How I Built an API That Cuts LLM Token Costs by 11-22%

<p>GPT-5.4 shipped on March 5. Seven weeks later, on April 23, 2026, OpenAI released GPT-5.5 — and the pace alone tells you something about where this race is headed. This isn't

<h2> Cursor and Windsurf are not AI coding tools. They're slot machines wrapped in a dark theme. Both exploits Claude Opus 4.7's broken tokenizer—which silently inflates your

<p>I run a lot of RAG pipelines. And for a while, I was doing what most people do: retrieve the top-k documents, concatenate them into the context, and ship the whole thing to the

<p>Every token you send to an LLM costs money and eats into your context window. If you're stuffing structured data - JSON arrays, database records, API responses - into your

<p>How it works:</p> <p>Request arrives at an OpenAI-compatible endpoint<br /> Classifier detects task type + complexity<br /> Adaptive router picks the highest-scoring model for

<p>In my previous post, "<a href="https://zenn.dev/bokuwalily/articles/hook-script-macos-traps" rel="noopener noreferrer">Writing hook scripts without stepping on macOS

<!-- SC_OFF --><div class="md"><p>I run local models for most tasks, but there are still cases where I fall back to OpenAI/Anthropic APIs (complex reasoning, long context, etc.).

<h2> The hidden tax in your AI pipeline </h2> <p>If you're building with GPT or Claude, you’ve probably done this:</p> <ul> <li><p>Call an API</p></li> <li><p>Get a big JSON