Articles on data normalization, API design, vibe coding, and building reliable integrations.
Use APIs for the hard parts, vibe code the glue. Why AI-generated code fails on complex problems and how to make it reliable.
Don’t let AI write the normalization layer. Go two layers deep: data APIs, then normalizer APIs. A real example combining calendar + events.
Use a format converter API instead of vibe-coding XML→JSON, Excel→PDF, and the rest. One pipe, many formats in and out.
Why schemas differ across sources, why canonical models matter, and how normalization APIs help you build reliable integrations.
What is a data combiner? Why merging APIs is hard, how schema conflicts arise, and how normalization APIs help.
Best practices for validating API request and response payloads in production systems.
Why you need a JSON Schema Validator, Diff Checker, and Payload Consistency Checker to catch API and schema changes before they catch you.