I Cut Claude API Costs by 50% Using a Self-Modifying Agentic System My Claude API bill hit $340 in a single month. The system I was running was doing what it was supposed to do—processing thousands of tasks per day, generating content, classifying inputs, drafting responses—but the cost curve was pointing straight up and I had no clear way to bend it without sacrificing quality. So I built something that fights back: a self-modifying agentic loop that analyzes each incoming task, routes it to the cheapest model capable of handling it, compresses the context window before every call, and caches repeated prompt structures using Anthropic’s native caching API. The result was a 50% reduction in monthly API spend with zero degradation in output quality on the tasks that mattered. ...

How to Build Your First AI Agent with Claude API: Step-by-Step Guide Most developers build their first AI agent the hard way: they wire up a chat loop, bolt on some tools, and watch it spiral into an uncontrollable mess of nested callbacks and race conditions. Building an agentic AI that actually works in production requires a different mental model from day one. This guide walks you through exactly that, using the Claude API, plain Python, and (optionally) LangChain to build something you can deploy and extend. ...

Claude API vs OpenAI API: Real Cost and Performance Breakdown for Developers Picking the wrong LLM API in production can cost you thousands of dollars a month. Claude API pricing and OpenAI API pricing look similar on paper, but the actual LLM API cost you’ll pay depends heavily on your token mix, context size, and throughput. This breakdown cuts through the marketing noise and gives you the numbers you actually need to make the call. ...