Articles
How to Optimize AI Agent Cost and Latency
Where agent cost and latency actually come from, the concrete levers to pull, and how to measure before you optimize the wrong thing.
Memory for AI Agents
How AI agents remember beyond the context window: working memory, long-term stores, episodic vs semantic memory, and the pitfalls.
The Agentic Loop, Explained
How the model-decides, harness-executes, context-accumulates cycle actually works, where it breaks, and how to bound it in production.
Guardrails and Safety for AI Agents
Why agents need more than a chatbot's safety filter, and how to layer input validation, scoping, approval, and sandboxing.
How to Write Your First Agent Skill
A practical, accurate walkthrough of Agent Skills: the SKILL.md format, why the description is the trigger, and how to test one before you ship it.
How to Evaluate and Test Your Prompts
A practical guide to building prompt test sets, choosing grading methods, gating CI, and catching regressions when you swap models.
Prompt Templates and Variables
Stop copy-pasting prompts. Learn how to template instructions, typed variable slots, and untrusted-data sections you can version, test, and secure.
Chain-of-Thought and Advanced Reasoning Prompting Techniques
How chain-of-thought, self-consistency, and decomposition prompting work — and when they're obsolete on reasoning models.
Multi-Agent Systems Explained
A team of agents is a scaling tool, not an upgrade. The two situations where multiple agents beat one, when a single agent wins, and how to decide.
RAG vs Tools vs Long Context
Three ways to give a model knowledge — and the obvious one is often wrong. When to use long context, RAG, or tools, plus the 2026 shift to agentic retrieval.