AI Agent Architecture Articles: Memory, Tools, Orchestration
Technical articles on AI agent architecture, orchestration patterns, memory boundaries, tool execution, state management, retrieval, and control-plane design.
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LLM, RAG, AI Agents, and MCP: What Each Term MeansA technical foundation for distinguishing LLMs, RAG, AI agents, and MCP
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LLM Agent Memory Architecture: Types, Lifecycle, and EvaluationA systems model for working state, persistent memory, functional memory roles, and lifecycle operations
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Tool-Using LLMs: Model-Led vs. Orchestrator-Led ExecutionA decision on where orchestration and policy enforcement live (model-led vs orchestrator-led)
Core articles
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When AI Systems Optimize Against the User’s Real GoalHow competing system objectives can produce acceptable outputs without completing the user’s actual task.
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LLM, RAG, AI Agents, and MCP: What Each Term MeansA technically precise explanation of LLMs, retrieval-augmented generation, AI agents, and the Model Context Protoco...
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LLM Agent Memory Architecture: Types, Lifecycle, and EvaluationA vendor-agnostic systems model for LLM agent memory types, working state, persistent memory, representation and st...
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Parallel Reasoning in Autoregressive LLMs: An Orchestration PatternWhy multi-path reasoning around standard autoregressive LLMs usually depends on inference-time branching, evaluatio...
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Tool-Using LLMs: Model-Led vs. Orchestrator-Led ExecutionA control-plane placement comparison for tool-using LLM systems, covering reliability, observability, latency, cost...
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LLM Memory vs. Context: 5 Architecture BoundariesA vendor-agnostic model of five boundaries that separate stored state from model-visible context: invocation, persi...
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Human vs. GenAI Capabilities: 22 LLM Gaps and Engineering ControlsA 22-row architecture map that turns common LLM capability gaps into external controls, implementation patterns, an...
Section resources
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About this section About this section
Focus
- Orchestration patterns (control-flow mechanisms) — where control flow lives and how workflows are sequenced.
- State & lifecycle management — what persists across steps and boundaries (session/thread/run), what resets, and when.
- Tool invocation lifecycle — selection, authorization/enforcement, validation, error handling, retries, and egress constraints.
- Write paths — where and how the system can persist changes to external systems.
Terminology
- Orchestrator: the component that owns control flow (decides next action/tool call) and enforces policy.
- Model-led: the model proposes next actions/tool calls within constraints enforced by the orchestrator.