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Agentic Engineering
  • Fundamentals
  • Agent Architecture
  • Tool Calling
  • RAG Engineering
  • Context Engineering
  • Memory & State
  • Planning
  • MCP — Model Context Protocol
  • Multi-Agent Systems
  • Human-in-the-Loop
  • Evaluation & Testing
  • Observability
  • Guardrails & Security
  • Reliability Engineering
  • Frameworks
Agentic/Learn/Fundamentals

Fundamentals

What makes a system agentic, the agent loop, and what agentic engineers actually build.

What Is Agentic AI?
▶ interactive

A system is agentic when a model decides which action to take next based on what it observed, inside a loop with a termination condition — everything else is a program with an LLM in it.

The Agent Loop
▶ interactive

Every agent is the same loop — observe, reason, choose an action, run a tool, fold the result into state, check for completion — and every production problem lives in one of those boxes.

What Agentic Engineers Build

Six recurring system types — assistants, RAG, tool-calling systems, process automation, multi-agent systems, and the evaluation/observability layer that makes the others shippable.

AI Assistants

Conversational, support, research, coding and internal assistants share one shape and differ on four axes — knowledge, tools, risk and latency — which decide the architecture.

Business Process Automation

Agents orchestrating APIs, databases, documents and humans replace glue work — but side effects demand idempotency, audit trails, and often a workflow engine instead of an agent.

Choosing the Right Abstraction

Escalate plain code → LLM call → structured output → tool calling → RAG → workflow → agent → multi-agent one rung at a time, and stop at the first rung that solves the problem.

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