Stop Writing Better Prompts. Start Reviewing AI Code
Stop chasing the perfect prompt. Start with a draft, review it like code, and iterate with constraints until the output matches your actual design.
Data-Engineering
The `with` Statement Is More Powerful Than You Think
You use with open() every day. Here’s how to build your own context managers — and why they’ll save you from leaked connections and forgotten cleanup.
Solutions Looking for Problems: A Field Guide to Fake Disruption
Project Elephant didn’t exist. But you’ve probably worked on it.
Tired of Passing 10 Parameters to Your Functions: Go For The ApplicationContext Pattern for Data Pipelines
Your pipeline functions don’t need tons of parameters. Here’s a simple pattern to clean up your Databricks and Snowflake code.
Stop Using Dicts for Config — Use Pydantic Instead
Load your YAML/TOML config files into validated, typed Python objects. No more silent typos, no more runtime surprises.
Why I'm Writing About Clean Python and AI-Assisted Coding
I spent 10 years as a SAP BODS consultant. It taught me a lot — especially about the frustration of working inside a black box. When something broke, I often couldn’t dig into the internals. I had to work around limitations rather than through them. The tool did the job, but I never felt like I truly understood my own pipelines end to end. And let’s just say that debugging a data flow through a GUI with cryptic error messages at 2am — while the documentation loads slower than your will to live — builds character. A lot of character. If you’ve ever opened a support ticket hoping for answers and received “working as designed,” you know exactly what I mean. ...