AI Skills & Capabilities
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Agent Skills: Reusable Capability Packages
What a 'skill' actually is: a folder with instructions, scripts, and assets that an agent loads on demand.
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Context Engineering for Long-Running Agents
Techniques that keep multi-turn agents from degrading: compaction, structured notes, and sub-agent isolation.
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Tool Calling: Making Agents Act
How agents choose and invoke external functions reliably — schema design, argument validation, and error recovery.
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Evaluating Agent Behavior
Build graders that measure agent output before you ship — rubrics, golden sets, and the code-vs-model tradeoff.
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Retrieval That Actually Helps
Why most retrieval pipelines underperform, and the fixes that matter: chunking, hybrid search, reranking, citation discipline.
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Multi-Agent Orchestration Patterns
When to split work across agents, four coordination topologies, and why most tasks should stay single-agent.
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Guardrails and Safe Defaults
Layered defenses for agent actions: input screening, permission gating, sandboxing, and designing irreversible switches to fail closed.
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Structured Output Patterns
Get machine-parseable results every time: explicit contracts, enum discipline, the NULL affordance, and validation-repair loops.
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MCP: Extending Agents with Tools
How Model Context Protocol standardizes tool integration — servers, transports, and when it beats writing your own glue.
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Designing Reliable Agent Workflows
Make long agent tasks survive reality: idempotency, checkpoints, resumability, and explicit failure states.