Repository navigation
Module 02 Amazon Bedrock Essentials
Your first real calls: Converse API, tokens, tool use, knowledge bases, guardrails.
Module 02 of 16 · track Invoke · Estimated time: 6–8 hours · Prerequisites: Modules 00–01, and an AWS account with Bedrock model access enabled.
This is where AWS enters properly. One API — Converse — carries you from a hello-world call all the way to tool use and retrieval. Learn it well here and every later module gets easier.
Open the module on GitHub ↗: the slides, notebooks, exercises and solutions are there. This page is the reading order, with the tutorial and the workbench alongside.
The lesson that frames this module is Why Your AI Agent Costs 4× the Estimate, and How to Fix It (7 min): what a token actually costs once the habits are counted. Then try the bill leak calculator in the workbench: the same decision, with your numbers.
- Invoke any Bedrock model through the Converse API and read the token accounting
- Hold a correct multi-turn conversation, including the assistant tool-use turn
- Define a tool schema the model actually calls correctly
- Query a Bedrock Knowledge Base and ground an answer in retrieved context
- Apply a Guardrail and observe what it blocks
| Portable GenAI concepts | AWS-specific surface |
|---|---|
| Prompting | Amazon Bedrock Converse API |
| Multi-turn state | InvokeModel |
| Tool/function calling | Bedrock Knowledge Bases |
| Retrieval grounding | Bedrock Guardrails |
| Safety filtering | IAM for Bedrock |
Portable concepts transfer to any stack. The AWS column is where this module touches the cloud — see docs/concepts/portability-matrix.md.
| # | Step | What it is | |
|---|---|---|---|
| 1 | 📖 | slides/Bedrock_Chapters_1_to_4.pptx |
Chapters 1–4: access, models, first calls, tokens |
| 2 | 💻 | notebooks/00_Bedrock_Onboarding.ipynb |
Onboarding notebook — verify your access works |
| 3 | ✏️ | exercises/Exercise_1_First_Calls_and_the_Converse_API.pdf |
Exercise 1 · first calls |
| 4 | 💻 | notebooks/converse_api_masterclass.ipynb |
Converse API masterclass |
| 5 | ✏️ | exercises/Exercise_2_Tokens_and_Multi-Turn_Conversations.pdf |
Exercise 2 · tokens and multi-turn |
| 6 | 📖 | slides/Bedrock_Chapters_5_to_8.pptx |
Chapters 5–8: tool use, RAG, guardrails, agents |
| 7 | 💻 | notebooks/travelmind_refund_agent.ipynb |
TravelMind refund agent — tool use in anger |
| 8 | ✏️ | exercises/Exercise_3_Tool_Use_and_Knowledge_Bases.pdf |
Exercise 3 · tool use and KBs |
| 9 | ✏️ | exercises/Exercise_4_Guardrails_Strands_and_End-to-End_Agent_Design.pdf |
Exercise 4 · guardrails and end-to-end design |
| 10 | 💻 | notebooks/Day5_Bedrock_Build.ipynb |
Build session — put it together |
📖 read 💻 run ✏️ practise 📊 workbook 🔖 reference
Worked solutions live in solutions/. Attempt every exercise closed-book first — the solutions are written to be read after you have a wrong answer to compare against.
projects/bedrock-mini-project — a self-contained build with scripts, KB documents and a cost analysis.
- Using
bedrockwhen you needbedrock-runtime. Different clients, different operations. - Dropping the assistant's tool-use message from history. The next turn then makes no sense to the model.
- Assuming model access is on by default. It is per-model, per-region, and must be requested.
Every error anyone has hit in this course is in the Error Index, by the exact string. Model access and region problems are in Model and Region Notes. If it is a question rather than an error, check the answered ones first, then ask in Q&A.
Frameworks
- Token Tax Ledger — Four of six taxes are charged on every turn
- Grounding Triangle — Retrieved ≠ cited ≠ verified
- Tool Surface Audit — Six axes per tool — the schema is what the model sees
Quick reference
- Bedrock Converse API — Clients, message shape, and the tool-use round trip
- Prompting for agents — The three prompts in an agent
Recipes and procedures
- Add a tool properly — 30-minute recipe for a tool the model calls correctly
← Module 01 · LLM Intuition and the AWS Bridge · All modules · Module 03 · Amazon Bedrock Agents →
✏️ This page is generated from modules/02-bedrock-essentials/README.md. To change it, edit the module README: an edit made here is replaced at the next sync.
This wiki is the connective layer. The repository is canonical and versioned; these pages are the cross-surface maps and the notes that change too often to live in a reviewed file. Anyone can edit — see Editing this wiki.
▶ Start here · 55 lessons, on the site ↗
- Getting started · 2
- Agentic PDLC fundamentals · 9
- Methods decoded · 7
- Running delivery · 13
- By role · 9
- Teams and organisation · 4
- Practice · 4
- Interviews and careers · 7
The method
The Agentic PDLC
The Eight Loops
Gates & Governance
The Evidence Pack
The journey · end to end
Product manager
Solution architect
Engineering lead
QA lead
DevOps & platform
The method · by role
Product manager
Solution architect
Engineering lead
QA lead
DevOps and platform
Sponsor
How to
Run an NFR workshop
Design an agent on paper
Build, buy or borrow
Cut sprints into bolts
Review by risk band
Prove the bar
Control the token bill
Hold the security boundary
Run a missing-control postmortem
Reference
Mental Models
Glossary
Formulas & Calculators
Decision Trees
Scenario Library
Exercises & Answers
Anti-Patterns
Sources & Confidence
Where do I find…?
The 16 modules
- Agentic Foundations
- LLM Intuition and the AWS Bridge
- Amazon Bedrock Essentials
- Amazon Bedrock Agents
- Agent Builder, Knowledge Bases and Guardrails
- The Agent Loop: No Framework to Strands
- Strands Foundations: Tools, Memory and MCP
- Multi-Agent Patterns with Strands
- LangChain and LangGraph
- LLM Memory Mechanics
- RAG, OpenSearch and LiteLLM
- Amazon Bedrock AgentCore
- A2A and A2UI: Agent Interoperability
- Agentic QA and Evaluation
- End-to-End Production Pipeline
- Agentic Product Lifecycle
Learning paths · Field guide
Study Plans
Eight sessions
Living notes
Error Index
Community Answers
Field Notes
Model & Region Notes
Cost Log
Scoreboard 🧪
The project
Roadmap
Editing this wiki
Maintainer Runbook
📘 The manual · live
🛫 Ninety Days, the simulator
🧰 The workbench
👔 For leadership
🧠 Mental models
Templates · Prompts
Frameworks & acronyms
The repository · Setup
Pinned discussions
Discussion map — where to post what
Exercise & lab index
Simulator Arena — get a lab graded
Pitch an idea
All discussions →