# Organization of the Documentation

The Nesa documentation is structured into four major parts: concept, core systems, usage, and infrastructure. This allows readers to progress from understanding *why Nesa exists* to *how to build and operate on it*.

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### Part I: Vision and Foundations

This section introduces the **motivations behind Nesa** and its place in the evolving AI landscape:

* What problems Nesa solves in the AI economy
* Why centralized AI systems are structurally flawed
* Where previous decentralized AI approaches fell short
* How Nesa differs architecturally, economically, and cryptographically

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### Part II: Core Systems and Innovations

This section presents Nesa’s **technical architecture**, including its novel execution and security primitives. It covers:

* How Nesa distributes and verifies large AI models
* How privacy and correctness are enforced with cryptography
* How performance is optimized across heterogeneous nodes
* How token economics and governance shape participation
* First-party applications showcasing on-chain AI

> 🛠 This section may evolve as we publish new protocol modules (e.g., inference scheduling, multi-agent coordination, on-chain routing) or refine the current ones.

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### Part III: Using Nesa

This section helps developers and users **interact with the network**, covering:

* Wallet setup, testnet access, and query submission
* Using Nesa via web, SDK, IBC, or bridging tools
* Integrating your models or consuming others’ models trustlessly

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### Part IV: Operating a Nesa Node

This section guides those who wish to **contribute compute** or run nodes:

* Hardware requirements and installation
* Runtime behavior and lifecycle
* Validator incentives and responsibilities
* Troubleshooting and CLI usage

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### Additional Resources

* **Community** — Join us via Discord or Twitter
* **Live apps** — Explore applications like DNA X
* **Policy** — Review our terms and privacy policies
* **Glossary** — Find definitions for key protocol terms

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This structure is designed to support **modular growth**. As Nesa evolves—from a decentralized inference engine to a foundation for verifiable autonomous AI—you’ll find new primitives, agents, and integrations reflected across the documentation.