AI Coding Dictionary: A Vocabulary for Agent Engineering
AI Hero publishes an AI coding dictionary that condenses the working vocabulary of agent engineering into terse entries. Instead of merely defining terms, it draws the conceptual lines that matter in practice: parametric vs contextual knowledge, the stateless model vs the stateful harness, input/output/cache tokens, and handoff mechanisms like compaction and handoff artifacts. It also introduces a few useful distinctions of its own — progressive disclosure as a way to load context on demand, Spec and Ticket as the building blocks of multi-session work, and DX/AX as separate measures of how well an environment serves humans and agents. Each definition is kept to a sentence or two, making the dictionary a useful reference for engineers debugging context-window waste, permission modes, or agent memory. For teams standardizing on terms like MCP, AGENTS.md, or subagents, this is a solid shared glossary. The piece is a lead magnet for AI Hero's newsletter, so treat it as a reference rather than a deep investigation.