Imagine hiring a brilliant assistant, handing them a 200-page manual, and asking a question. They read all 200 pages, answer, and then promptly forget everything. Next question? They read all 200 pages again. And you pay them by the page. That’s roughly how large language models (LLMs) work by default. Prompt caching is the fix. […]
Read More →Your agentic app just ran a search. The tool returned 500 results as JSON. Your agent appended all of it and fired off an API call — 45,000 tokens to answer a question that needed maybe 4,500. Tejas Manohar, a senior engineer at Netflix, hit this problem every day. He was running out of tokens […]
Read More →Claude Code isn’t a chatbot that suggests code. It’s an autonomous agent that inhabits your terminal, reads your entire codebase, runs commands, edits files, commits changes, and iterates until the job is done — all from a single natural language instruction. Table of contents The Fundamental Shift: From Autocomplete to Autonomous Agent To understand what […]
Read More →The Model Context Protocol (MCP) is an emerging approach to managing how language models interact with and understand context. In this blog post, I’ll explain what the Model Context Protocol is, why it matters, and how it’s shaping the future of AI interactions. What is the Model Context Protocol?The Model Context Protocol is a standardized […]
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