Hey, Luca here, welcome to a weekly edition of the💡Monday Ideas💡 from Refactoring!
I am repeating last week’s experiment of adding the best articles I have read last week, other than the classic weekly ideas. Let me know if you like it!
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Secure your mobile app and the APIs it interacts with
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In February we published a great guide by the one and only Pat Kua about the various CTO Archetypes. Last year we also published a similar one about Engineering Managers.
I like archetype articles, because I believe they are useful for many things:
1) Clarify expectations
Two people with the same title can have radically different responsibilities. Naming the archetype you’re operating in helps make explicit where you’re spending time and what you’re optimizing for.
2) Sense how the role evolves over time
Archetypes are not a personality quiz, also because people, orgs, and roles change over time. They are most useful as point-in-time references. E.g. as a company grows from startup to international brand, the CTO role might shift from Startup to Scale-Up to M&A. The same applies individually: a Group CTO might leave to found a company, becoming a Founder CTO.
3) Identify signals when hiring
Strong candidates use interviews to both sense and shape the role. Archetypes help you understand a company’s situation and spot mismatches early. If the role doesn’t align with your strengths, the model gives you language to say: “This is a valid role, but not the one I’m best suited for.”
4) Plan intentional career growth
Many tech leaders excel at one company but struggle at another. Archetypes explain why: they help you reflect on where your strengths play best and what you’d need to develop to grow into other archetypes.
At some point I asked him what his ideal product team looked like — I mean the atomic unit of <10 people building a product together.
His answer focused on a single quality: speed of learning. The fundamental question the team needs to ask all the time is: what’s the fastest way to get the information needed to make the next decision?
Granted, simply asking the question is not enough, because there exist plenty of *bad answers.*To get good answers, Rob believes the team needs three factors:
🎯 Clear business understanding — every engineer needs to understand what the business is trying to achieve and why
⚡ Rapid experimentation mindset — willingness to test hypotheses quickly rather than debate endlessly
🤝 High trust environment — team members can admit when they’re stuck and ask for help without fear. Build the trust needed for anyone to be able to raise their hand and say “I have no idea how to do this”.
I finally caught up with this viral imaginary report from 2028, that was published last month. Very useful to read to reflect on the second and third order effects of AI. It was a good test for my own beliefs: which predictions do I find reasonable? Which dubious?
Tale as old as time — we most often reward complexity as a display of brilliance, and ignore simplicity. Engineers who over-build get a compelling narrative, while the ones who ship the simplest (and thus the best!) thing get… nothing.
I am really enjoying Rands’ blog lately. It has become a blend of classic Rands’ management advice and occasional tales from his own AI experiments. This is one of the latter. I also love how practical he explains these — there are code snippets!
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