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As LLM applications grow more complex, inference cost and latency become increasingly important. A single request can contain thousands or even millions of tokens from system instructions, conversation history, retrieved documents, tool definitions, and user input. Reprocessing the same information again and again wastes both time and compute. Caching helps avoid this repeated work. But […]
OpenCode is open source and works with any model, but those are no longer its most interesting features. Model choice is table stakes. What sets OpenCode apart is its architecture, and the trade-offs that come with it, especially if you are coming from Claude Code. In this article, we look at what OpenCode is, what makes its architecture different, what
OpenCode Explained: The Open-Source AI Coding Agent Read More »
If you have ever tried downloading a local LLM, you have probably seen model names that look like this: Qwen3.8-27B-A3B-It-2507-gguf-q2ks-mixed-AutoRound At first, it looks like meaningless technical shorthand. It isn’t! Every part of that name tells you something about the model: how large it is, how it is built, how much of it is used at a time, how
AI agents are everywhere right now. You hear terms like tool calling, agent loops, MCP, guardrails thrown around as if its common language… it isn’t! But that is about to change. Agentic AI isn’t nearly as complicated as it sounds once you understand the few core ideas that actually matter. Here are 10 agentic AI concepts
10 Essential Agentic AI Concepts Explained Simply Read More »
I have written enough specs for Claude Code now to have hit the failure mode nobody warns you about. The spec was fine. The plan was fine. Claude worked through the tasks, ran the test suite, and reported everything passing. I looked at the diff properly the next morning and found it had converted a
Spec-Driven Development with Claude Code: Writing Bulletproof Specs Read More »
Claude now marks AI-generated content. But it does not mark everything the same way. Anthropic currently uses embedded watermarks for text and signed C2PA provenance metadata for supported files. Code sits somewhere in between: it is still text, but its structure gives the watermark fewer places to work. I went into detail about Claude’s watermarks
How to Remove Claude Watermarks from Text, Code, and Files Read More »
Ever wondered how ChatGPT, Gemini, and other chat interfaces generate PDFs, PowerPoints, and more when all they have under the hood is an LLM? The trick isn’t a smarter model. It’s something simpler: skills which are instructions an agent loads only when needed. Next, let’s explore how skills work using LangChain and how they can make
You have probably heard by now. Claude Code burns through usage limits! But most of us live in the web app… distant from the terminal app, around which the buzz is about. Maybe that was enough to make you curious. Maybe you already knew exactly what it was and just want it running on your
How to Install Claude Code: A Step-by-Step Guide Read More »
The real skill isn’t getting AI to answers! But to do so in a manner that fits our budgets and fulfils our requirements. It’s guiding it with clear context and turning its output into useful action. This list is built around a simpler idea. Instead of searching through thousands of skills, you start with the
I used to think Claude Code best practices were a matter of taste. Plan mode or not. Long CLAUDE.md or short. Pick what suits you, move on. Then Anthropic scored roughly 400k sessions from over 235k users against hard evidence of success. Tests passing, commits landing, users confirming they got what they asked for. Taste
Claude Code Best Practices: 3 Lessons from 400,000 Sessions Read More »
