Introduction I've been seeing more developers say that Codex has become easier to use, more cost-effective, or simply a better fit for some workflows than it used to be. This is not a "Claude Code is bad, everyone should switch" article. I still use Claude Code at work, and if cost were less of a factor in my personal setup, I would probably be using both more actively. If you're already comfort
Fixed-length chunking requires no external services, yet semantic chunking absolutely needs an Embedding API — why? The core idea of semantic chunking is to split text at semantic boundaries. Determining whether "two pieces of text belong to the same topic" requires converting text into vectors and computing similarity — that's exactly what the Embedding API does. Dimension Fixed-Length / Recur
Hello everyone! I wanted to write this article to share my experience with agentic coding without Claude and Codex, I started dabbling with agentic coding a few months ago when Claude had decent limits on the 20$ plan, You prompt the agent: I want e2e tests, and it will study the codebase and implement them. When I've started hitting limits on Claude code, and this is not a secret that they reduc
Why Does Switching Embedding Models Make Such a Huge Difference? In the first four articles, we built the RAG pipeline, tuned parameters, and mastered chunking strategies. But there's one question we haven't dived into: After your documents are chunked, how do they become vectors? This process is called Embedding. It transforms human-readable text into machine-computable vectors. The choice of E