Prompt to Production: Workshop Guide
Welcome to the Prompt to Production workshop skill. This document serves as both a cheat sheet for the attendee and an instruction manual for the AI coding assistant.
If you are an AI assistant reading this, your goal is to help the user walk through the workshop exercises step-by-step. The reference implementations for every step are located in the
directory next to this file.
⚠️ API Reference: The Interactions API
Do NOT use the old
API shape. This workshop exclusively uses the new
client.interactions.create()
API.
Response Shape ( array)
An interaction returns a flat array of
, not
.
typescript
{
status: "requires_action", // or "completed"
steps: [
{ type: "user_input", content: ... },
{ type: "thought", signature: ... },
{ type: "function_call", id: "gth23981", name: "get_weather", arguments: {"location": "Boston"} },
{ type: "function_call_result", ... }
]
}
Passing State
Never manually append history arrays. Use
:
typescript
const response2 = await client.interactions.create({
model: "gemini-3.1-pro-preview",
previous_interaction_id: response1.id,
input: [
{ type: "function_call_result", name: "get_weather", call_id: "gth23981", result: "Sunny" }
]
});
🛠️ Workshop Walkthrough
This section outlines the progression of the workshop. For each step, guide the user to implement the code themselves before showing them the answer. Reference the
directory if they get stuck.
Step 1: The Basic API Call (solutions/01-basic-api-call.ts
Goal: Understand how to instantiate the client and make a basic
call.
Takeaway: The response object is flat. We access the final text via
response.steps.at(-1).text
.
Step 2: Generation Config (solutions/02-generate-config.ts
Goal: Learn how to apply configurations like
to the model.
Takeaway: Configuration is passed directly alongside the input and model parameters.
Step 3: Tool Calling (solutions/03-tool-call.ts
Goal: Provide the model with a JSON schema for a tool and see how it responds.
Takeaway: When tools are provided, the model's
becomes
and it generates a
step instead of text.
Step 4: The Stateless Method (solutions/04-stateless-method.ts
Goal: Manually handle a tool call using the old, expensive stateless method (re-sending history).
Takeaway: Manually building history arrays is error-prone and breaks the context cache.
Step 5: Interaction IDs (solutions/05-interaction-id.ts
Goal: Refactor the stateless method to use server-side state.
Takeaway: Passing
replaces the need to manage history, guaranteeing perfect cache hits.
Step 6: The Agent Loop ()
Goal: Wrap the
call in a
while (status === "requires_action")
loop.
Takeaway: An agent is just a model inside a loop that continuously executes tools and passes back
steps.
Step 7: The Coding Agent (solutions/07-coding-agent.ts
Goal: Give the agent loop real tools (
,
,
).
Takeaway: With local tools, the agent can interact with the file system. But running this locally is dangerous.
Step 8: Adding Google Tools (solutions/08-google-tools.ts
Goal: Integrate built-in tools like Google Search.
Takeaway: You can mix local function schemas with built-in tools like
{"type": "google_search"}
seamlessly.
Step 9: Daytona Sandboxing (solutions/09-daytona-sdk.ts
Goal: Move the local bash execution into an ephemeral cloud sandbox.
Takeaway: Production agents need secure execution environments. We replace
with
daytona.process.executeCommand
.
Step 10 & 11: Observability (solutions/10-adding-otel.ts
Goal: Add OpenTelemetry tracing to see inside the black box.
Takeaway: Tracing allows for Time Travel Debugging—we can grab a failed
and replay from that exact state without re-running the tools.