AI Agent & Automation Workflows

Master skill for building production-grade agentic products — software systems where part of the process is dynamically directed by LLMs within deterministic architecture with explicit trust boundaries. Use this skill whenever the user mentions building an agent, agentic product, agentic workflow, AI agent, multi-agent system, agent loop, agent harness, or asks how to design, architect, ship, or harden any system with LLM-driven decision-making. Also use when they reference frameworks like LangGraph, CrewAI, OpenAI Agents SDK, Claude Agent SDK, Pydantic AI, AutoGen, or when they want to add tools, memory, evals, or human-in-the-loop to an LLM system. This is the entry point — it routes to specialized sub-skills for architecture, context engineering, harness, tools/MCP, memory, durable execution, evals, framework choice, production readiness, and antipattern review.

Review existing agentic code, designs, or plans through the lens of the 12 canonical antipatterns. Diagnose what's likely to fail in production. Use whenever the user asks you to review their agent code, asks "what's wrong with this design," is debugging mysterious failures, or wants a second opinion on an architecture. Also use proactively when you notice any of the 12 antipatterns in a conversation, even if the user didn't ask for review.

Make agents survive crashes, timeouts, restarts, and human waits — using Temporal, Inngest, Restate, or LangGraph's checkpointer. Cover the Workflow + Activity pattern, pause/resume semantics, retry policies, and when to retrofit (answer: before your first long-running agent goes to production). Use whenever the user mentions long-running agents, multi-hour tasks, pause/resume, retry on failure, agent crashing mid-flight, state persistence, Temporal, Inngest, Restate, or asks how to handle reliability over hours/days.

Choose the right agentic framework — LangGraph, OpenAI Agents SDK, Claude Agent SDK, CrewAI, Pydantic AI, AutoGen/AG2, LlamaIndex Workflows, Semantic Kernel, Mastra, DSPy, mcp-agent — based on the team's dominant constraint, not hype. Use whenever the user asks "which framework should I use," compares any two of these, hits limits with their current framework, or is starting a new project and needs to pick the stack.

Five-layer memory architecture: where each fact lives, how layers interact, when to promote…

Comprehensive pre-deployment validation ensuring code is production-ready. Runs complete audit pipeline, performance benchmarks, security scan, documentation check, and generates deployment checklist.

The AgenticProduct paved road — how to stand up and wire the family's reference implementations so each surface of the standard is satisfied out of the box. Covers AgenticMind (knowledge & memory over MCP), AgenticOps (runtime & fleet operations), AgenticPerformance/APL (evals & observability over OpenTelemetry), AgenticGateway (model & cost plane — one OpenAI-compatible key, eval-sourced routing, cost circuit breakers), and AgenticAssurance/AAL (red-team security assurance). Use whenever the user asks "what should I actually use to build this", wants the batteries-included stack, wants to install or wire our tools, wants conformance without assembling every surface by hand, or mentions AgenticMind / AgenticOps / AgenticPerformance / AgenticGateway / AgenticAssurance. The standard stays vendor-neutral (Principle 2) — this is the recommended paved road, not a mandate; bring-your-own is always fine.

Design tenant isolation for a multi-tenant agentic product so one customer can never read, retrieve, remember, or be billed for another's data. Covers the three isolation models (pooled + row-level, bridge, silo), the agent-specific leakage paths most teams miss (cross-tenant retrieval, memory, cache, trace, and model-supplied tenantid), where tenantid binds into the Agent Contract / permissions / memory / tools / evals, and the mandatory cross-tenant leakage eval. Use whenever the user mentions multi-tenant, multi-tenancy, tenant isolation, B2B SaaS agent, per-customer data, row-level security / RLS, data residency, "can tenant A see tenant B's data," noisy neighbor, or namespacing memory/knowledge per customer.

Design tools for agents — function/tool definitions, MCP (Model Context Protocol) servers, tool routing when there are many tools, structured outputs, and the rules of thumb that prevent tool selection failures. Use whenever the user is adding tools/functions to an agent, integrating external systems, building or consuming MCP servers, hitting "the agent picks the wrong tool" failures, designing function signatures, choosing between MCP and direct function calling, or wondering how many tools is too many.