet(01:20:03) Rapid-fire questions: slang, food, and culture(01:25:47) Giveaway(01:26:26) OutroNew episodes every other Wednesday. Subscribe for more deep, developer-focused conversations.Watch the episodes on YouTube: https://jb.gg/themarco.show-youtubeFollow Jodie Burchell:LinkedIn: jodieburchellBluesky: @t-redactyl.bsky.socialMastodon: @t_redactyl@fosstodon.orgFollow The Marco Show:Instagram: @themarco.showTikTok: @themarco.show