Weekly Dev Log 2026-W04

🗓️ This Week

• I had a long holiday during Golden Week in Japan and really enjoyed the break!
• Because of that, I didn't have as much learning time compared to last week 😂
• I made a little more progress in the SwiftUI tutorial
• It was my first time using GitHub Copilot in Xcode, and I tried using the chat feature to generate unit tests. I'd also like to gradually explore more advanced features such as custom instructions.

I also want to thank everyone who commented on my previous Weekly Dev Log 2026-W03✨

Since English is not my native language, I was honestly a bit nervous about posting in English at first. But interacting with people on this platform has been a really valuable learning experience for me.

The kind comments and discussions gave me more confidence to continue sharing my learning journey here. Thank you so much😊

📱 iOS (SwiftUI)

• Worked through the Swift tutorial and completed Section 5: "Create an Algorithm for Badges"
• Used GitHub Copilot in Xcode to generate unit tests for badge sorting logic.

🌐 Web Development

• Posted my weekly dev log on Dev.to 📝

🔐 Security (TryHackMe)

• Worked on the AI Forensics room (part of the AI Security Learning Path) on TryHackMe

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💡 Key Takeaways

• Reviewed the basics of building SwiftUI views using NavigationStack, ScrollView, and HStack
• Learned how to integrate AI-assisted code generation into the testing workflow.

TryHackMe Learning

AI Forensics

• Learned how AI/ML enhances DFIR through large-scale data processing, anomaly detection, and scalable analysis
• Explored practical AI use cases in DFIR tools, including phishing detection, malware classification, alert prioritisation, and event correlation
• Learned the difference between deterministic systems and probabilistic AI models, and why non-determinism can become a challenge in digital forensics
• Studied key AI evaluation metrics such as accuracy, precision, and recall, and learned why these metrics can be misleading when viewed in isolation
• Understood the “Garbage In, Garbage Out (GIGO)” principle and how low-quality training data can lead to unreliable AI outputs
• Learned that AI can accelerate DFIR workflows, but human oversight and validation are still essential in forensic investigations

🚀 Next Week

• Continue working on the badge algorithm (Section 6) in the SwiftUI tutorial
• Continue posting small articles on Dev.to
• Continue working on the AI Security Learning Path

🌈 Goals for This Year

📱 iOS (SwiftUI)

• Build a solid foundation in SwiftUI and create at least one iOS app

🌐 Web Development

• Continue posting learning logs on Dev.to and eventually turn them into a portfolio site using React Router v7

🔐 Security (TryHackMe)

• Keep learning cybersecurity on TryHackMe