A Rust-first coding agent with a framework and learning system for building production-grade AI agents.
This stack combines a coding agent, an agent framework, and guided learning into one coherent Rust-first system.
You learn, build, and run reliable AI agents using the same architecture — from first principles to real execution.
Structured, hands-on materials for agent systems engineering in Rust.
You learn by working with real code and the same architecture used by the agent and framework — not isolated tutorials.
A hybrid actor / FSM / task framework for building reliable AI agent systems.
Focused on explicit state, supervision, orchestration, and predictable execution, with WASM support.
A transparent coding workspace for working with AI on real code.
Watch diffs, follow task progress, and review every edit while the agent executes across your local development environment.
All components are designed together as parts of a single agent system.
What you learn in KNOWLEDGE maps directly to CRB, and RIDE operates on the same structures — no translation layer, no conceptual gaps.
Learn concepts in KNOWLEDGE, apply them through CRB, and execute them with RIDE.
The same mental models, abstractions, and code structures flow across all layers without context switching.
Every component is designed around predictable behavior and explicit control.
No toy examples or abstract demos — the entire system is built around real constraints and failure modes.
Rust is not an add-on or backend choice — it is the execution model.
State, concurrency, memory, and safety are handled explicitly from learning to execution, without language switching.
Courses teach the same patterns implemented in the framework.
RIDE understands and operates on those patterns directly.
The framework itself is used in all examples. One architecture, reused everywhere.
You don't need to assemble tools or invent glue code.
The system provides a clear path from first principles to executable agents, reducing friction and cognitive overhead.
AI is treated as part of the system, not a black box.
Reasoning appears in agents, execution in pipelines, and feedback in tooling — aligned across all layers.
The stack guides you through a single, coherent path — from understanding agent systems to running them as real software.
Each stage builds on the same architecture, tools, and mental models.
Access the Rust-based coding agent, framework, and learning materials — designed as a single coherent system.
