🌀 Luca Rossi

Refactoring

I help engineers write great software and work well with humans ❤️

Founder

Translated

Head of Engineering

Wanderio

Co-Founder & CTO

Università degli Studi Roma Tre

Ph.D Student

InnovAction Lab

Alumnus

FHOSTER

Software Engineer

CTO • Author of Refactoring.fm • I write weekly about making software and working with humans, to 50K+ engineers and managers.

Hey! 👋 I am Luca. I am an entrepreneur who loves leading engineering teams working on great products. 

🌀 I am Founder of Refactoring.club  — a weekly newsletter about engineering leadership.
🔨 I was Head of Engineering at Translated between 2020 and 2021,
🚀 I co-founded and was CTO of Wanderio between 2013 and 2020.

When I am not working, I am probably playing guitar or studying how to improve my cacio e pepe 🍝

I help 25K+ managers, founders and developers build better engineering teams ❤️

Managers have been vibe coding forever.

Saw this on X — it put a smile on my face but also made me think a lot.

Author of Refactoring.fm • I write about making software and working together, to 150K+ engineers

We, managers, are back to coding! Is this a good thing?

One of the biggest stories I have been hearing recently is that many engineering managers are back to coding, because of AI. 

AI is helping in two ways:

↳ 🧠 𝗜𝘁 𝗿𝗲𝗱𝘂𝗰𝗲𝘀 𝘁𝗵𝗲 𝗰𝗼𝗴𝗻𝗶𝘁𝗶𝘃𝗲 𝗹𝗼𝗮𝗱 — managers often retain good taste for what good code looks like, but are a bit rusty on implementation details. AI makes the latter less relevant.

↳ 🗓️ 𝗜𝘁 𝗳𝗶𝘁𝘀 𝗰𝗼𝗱𝗶𝗻𝗴 𝗶𝗻𝘁𝗼 𝗽𝗮𝗰𝗸𝗲𝗱 𝗮𝗴𝗲𝗻𝗱𝗮𝘀 — by letting terminal agents run while people are on meetings or doing something else.

Is this a good thing? A reader told me "Managers need to focus on the things that only they can do, rather than the things that anyone on their team can do."

This is not wrong, but I also think many managers end up completely detached from how their team works, and spending some time coding can help *a lot*. 

The benefit here is not about throughput, but about empathy and staying in touch with what the DX and the whole process looks like.

This is most definitely good and I would love to see more of it.

Have a good week! ☀️

refactoringclub

John Obelenus

Our AI industry report is out! It's our biggest research ever! 💥

Together with the folks at Augment Code, over the last three months we surveyed more than 500 teams and held countless conversations with tech leaders about 𝗵𝗼𝘄 𝘁𝗵𝗲𝘆 𝘂𝘀𝗲 𝗔𝗜 𝗶𝗻 𝘁𝗵𝗲𝗶𝗿 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝘁𝗲𝗮𝗺𝘀.

The result is a massive report which combines both quantitative and qualitative data, going out today for ✨ 𝗳𝗿𝗲𝗲 ✨ to every Refactoring subscriber!

Here are some of the main takeaways — and you can find more in the full report in the comments!

↳ 🚀 𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹 𝗮𝗱𝗼𝗽𝘁𝗶𝗼𝗻 𝗶𝘀 𝘀𝘁𝗿𝗼𝗻𝗴 — 77% of engineers use AI daily, with 54% saving 5+ hours weekly through coding assistance and task automation.

↳ 📝 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗶𝘀 𝘁𝗵𝗲 𝘀𝗲𝗰𝗿𝗲𝘁 𝘄𝗲𝗮𝗽𝗼𝗻 — Engineers happiest with AI use it extensively for docs, creating better understanding for both humans and AI.

↳ 👥 𝗧𝗲𝗮𝗺 𝗮𝗱𝗼𝗽𝘁𝗶𝗼𝗻 𝗹𝗮𝗴𝘀 𝗯𝗲𝗵𝗶𝗻𝗱 𝗶𝗻𝗱𝗶𝘃𝗶𝗱𝘂𝗮𝗹 𝘂𝘀𝗲 — While 77% of teams recommend AI tools, most lack shared practices, keeping adoption bottom-up and chaotic.

↳ 💼 𝗠𝗮𝗻𝗮𝗴𝗲𝗿𝘀 𝗮𝗿𝗲 𝗰𝗼𝗱𝗶𝗻𝗴 𝗮𝗴𝗮𝗶𝗻 — AI brings engineering managers back to hands-on work by reducing cognitive load and fitting coding into packed schedules.

↳ 😊 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 𝗮𝗿𝗲 𝗼𝗽𝘁𝗶𝗺𝗶𝘀𝘁𝗶𝗰 — Despite online negativity, 71% believe AI will make their jobs better and more enjoyable.

↳ 📊 𝗛𝗲𝗮𝗱𝗰𝗼𝘂𝗻𝘁 𝗳𝗲𝗮𝗿𝘀 𝗮𝗿𝗲 𝗼𝘃𝗲𝗿𝗯𝗹𝗼𝘄𝗻 — Only 11% of Directors/VPs/CTOs expect fewer engineers needed; 26% actually plan to hire more.

↳ 🎯 𝗦𝗸𝗶𝗹𝗹𝘀 𝗮𝗿𝗲 𝘀𝗵𝗶𝗳𝘁𝗶𝗻𝗴 𝘂𝗽𝘄𝗮𝗿𝗱 — 73% report changed hiring priorities, focusing on high-level skills like system design over specific languages.

↳ 🌱 𝗙𝗼𝗹𝗹𝗼𝘄 𝘁𝗵𝗲 𝗮𝗱𝗼𝗽𝘁𝗶𝗼𝗻 𝗽𝗮𝘁𝗵 — Successful teams progress through: Explore (individual experimentation), Embrace (team practices), and Empower (expanding scope).

What do you think about the above? Is anything surprising? Let me know where you stand on these topics!

Also, you can find the full free report in the comments 👇

Just made a search on Google and everything above the fold was an ad.

I don't know how often it happens, but it surely felt like crap. Especially because it was a simple brand search, and you see results like "try this instead".

It would be a lot harder for AI to disrupt search if search did not sabotage itself like this.

How do you build psychologically safe teams? 🛡️

This week on the podcast I had an eye-opening conversation with Meg Adams, Senior Director of Engineering at The New York Times, about the neuroscience of leadership and creating psychological safety in engineering teams.

The problem with these topics is that they always risk staying fluffy and high-level, but Meg instead was super practical and provided plenty of examples. 
 
Here are a few things I learned:

↳ 🧠 𝗧𝗵𝗲 𝗦𝗖𝗔𝗥𝗙 𝗺𝗼𝗱𝗲𝗹 — our brains respond to social situations as if they were physical threats. The five key domains are Status, Certainty, Autonomy, Relatedness, and Fairness. When threatened, we lose cognitive capacity for creative problem solving.

↳ 🎯 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 𝗻𝗲𝗲𝗱 𝗰𝗲𝗿𝘁𝗮𝗶𝗻𝘁𝘆 𝗮𝗻𝗱 𝗮𝘂𝘁𝗼𝗻𝗼𝗺𝘆 — engineers are particularly sensitive to knowing where the goalpost is and having control over their time and approach. Most team practices (e.g. code reviews), when handled poorly can trigger status and autonomy threats.

↳ 🗣️ 𝗔𝗰𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝘁𝗵𝗲 𝘁𝗵𝗿𝗲𝗮𝘁 𝘀𝘁𝗮𝘁𝗲 — when you can't provide certainty (like during layoff rumors), just acknowledge the uncertainty. Saying "I don't have information to share right now" still provides some certainty about the process.

↳ 🤝 𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴 𝗯𝗲𝗮𝘁𝘀 𝗽𝗿𝗼𝗰𝗲𝘀𝘀 — cultural change happens when leaders embody good behaviors in real situations, not through abstract processes or documents. The most powerful moments come from being part of a team and demonstrating these principles.

↳ 🚨 𝗠𝗮𝗻𝗮𝗴𝗲𝗿𝘀 𝗮𝗿𝗲 𝗺𝗼𝗿𝗲 𝗮𝘁 𝗿𝗶𝘀𝗸 — individual contributors have more automatic relatedness from their team. Managers have at once 1) larger surface area for triggers, and 2) rarely anyone taking care of them.

You can find the full episode in the comments!

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