AI Agents on Uni Matrix Zero

Agent Memory Architecture: Working, Episodic, Semantic and Procedural Memory

Wed, 12 Aug 2026 00:00:00 +0000

An agent memory architecture determines more than where conversation history is stored. It decides which observations become memories, what type they become, who may retrieve them, when they expire and whether they can influence an action without being mistaken for current truth.

AI Agent Architecture: Models, Memory, Tools, State and Control

Wed, 12 Aug 2026 00:00:00 +0000

An AI agent is not just an LLM with tool definitions. A production agent is a runtime system that assembles context, chooses actions, interacts with external services, preserves state and proves what happened.

Generative AI Production Architecture

Wed, 12 Aug 2026 00:00:00 +0000

A generative AI production architecture defines more than which model receives a prompt. It determines where truth lives, how decisions become actions, which intermediate states remain inspectable and what must happen before a generated result becomes part of the system.

Graph RAG vs. Agent Memory vs. World State

Wed, 12 Aug 2026 00:00:00 +0000

Graph RAG, agent memory and world state are often grouped under “giving the model more context.” That description is too broad for architecture. They solve different problems and carry different levels of authority.

Knowledge Graphs as the Control Plane for AI Agents

Wed, 12 Aug 2026 00:00:00 +0000

An AI agent needs more than retrieved paragraphs. It needs an inspectable map of the entities it may act on, how they relate, which sources support a claim and which transitions are permitted. A knowledge graph can provide that semantic control plane.

Stateful AI Agents: Why Memory Is Not State

Wed, 12 Aug 2026 00:00:00 +0000

A stateful AI agent can continue work across steps, interruptions and sessions. That does not mean the model itself “has state.” Reliable statefulness comes from external persistence and explicit transition rules around the model.

The Production Black Box: Why Generative Models Should Be Operators, Not Systems

Tue, 11 Aug 2026 00:00:00 +0000

Generative models are following the same product trajectory in two different media.

Language models moved from token prediction to chat, reasoning, agents and finally the promise to complete an entire task. Video models moved from frames to clips, synchronized audio, consistent characters, camera direction and now complete multi-shot sequences.

Each step is useful. Each step also moves more of the production process inside one probabilistic model call.

Agentic Workflows vs. Production Pipelines

Sat, 22 Jun 2024 00:00:00 +0000

The choice is not “pipeline or agent.” Reliable AI systems usually combine deterministic production pipelines with a few bounded model-driven decisions. The architectural task is deciding where variability is valuable and where it becomes operational risk.

Integrating AI Agents with Existing Systems: MCP, Skills and Cowork

Sat, 22 Jun 2024 00:00:00 +0000

Integrating an AI agent with an existing system used to mean writing a function for every API call. That remains necessary, but it is no longer the whole architecture. Modern agent environments separate connectivity, working instructions, execution context and operational control.

MCP tells an agent what external capabilities exist. Skills teach it how to perform recurring work. Cowork systems provide a persistent place to combine files, tools and human feedback. The coordinator preserves process sovereignty: it decides which proposed step becomes part of the accepted process.