Context Pruning and Relevance Maintenance Context pruning is how long-running agents stay relevant. Without pruning, context grows until it becomes expensive, slow, and misleading. The goal is to keep the minimal state needed to complete tasks while removing noise and outdated assumptions. Pruning Techniques | Technique | How It Works | Best For | |—|—|—| […]

State Management and Serialization of Agent Context Agents turn AI from a single-turn responder into a system that can plan, act, and recover. The price of that capability is state. Without state management, an agent is forgetful in the worst way: it repeats tool calls, loses track of commitments, redoes work, and fails to explain […]

Tool Selection Policies and Routing Logic Modern agents are not “just a model that talks.” They are decision systems that translate intent into actions across a toolchain: search, retrieval, databases, spreadsheets, ticketing systems, payment rails, code runners, and internal services. The most important technical question is not whether a model can call tools, but whether […]