·AWS Bedrock
Capstone Project: Enterprise AI Assistant
The Final Challenge. Building a production-grade, secure, and observable AI system on AWS Bedrock.
AWS Bedrock
60 articles
·AWS Bedrock
Module 1 Lesson 1: What is AWS Bedrock?
Understanding the foundations of AWS Bedrock, the managed service for foundation models.
·AWS Bedrock
Module 1 Wrap-up: Foundations and Model Selection
Hands-on: Analyzing model suitability and understanding the serverless AI paradigm.
·AWS Bedrock
Module 10 Lesson 1: What are Bedrock Agents?
The Autonomous Brain. Understanding how Bedrock Agents use reasoning to solve multi-step problems.
·AWS Bedrock
Module 10 Lesson 2: Agent Instructions
Defining the Mission. How to write effective 'Agent Instructions' that guide an autonomous AI through complex workflows.
·AWS Bedrock
Module 10 Wrap-up: Designing your Agent
Hands-on: Design the mission statement and tool-set for your first Bedrock Agent.
·AWS Bedrock
Module 11 Lesson 1: Action Groups and Schemas
Defining the Capability. How to describe your APIs to a Bedrock Agent using OpenAPI schemas.
·AWS Bedrock
Module 11 Lesson 2: Lambda-Backed Tools
Connecting to Code. How to use AWS Lambda to execute the actual logic behind your agent's action groups.
·AWS Bedrock
Module 11 Wrap-up: Giving your Agent Skills
Hands-on: Write a Lambda function and a schema for an agent that can track package deliveries.
·AWS Bedrock
Module 12 Lesson 1: The Reasoning Loop
How Agents Think. Understanding the ReAct (Reason + Act) cycle that powers Bedrock's autonomous decisions.
·AWS Bedrock
Module 12 Lesson 2: Handling Agent Failures
Resilient Autonomy. How to design agents that can recover from API errors and tool failures gracefully.
·AWS Bedrock
Module 12 Wrap-up: The Master Planner
Hands-on: Trace the execution of a multi-step agent and identify reasoning bottlenecks.
·AWS Bedrock
Module 13 Lesson 1: The Planner-Executor Pattern
Division of Labor. How to split 'Thinking' and 'Doing' between two different agents for higher reliability.
·AWS Bedrock
Module 13 Lesson 2: Supervisor Agents
The AI Manager. How to build a supervisor agent that routes user queries to the correct specialized sub-agent.
·AWS Bedrock
Module 13 Wrap-up: The Team Lead
Hands-on: Design the architecture for a multi-agent system that handles a complex business workflow.
·AWS Bedrock
Module 14 Lesson 1: Agent Approval Flows
Safe Autonomy. How to implement 'Pause and Approve' patterns to ensure humans sign off on high-stakes AI actions.
·AWS Bedrock
Module 14 Lesson 2: Escalation Strategies
Knowing your Limits. How to design agents that realize they are stuck and hand over the conversation to a human expert.
·AWS Bedrock
Module 14 Wrap-up: The Collaborative AI
Hands-on: Design a human-in-the-loop workflow for a high-value financial transaction agent.
·AWS Bedrock
Module 15 Lesson 1: Logging and Tracing
Sseeing the Thoughts. How to use CloudWatch and Tracing to debug your Bedrock Agents and see their step-by-step logic.
·AWS Bedrock
Module 15 Lesson 2: Cost Monitoring
Protecting the Wallet. How to track token usage and set up alerts to prevent unexpected AWS bills from your GenAI apps.
·AWS Bedrock
Module 15 Wrap-up: The Observability Suite
Hands-on: Create a CloudWatch dashboard that tracks your agent's success rate and token spend.
·AWS Bedrock
Module 16 Lesson 1: Hardening the Agent
Locking Down the AI. How to use IAM roles and AWS Secrets Manager to ensure your agent can only access exactly what it needs.
·AWS Bedrock
Module 16 Lesson 2: Defending the Prompt
Prompt Injection Defense. Advanced strategies for preventing users from tricking your agent into tool misuse.
·AWS Bedrock
Module 16 Wrap-up: The Security Audit
Hands-on: Design a secure architecture that involves IAM, Secrets Manager, and Guardrails.
·AWS Bedrock
Module 17 Lesson 1: Versioning and Aliases
Safe Deployments. How to use Bedrock Agent Versions and Aliases to update your AI without breaking your production app.
·AWS Bedrock
Module 17 Lesson 2: Scaling and Retries
Handling the Peak. Advanced strategies for dealing with Bedrock's rate limits using exponential backoff and request queuing.
·AWS Bedrock
Module 17 Wrap-up: Ready for Production
Hands-on: Design a deployment strategy for a mission-critical AI agent.
·AWS Bedrock
Module 18 Lesson 1: Introducing AgentCore
The Enterprise Orchestrator. Understanding why AgentCore exists and how it brings deterministic control to AI workflows.
·AWS Bedrock
Module 18 Lesson 2: AgentCore vs Basic Agents
Choosing the Right Tool. Comparing the strengths of autonomous Bedrock Agents and controlled AgentCore workflows.
·AWS Bedrock
Module 18 Wrap-up: The Enterprise Mindset
Hands-on: Identify a business workflow that requires the control and state management of AgentCore.
·AWS Bedrock
Module 19 Lesson 1: AgentCore Nodes and Flow
The Blueprint. Understanding how AgentCore uses 'Nodes' and 'Edges' to create complex, manageable AI graphs.
·AWS Bedrock
Module 19 Lesson 2: Persistence and Recovery
AI with Memory. How AgentCore preserves state across days or weeks, allowing workflows to survive crashes and wait for human input.
·AWS Bedrock
Module 19 Wrap-up: Mapping the Logic
Hands-on: Design a multi-node AgentCore graph that includes AI reasoning and data validation.
·AWS Bedrock
Module 2 Lesson 1: IAM for Bedrock
Mastering Identity and Access Management for AI. Creating policies that allow your apps to talk to Bedrock securely.
·AWS Bedrock
Module 2 Lesson 2: Enabling Model Access
The 'Edit Model Access' step. How to manually request access to foundation models in the AWS Console.
·AWS Bedrock
Module 2 Wrap-up: Getting Ready for Code
Hands-on: Verify your AWS configuration and enable your first foundation models.
·AWS Bedrock
Module 20 Lesson 1: Controlled RAG
High-Fidelity Search. How to use AgentCore to make your RAG systems more reliable by adding pre-search and post-search nodes.
·AWS Bedrock
Module 20 Lesson 2: Multi-Stage Reasoning
Chain of Thought Orchestrated. How to build complex reasoning pipelines where multiple AI models check each other's work.
·AWS Bedrock
Module 20 Wrap-up: The High-Fidelity Assistant
Hands-on: Design an AgentCore workflow that uses a critic node to verify RAG output.
·AWS Bedrock
Module 3 Lesson 1: The InvokeModel API
Going Raw. How to use InvokeModel to send model-specific JSON payloads to Bedrock.
·AWS Bedrock
Module 3 Lesson 2: The Converse API
Unified AI. How to use AWS Bedrock's standard interface to write model-agnostic code.
·AWS Bedrock
Module 3 Wrap-up: Your First AI Call
Hands-on: Write a script that compares the outputs of two different models using the same prompt.
·AWS Bedrock
Module 4 Lesson 1: System Prompts in Bedrock
Defining the Persona. How to use the 'System' role in Bedrock to control AI behavior and safety.
·AWS Bedrock
Module 4 Lesson 2: Cost-Aware Prompting
Saving Money by Design. How to optimize your prompts to use fewer tokens and reduce your AWS bill.
·AWS Bedrock
Module 4 Wrap-up: Engineering the Instruction
Hands-on: Robust prompt engineering to reduce hallucinations and maximize cost-efficiency.
·AWS Bedrock
Module 5 Lesson 1: Streaming Responses
The Typing Effect. How to use converse_stream to send tokens to your UI as they are generated.
·AWS Bedrock
Module 5 Lesson 2: Latency and Throttling
Handling the Load. Understanding Bedrock's rate limits and how to optimize for the fastest response times.
·AWS Bedrock
Module 5 Wrap-up: Real-time Performance
Hands-on: Build a streaming CLI chat application that handles tokens as they arrive.
·AWS Bedrock
Module 6 Lesson 1: FastAPI + Bedrock
Creating the Backend. How to wrap your Bedrock logic in a high-performance REST API.
·AWS Bedrock
Module 6 Lesson 2: Managing Chat State
Memory in the Cloud. How to maintain conversation context across multiple API requests.
·AWS Bedrock
Module 6 Wrap-up: Shipping the API
Hands-on: Build a functional REST API with FastAPI that exposes multiple Bedrock models.
·AWS Bedrock
Module 7 Lesson 1: What is a Knowledge Base?
Foundations of RAG. Why Knowledge Bases are the secret to building AI that 'knows' your private business data.
·AWS Bedrock
Module 7 Lesson 2: Chunking and Embeddings
Slicing the Data. Understanding how Bedrock breaks docs into 'Chunks' and turns them into 'Vectors' of meaning.
·AWS Bedrock
Module 7 Wrap-up: Designing the Library
Hands-on: Design your first Knowledge Base and select your chunking strategy.
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Module 8 Lesson 1: Retrieve and Generate
The RAG APIs. Understanding the difference between raw retrieval and the fully managed 'Answer' API.
·AWS Bedrock
Module 8 Lesson 2: Source Attribution
Proving the Answer. How to extract citations and references to show users exactly where the AI found its information.
·AWS Bedrock
Module 8 Wrap-up: Real-World RAG
Hands-on: Build a Python script that answers questions about your S3 documents and prints the citations.
·AWS Bedrock
Module 9 Lesson 1: Bedrock Guardrails
Setting the Safety Net. How to use AWS Bedrock Guardrails to filter sensitive content and block inappropriate prompts.
·AWS Bedrock
Module 9 Lesson 2: Verification and Grounding
Fighting the Hallucination. Advanced techniques to ensure the AI stays strictly within the retrieved documentation.
·AWS Bedrock
Module 9 Wrap-up: The Safe Assistant
Hands-on: Implement a Bedrock Guardrail and verify your grounding instructions.