Month March 2026

Hashtag Jakarta EE #325 Welcome to issue number three hundred and twenty-five of Hashtag Jakarta EE! I am on my way home from JavaOne 2026 with a bag full of swag and a head full of inspiration and new ideas. One…

The most impactful engineering leader I ever worked with was a guy named Bill Scott who led UI engineering at PayPal. What I loved about Bill was his constant enthusiasm for new technology. He helped lead the charge to take…

Here’s Everything We Found An AgentAutopsy post — dissecting AI agent failures so you don’t have to 177. That’s how many times our decision-making agent’s context got compacted in two weeks. Claude Opus, sitting at the center of our 1-human…

Let me paint you a picture. You join a company. You ask how secrets are managed. Someone looks at their shoes. Eventually you find a .env file in a shared Google Drive folder. It has been there for three years.…

In theory, checking disk usage looks simple — just grab the percentage from df -h. But in the real world, scripts break, formats differ, and human‑readable values like 374G don’t compare cleanly. This post is about the lessons learned when…

I wanted to evaluate model-based extraction in a way that would tell me more than benchmarks alone. The scenario is building an AI recruiting agent to help match candidates to job postings. To do this, we need to ingest job…

JavaOne 2026 If I should pick one conference that has been instrumental in defining my career, it would be JavaOne. I have attended almost all editions of JavaOne since my first time in 1999 including the years it was branded…

The scenario is almost always the same, which is a data table inside a scrollable container. Every row has an action menu, a small dropdown with some options, like Edit, Duplicate, and Delete. You build it, it seems to work…

Context windows are getting huge, but token budgets are tightening. Every time your agent iterates in an autonomous loop, you’re potentially sending a massive, bloated prompt filled with conversational filler, redundant whitespace, and low-entropy “slop.” Today, I’ve merged the Prompt…

Originally published at In the last chapter, we installed NocoBase and got familiar with the interface. Now it’s time to build the skeleton of our HelpDesk system — the data model. This chapter creates two collections — Tickets and…