Architecture components for production AI systems: agents, memory, orchestration, retrieval, tools, and evals.
Delegation, coordination, state transitions, and typed execution boundaries for autonomous workflows.
Episodic memory, semantic retrieval, compression, persistence, and replayable context for stateful agents.
Durable execution, retries, branching, checkpoints, and human-in-the-loop gates for production AI flows.
Embedding pipelines, hybrid search, metadata filters, reranking, and frozen eval sets for RAG systems.
MCP integrations, typed tools, routing schemas, permission boundaries, and protocol adapters.
Regression suites, adversarial cases, trace review, cost tracking, and production-readiness evidence.
Semantically focused pages connecting concepts, projects, and technical writing.
Architecture patterns for coordinating multiple AI agents with explicit roles, state, tools, and failure handling.
Routing, delegation, checkpoints, and supervision patterns for production-grade agent workflows.
Durable workflow design for AI systems that need branching, retries, persistence, and auditability.
Patterns for AI workflows that survive partial failure and remain inspectable after execution.
Memory layers for AI systems: semantic recall, episodic traces, compression, persistence, and retrieval evaluation.
Model Context Protocol integrations, connector identity, tool boundaries, and agent-facing operational surfaces.
Hybrid search, embedding pipelines, metadata strategy, reranking, and evaluation for production RAG systems.