Today's guest is Hywel Carver! Hywel is co-founder and CEO of Skiller Whale, which provides live team coaching for software engineering teams. With Hywel, we got deep into what makes traditional developer training awful, what engineers truly learn and what they should learn. Then we explored how to measure the impact of learning and how AI may possibly change both how learning works and our own skills.(00:00) Preview(01:15) Introduction(02:22) Hywel's journey in tech(06:20) Spreading good learning(07:55) Training as a compliance(09:34) The effectiveness of learning(12:42) Training with an expert(18:02) Knowledge, Skill and Wisdom(24:16) How Skiller Whale works?(30:26) The outcomes(34:53) Finding the proper learning method(40:12) Measuring learning value(46:54) AI, humans and code bases—You can also find this at:• 📬 Newsletter: https://refactoring.fm• 🎧 Spotify: https://open.spotify.com/show/7Luds9dmzZDoDC8Q7EMbSw• 📱 Apple: https://podcasts.apple.com/us/podcast/refactoring-podcast/id1719137305—For inquiries about sponsoring the podcast, or appearing as a guest, email: luca@refactoring.club

Today's guest is Darragh Curran!

Darragh is the CTO of Intercom, which is one of the world's leading customer service products with more than 600 million users.

With Darragh, we talked about how AI poses at the same time an existential risk and an incredible opportunity for Intercom, and how this led them to the decision of creating a completely separate product and deflect most team resources to it.

Then we discussed how AI is being adopted inside Intercom itself to achieve Darragh's ambitious goal of doubling the team's productivity.

And finally, we explored Darragh's own role as CTO and what he believes he needs to get right to make all of this happen.

(00:00) Preview

(01:31) Introduction

(02:19) How Intercom changed with AI

(07:02) Intercom and Fin

(11:37) AI productivity gains

(16:36) Measuring productivity increase

(25:06) Experience and AI

(31:02) AI in large and legacy systems

(32:47) The CTO role in an AI framework

(38:56) Good for human = Good for AI

(42:03) Improving AI models: Fin's case

(45:03) How Fin improved so fast

(49:08) One big challenge

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You can also find this at:

• 📬 Newsletter: https://refactoring.fm

• 🎧 Spotify: https://open.spotify.com/show/7Luds9dmzZDoDC8Q7EMbSw

• 📱 Apple: https://podcasts.apple.com/us/podcast/refactoring-podcast/id1719137305

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For inquiries about sponsoring the podcast, or appearing as a guest, email: luca@refactoring.club

Today's guest is Meg Adams!Meg is Senior Director of Engineering for the New York Times. With Meg, we talked about her fantastic journey in tech, from management in sales and retail, to learning software development from scratch, to management again, but this time in technology. And then we especially talked about Neuro Leadership, what it is, how you can apply it in practice in your team processes, and how things are different for ICs versus managers, and how you scale all of this to your whole organization.(01:22) Introduction(01:38) Meg's journey in tech(06:03) Managing skills in individual contribution(09:32) What is Neuroleadership?(11:06) Neuroleadership in tech(14:12) The SCARF model(21:18) Applying the SCARF(27:29) Designing good communication(30:42) Psychological safety(35:10) Identifying a threat(38:28) Making SCARF model part of a culture(41:27) A good example: Meg's time at Etsy—This episode is brought to you by Augment Code! Augment Code is the only AI engineering platform built for real engineering teams.Learn more at augmentcode.com!—You can also find this at:• 📬 Newsletter: https://refactoring.fm• 🎧 Spotify: https://open.spotify.com/show/7Luds9dmzZDoDC8Q7EMbSw• 📱 Apple: https://podcasts.apple.com/us/podcast/refactoring-podcast/id1719137305—For inquiries about sponsoring the podcast, or appearing as a guest, email: luca@refactoring.club

Today's guest is Birgitta Böckeler!

Birgitta is is a distinguished engineer and global lead for AI-assisted software delivery at ThoughtWorks. Her full-time work is to figure out how engineering teams can make the most out of AI.

With Birgitta, we talked about her favorite workflows, how she uses AI in the IDE, in the terminal or in a genetic mode. We discussed AI impact on productivity and what the best teams are getting right, which others are not. And finally, we talked about how AI impacts both junior and senior engineers and how we can get the best out of both skeptics and optimists.

(01:27) Introduction

(04:58) A day in the work of data

(11:04) Large and smalls change sets

(15:57) The strength of Cloud Code

(18:35) Using AI tools in ThoughtWorks

(21:41) Figuring AI productive value

(27:24) Getting the most out of AI

(30:10) AI assistance in large code bases

(32:21) Good for humans = Good for AI

(39:10) AI and documentation

(41:49) Software engineer role in AI landscape

(48:24) Junior engineers and learning

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This episode is brought to you by Augment Code! Augment Code is the only AI engineering platform built for real engineering teams.

Learn more at augmentcode.com!

—

You can also find this at:

• 📬 Newsletter: https://refactoring.fm

• 🎧 Spotify: https://open.spotify.com/show/7Luds9dmzZDoDC8Q7EMbSw

• 📱 Apple: https://podcasts.apple.com/us/podcast/refactoring-podcast/id1719137305

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For inquiries about sponsoring the podcast, or appearing as a guest, email: luca@refactoring.club

Today's guest is Antonia Scheidel!Antonia is Director of Engineering at Duolingo, where she made the whole career progression, starting as a simple intern 12 years ago. Antonia is an expert at designing good, automated processes for your team. We discuss how to create good automation to avoid people doing glue work, how not to become a bottleneck as a manager, and how to make the team own the process and repair it when needed.(01:25) Introduction(02:02) Antonia's journey into tech(03:34) Antonia's career in Duolingo(06:55) From engineering to management(10:19) Good processing and notes(14:18) Fixing the process and team alignment(18:06) The burden of asking(23:08) Invisible work and visible improvements(27:55) Automation trade-offs(33:14) Responsibilities in estabilished processes(37:24) How to do notifications right(49:09) Automation for the sake of relationships(54:33) The "usual suspects" of management—This episode is brought to you by Augment Code! Augment Code is the only AI engineering platform built for real engineering teams.Learn more at augmentcode.com!—You can also find this at:• 📬 Newsletter: https://refactoring.fm• 🎧 Spotify: https://open.spotify.com/show/7Luds9dmzZDoDC8Q7EMbSw• 📱 Apple: https://podcasts.apple.com/us/podcast/refactoring-podcast/id1719137305—For inquiries about sponsoring the podcast, or appearing as a guest, email: luca@refactoring.club

Today's guest is Adam Tornhill! Adam is the author of the popular book Your Code as a Crime Scene, and he's the founder of Code Scene. With Adam, we discussed his unique insights about technical debt and code quality, which come from his study of forensic psychology. We explored how static analysis is not enough to understand code health and why you need to look into version control history to understand hotspots, change distribution and bus factor. And finally, we inevitably talked about AI and how it changes, or maybe does not change, how we should write code.(01:23) Introduction(02:25) Adam's journey into tech(05:58) The crime scene metaphor(08:27) Version control history(10:22) A natural law of software(14:03) Code Red(15:56) Assessing good code health(22:31) Distribution of impact and the bus factor(25:33) Reducing bus factor(29:57) Reassessing knowledge(32:25) The entropy of code bases(34:53) AI in code analysis(39:44) The impact of AI coding(41:58) Preventing technical debt(44:13) The actual developer tool space(46:21) Code data and team ceremonies—This episode is brought to you by Augment Code! Augment Code is the only AI engineering platform built for real engineering teams.Learn more at augmentcode.com!—You can also find this at:• 📬 Newsletter: https://refactoring.fm• 🎧 Spotify: https://open.spotify.com/show/7Luds9dmzZDoDC8Q7EMbSw• 📱 Apple: https://podcasts.apple.com/us/podcast/refactoring-podcast/id1719137305—For inquiries about sponsoring the podcast, or appearing as a guest, email: luca@refactoring.club

Today's guest is Meri Williams, who is the CTO of Pleo and the host of LeadDev conferences for more than 10 years. With Meri, we started by talking about diversity, why it is such a controversial topic, why diverse teams make for stronger teams, and what are the mistakes engineering leaders should avoid. Then we took from her experience with Lead Dev to explore what makes for a good talk, and what Meri looks for when she selects the best ones.And finally, we explored how AI is going to change how we develop engineers and grow junior co-workers.(01:19) Introduction(02:04) Meri's journey into tech(07:29) Conferences, meetups and LeadDev(10:14) Recurring issues in engineering leadership(12:21) Why diversity matters(15:04) A proper diverse environment(22:52) How to create a truly memorable talk(26:25) LeadDev and conferences(28:53) Speaking on stage(30:50) Speaking as a benefit for your career(33:59) Junior engineers in the age of AI(39:37) Is AI a turning point?(44:44) Seniors engineers and AI(46:31) Guiding junior engineers—This episode is brought to you by Augment Code! Augment Code is the only AI engineering platform built for real engineering teams.Learn more at augmentcode.com!—You can also find this at:• 📬 Newsletter: https://refactoring.fm• 🎧 Spotify: https://open.spotify.com/show/7Luds9dmzZDoDC8Q7EMbSw• 📱 Apple: https://podcasts.apple.com/us/podcast/refactoring-podcast/id1719137305—For inquiries about sponsoring the podcast, or appearing as a guest, email: luca@refactoring.club

Today's guest is Annie Duke, who is a former world-class professional poker player and one of the world's top experts on decision-making.She's a bestseller author and coach of many tech founders and teams.With Annie we talked about her journey from studying decision science to becoming a top poker player and back to decision-making. We explored how to make good decisions under uncertainty, alone and in a team. And we particularly focused on quitting decisions, what maked for a good versus a bad quit and why we are so bad at recognizing those.00:01:31 Introduction00:03:45 From poker to decision-making00:08:30 Sponsor00:10:07 Poker and the definition of "resulting"00:16:42 Feedback loops and decision-making00:21:59 Successful but not hungry00:26:14 A good decision-making process00:35:24 Qualifying the market00:38:17 Team decision-making00:47:46 Quitting00:52:43 Make quitting easier01:08:43 Kill criteria—This episode is brought to you by Unblocked! Unblocked brings all the context about your codebase together, so your team gets expert-level answers, no matter where they’re working.Learn more at getunblocked.com!—You can also find this at:• 📬 Newsletter: https://refactoring.fm• 🎧 Spotify: https://open.spotify.com/show/7Luds9dmzZDoDC8Q7EMbSw• 📱 Apple: https://podcasts.apple.com/us/podcast/refactoring-podcast/id1719137305—For inquiries about sponsoring the podcast, or appearing as a guest, email: luca@refactoring.club