Copy-paste ready
Tooling cheat sheet
Get productive fast — environment, your agentic IDE on your laptop, and a Strands quickstart.
Before you arrive (on your laptop)
The afternoon fork runs on your own laptop, so install ahead of time:
curl -LsSf https://astral.sh/uv/install.sh | sh # uv (Python package + venv manager)First 10 minutes (workshop environment — for the morning labs)
Labs 1–2 run in VS Code Server on EC2, region us-west-2.
- Open the Workshop Studio event dashboard → Event Outputs → open the Code Editor URL (VS Code Server).
- In the VS Code terminal, install dependencies and set the region:
uv sync
aws configure set region us-west-2
aws configure get region- Open
01-bedrock-knowledge-base/01_create_knowledgebase.ipynb→ Select Kernel → Python Environments → Venv → Use Existing (.venv).
#1 snag: if the notebook can't find the kernel, run
source .venv/bin/activate in the terminal, then re-select the kernel.Your agentic IDE (afternoon fork — on your laptop)
Build your agent in your own IDE against your workshop AWS credentials. Get those from the Workshop Studio dashboard, then point your laptop at us-west-2:
# Workshop Studio dashboard -> "Get AWS CLI credentials" -> paste the export block, then:
aws configure set region us-west-2
aws sts get-caller-identity # confirms you're in the workshop accountKiro
kiro-cli chat- Steering:
.kiro/steering/*.md(orAGENTS.md) - Skills:
.kiro/skills/NAME/SKILL.md - Powers: MCP + knowledge bundles (Kiro panel)
- MCP:
.kiro/settings/mcp.json· Agents:.kiro/agents/ - Ask Kiro about Kiro:
/guide
Claude Code
npm install -g @anthropic-ai/claude-code- Memory:
CLAUDE.md(read every session) - Skills:
.claude/skills/NAME/SKILL.md - Subagents:
.claude/agents/ - MCP:
claude mcp add ...· Hooks:.claude/settings.json - Slash commands:
.claude/commands/*.md
Write once, use in both. Skills follow the open Agent Skills standard — a
SKILL.md works in Kiro and Claude Code. And CLAUDE.md ≈ AGENTS.md ≈ Kiro steering.Recommended setup for this build
Install Strands (Python)
uv add strands-agents strands-agents-toolsAdd an AWS docs MCP server
Kiro — .kiro/settings/mcp.json:
{
"mcpServers": {
"aws-docs": {
"command": "uvx",
"args": ["awslabs.aws-documentation-mcp-server@latest"]
}
}
}Claude Code — one command:
claude mcp add aws-docs -- uvx awslabs.aws-documentation-mcp-server@latestStarter project context (steering / CLAUDE.md / AGENTS.md)
# Building a Strands (Python) agent on Amazon Bedrock AgentCore.
- Region: us-west-2. Package manager: uv. Python 3.10+.
- Framework: Strands Agents (model-driven). Model: Claude Sonnet 5 (us.anthropic.claude-sonnet-5).
- Pattern: Agents-as-Tools — a supervisor routes to specialist agents.
- Deploy target: AgentCore Runtime. External APIs via AgentCore Gateway (MCP).
- Always: write tests, least-privilege IAM, no secrets in code.Strands quickstart (a tool-using agent in ~10 lines)
from strands import Agent, tool
@tool
def get_current_rate(term_years: int) -> str:
"Return today's rate for a given mortgage term."
return lookup_rate(term_years)
agent = Agent(
model="us.anthropic.claude-sonnet-5", # current Sonnet for your own build
system_prompt="You are a helpful mortgage assistant.",
tools=[get_current_rate],
)
print(agent("What are 15-year rates today?"))Model note: the morning labs are pinned to Claude 3.7 Sonnet for reproducibility. For your own agent use a current model — Claude Sonnet 5 (
us.anthropic.claude-sonnet-5) or the prior gen us.anthropic.claude-sonnet-4-6. Swapping is a one-line model= change.