---
title: "Explorer"
---

import SupportCTA from "/snippets/support-cta.mdx";

<SupportCTA />

Best for people who want a high-level understanding of agent systems without
committing to a strict build sequence.

## Recommended reads


- [The Agent Systems](../foundations/the-agent-system): start

  with the core definition and operating loop.
- [History Of Agent Ideas](../foundations/history-of-agent-ideas): use the
  short historical arc to understand why the field looks the way it does.
- [Agents Vs Workflows](../foundations/agents-vs-workflows): clarify the
  boundary between deterministic orchestration and bounded autonomy.
- [Deep Research Agents](../case-studies/deep-research-agents): see how one
  of the clearest modern agent products is structured.
- [Ecosystem](../ecosystem/index): compare the major tools, platforms, and
  market categories.
- [Radar](../radar/index): track what is changing quickly across the field.

## Optional deeper dives

- [Agent Memory And Retrieval](../patterns/agent-memory-and-retrieval): go
  here if you want a practical mental model for memory, retrieval, and
  artifacts.
- [Reasoning And Control Patterns](../patterns/reasoning-and-control-patterns):
  go here if you want the control-loop view of agent behavior.
- [LLM Foundations For Agent Systems](../foundations/llm-foundations-for-agent-systems):
  go here if you want the minimum model literacy behind modern agents.
- [Context Engineering](../systems/context-engineering): go here if you
  want the production-minded view of how context is managed over time.
- [AI Education Policy To Practice](../contributor-kit/reference-notes/ai-education-policy-to-practice):
  go here if you want a product-agnostic example of turning AI policy language
  into a practical learning activity.

## What this guide optimizes for

- Clear orientation without requiring a fixed sequence
- High-level understanding before implementation detail
- A broad view of the field and its moving parts