Laytoun' thoughts!

Have you ever sat through watching a 90-minute political interview, knowing there were important claims buried in there somewhere, but the idea of scrubbing back and forth to find them made you want to close the tab?!

I've been working on MCP apps for a while now, and I'm lucky enough to have shipped two Spotify production apps running inside ChatGPT and Claude!

The last time I did a proper JEP-by-JEP writeup, records were the shiny new preview toy and we were all arguing about whether switch expressions would ever feel natural (they do).

In part 1, we wired a fully local coding agent: Gemma 4 served by Docker Model Runner on the host, driving a cagent-based agent inside a Docker Sandbox microVM, with a default-deny network policy between them.

It's been a while since I wrote anything here.

When I published the original series in November 2025, I was happy with where the system landed.

We finally got first drop of snow this week in Stockholm.

In the first part, we explored the production challenges of RAG systems: latency, reliability, cost, quality, and observability.

I've been quiet on this blog for a while now.

When you think about building machine learning apps, Java is not the first language that comes to mind, probably not even in the top 3 or 5!

Needless to say how important monitoring and observability is, especially in a cloud native, distributed world!

If you've been following the news lately in the Java ecosystem (aside from Java 28th anniversary), you should've heard of CRaC.

Hello dear reader 👋 Let me set come context some context first before diving into how I set up my home office.

When it comes to building CLI apps, Java is not your first ( not even among the top 3) choice that comes to mind.

This is the fourth and last post in the blog post series I wrote covering the features that has been added to java 14, released just a couple of days back.