Happy New Month, dear reader! We made it to a new month. Another month, another chance to try to do better.

Day 47/60 system design question shares on breaking apart a monolithic app by extracting a Returns service without resorting to a risky rewrite. The focus of the question is on architectural thinking, such as using patterns like the Strangler Fig to migrate functionality incrementally. Making safe, incremental changes that minimise business risk while gradually improving scalability, maintainability, and team autonomy.

Performance Has Layers: Optimisation is about removing bottlenecks across every layer of a system, rather than finding a single magical fix for all. The article details how owning the stack from hardware to networking software allows engineers to continuously identify and optimise these layers in concert, a feat that would be difficult to achieve when responsibility is fragmented across multiple vendors.

Open Source Summit, Linus Torvalds, Creator of Linux & Git with Dirk Hohndel, Founder, DH Consulting: Torvalds views AI as an evolution of programming tools, comparing it to compilers. AI improves developer productivity but does not replace the need for deep technical understanding. In his view, AI excels at generating prototypes and disposable code, but building and maintaining complex software over decades still requires developers who understand the systems beneath the AI-generated output.

The Rise of Proof-Based Hiring: Hiring is shifting toward evaluating verifiable evidence of candidates’ abilities rather than claims about them. Tangible proof like open source contributions, technical writing and case studies. In the age of AI, the strongest candidates will be those who can consistently demonstrate impact and document how they think, build, and solve problems, making authenticity and a public body of work more valuable than credentials or self-reported experience alone.

The Architecture Behind 10,000 API Providers: this article shares how the author was able to build and scale a searchable catalog og over 10,000 APi providers by combining three key components:

• An open metadata standard

• Machine-readable catalogue

• Automation tooling

Instead of treating each API as an isolated resource, every provider is represented by a GitHub repository containing an apis.yml file that describes the provider, its APIs and other attributes. The value lies in creating a shared knowledge base that makes the API ecosystem searchable and collaborative, with GitHub as the version control.

5 Lessons at 50: Murat shares lessons on mindset. He warns against letting fear stifle your curiosity and reminds us that we, as people, are more adaptable than we give ourselves credit for. He also emphasises the importance of investing in relationships, as they often outlast professional achievements.

The “I don’t know, Claude wrote this” pandemic: The biggest risk of AI-assisted software development is that developers have stopped taking ownership of what they ship. The healthy way is to use AI to accelerate implementation while the engineer still understands, reviews and validates every change. In an AI-first world, the competitive advantage is no longer writing code quickly but exercising sound engineering judgment and remaining accountable for every line that reaches production.

What the Top 1% of Engineering Teams Do Differently with AI: Competitive teams use AI as a system-wide capability that transforms the software development lifecycle, allowing engineers to spend more time on product thinking, design, and decision-making while AI handles implementation.

The word of the day is fubsy. Fubsy means short and stocky with a warm, affectionate quality that makes it endearing.

Example in a sentence:
A row of fubsy, round cacti lined the windowsill, looking entirely too friendly to prick anyone.

I am making my grand departure into the unknown.

Take care of yourself!

Until the next fortnight, my treasured reader, go forth, and may the odds be ever in your favour! 👏 🤖 ✊ ☠️ 🏹 🪖

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