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  1. Every coding agent I use is opaque in the same way.

  2. My last post was about companies discovering their AI bills and installing caps.

  3. Last month I ended my Fable 5 post saying I was seeing more and more content about companies starting to look at their AI costs.

  4. I’ve been experimenting with pointing LLMs at databases through MCP servers and asking them questions.

  5. Trying Out Fable 5

    I like to redesign this blog every once in a while, and this time it lined up with Anthropic releasing Fable 5, their new model that sits above Opus.

  6. I have become angry and disillusioned with AI.

  7. When I learned Python, the standard setup was python -m venv and pip.

  8. I built an agent for work some time ago, but the field moves fast, and I wanted to build something with the current tooling and see where things are at.

  9. I made a tiny roguelike

    Dungeon is a short turn-based roguelike that runs in your browser.

  10. Using open source tools for a while, I started wondering about the commercial side.

  11. I wanted to understand the cloud data warehouse space beyond the usual names.

  12. Games I Played in 2025

    Looking back at my Steam Replay, I touched 30 games in 2025.

  13. This post continues from Building a Generative Art System in Go, where I build the foundation for a modular generative art framework.

  14. I recently watched a video going through this article (thanks attention economy).

  15. 1.

  16. Compression setting are set and forget in most cases, if it works no reason to change it.

  17. You Might Be Using The Wrong Compression Algorithm If you work in data engineering, you’ve probably used gzip, Snappy, LZ4, or Zstandard (zstd).

  18. The Problem Too often, data engineering tasks that should be simple end up requiring heavyweight tools.

  19. Project Links GitHub: github.com/KonMam/kafka-replay-cli PyPI: pypi.org/project/kafka-replay-cli Why I Built This I wanted more hands-on Kafka experience - that’s the gist of it.

  20. A Kafka producer is the entry point for all data written to Kafka.

  21. Kafka is built for high throughput, scalability, and fault tolerance.

  22. About

    I’m a data engineer by day.

  23. Kafka routinely handles millions of messages per second on commodity hardware.