---
title: "Agentic AI with Sruja"
summary: "Model agent systems, RAG pipelines, and governance with Sruja DSL."
difficulty: "advanced"
topic: "ai"
description: "A practical course on architecting agentic AI systems using Sruja: foundations, RAG, orchestration, and production governance."
estimatedTime: "3–4 hours"
---

# Agentic AI with Sruja

Learn to design agent-based AI systems with clear boundaries, interfaces, and governance using Sruja DSL.

**Learning objectives**

- Model orchestration, tools, and memory in `.sruja`.
- Use **`sruja agent loop`** for autonomous coding tasks and Sruja's **deterministic gates** (lint, drift, evidence, MCP) for interactive editor workflows.
- Operate continual learning in token space: agent memory, `agent loop`, `agent plan` / `agent apply`, and optional local inference via `--enrich-cmd`.

For how Sruja combines autonomous coding with an independent deterministic grader, see [Grounded harness and continual learning](../../../../docs/GROUNDED_HARNESS_AND_CONTINUAL_LEARNING.md). For the **Context Graph** model, custom `schema` syntax, and default validation rules, see [Domain schema and context graphs](../../../../docs/architecture/domain-schema.md).
