Conversational Bot Architecture with Rust and Deno

Coursera Courses ↗ · Coursera

Open Course on Coursera

Free to audit · Opens on Coursera

Conversational Bot Architecture with Rust and Deno

Coursera · Intermediate ·🤖 AI Agents & Automation ·4h ago
Build multi-platform conversational bots using Rust and Deno by applying architecture patterns that separate core logic from platform-specific bindings. You will design Cargo workspace structures for organizing multi-crate bot projects, implement async event loops with the Tokio runtime for concurrent conversation handling, and apply Rust's ownership and borrowing model to write memory-safe concurrent code without garbage collection. The course walks through a universal bot crate that provides platform-agnostic conversation logic using Rust traits and generics. You will connect this universal bot to Amazon Bedrock for Large Language Model (LLM) powered responses using Claude, build an interactive Command-Line Interface (CLI) for testing bot conversations, and deploy a Discord bot using Deno and TypeScript. Deno's built-in permissions, TypeScript support, and Web Standard APIs simplify bot deployment compared to traditional Node.js approaches. Each module includes hands-on demonstrations of real bot implementations, from basic CLI conversation loops to production Discord integrations. The final project synthesizes workspace architecture, async runtime patterns, and platform bindings into a complete multi-platform bot system.
Watch on Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related AI Lessons

Why I spent 14 months building a firewall for AI agents
Learn why building a firewall for AI agents is crucial for production environments and how to approach this challenge
Dev.to · Alexander Paris
"Almost every time" vs "every time": why hooks beat instructions for AI agents
Learn how to use hooks to enforce constraints for AI agents, making them more reliable and efficient
Dev.to · Ken Imoto
AI is spitting out more potential drugs than ever. This start-up wants to figure out which ones matter.
AI is generating more potential drugs than ever, and a startup is working to identify the most promising ones, highlighting the importance of AI in drug discovery and development.
TechCrunch AI
Extreme AI Programming
Learn how to leverage AI agents for extreme programming and improve development efficiency
Dev.to · Barrie Hadfield
Up next
AI Agent Observability: How to Optimize
Voiceflow
Watch →