Agent Engineering
Skills, slash commands, hooks, MCP, harnesses, and the multi-agent systems built on top of them — explained from first principles, by the Noddle Deck team.
Agent Engineering
Agent Skills, Explained: Teach Your AI Agent Like You'd Onboard an Engineer
Skills package expertise so an agent can load it only when the task calls for it. Here's the anatomy, the lifecycle, and the mistakes that make skills invisible to the agent that should be using them.
Agent Engineering
Slash Commands: Reusable Prompts You Can Ship
A slash command turns a prompt you'd otherwise retype into a versioned, shareable action — the difference between a good prompt and a piece of team tooling.
Agent Engineering
Hooks: Deterministic Guardrails for Non-Deterministic Agents
Hooks run outside the model's judgment entirely — deterministic checks that fire before or after a tool call so the same rule holds every single time, not just most of the time.
Agent Engineering
MCP: The USB Port for AI Agents
The Model Context Protocol gives agents one standard way to talk to any tool or data source, instead of a bespoke integration for every model-and-service pair.
Agent Engineering
The Agent Harness: Everything Around the Model
The model is one component. The harness — the loop, the tool router, the context manager, the permission system — is what actually turns it into a working agent.
Agent Engineering
Multi-Agent Systems: Orchestrating a Team of AIs
Splitting a task across a lead agent and several subagents can beat one big context window — if you get the handoffs and the shared state right.
Agent Engineering
Loop Engineering: Agents That Run While You Sleep
Long-running agent loops need their own discipline — checkpointing, budget limits, and exit conditions — or they either stall out or burn through your quota unattended.