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Build an agent with the ADK

This guide walks through how to go from a blank slate to a production-ready voice agent using Agent Studio, the PolyAI ADK, and optionally a coding tool such as Claude Code.

There are two common ways to build with the ADK:

Workflow Description
CLI workflow The hands-on developer path. You run the commands yourself, edit files locally, and push changes back to Agent Studio.
AI-agent workflow You provide a brief; a coding tool uses the ADK to generate and push the project files on your behalf.

  • You provide context

    Gather the requirements, business rules, API information, and reference material.

  • The agent or developer builds

    Using the ADK, the project files are created, edited, validated, and prepared locally.

  • Agent Studio hosts and deploys

    The generated work is pushed back into Agent Studio, where it can be reviewed, merged, and deployed.

Architecture at a glance

Role Responsibility
You Provide requirements, project context, and business rules
PolyAI ADK Connect the local project to Agent Studio and manage sync, validation, and tooling
Coding agent Optionally generate and update files using the ADK
Agent Studio Host, preview, review, merge, and deploy the agent

Local project structure

When an Agent Studio project is linked locally, it follows this general structure:

<account>/<project>/
├── agent_settings/
│   ├── personality.yaml
│   ├── role.yaml
│   ├── rules.txt
│   └── experimental_config.json
├── config/
│   ├── entities.yaml
│   ├── handoffs.yaml
│   ├── sms_templates.yaml
│   └── variant_attributes.yaml
├── voice/
│   ├── configuration.yaml
│   ├── speech_recognition/
│   │   ├── asr_settings.yaml
│   │   ├── keyphrase_boosting.yaml
│   │   └── transcript_corrections.yaml
│   └── response_control/
│       ├── pronunciations.yaml
│       └── phrase_filtering.yaml
├── chat/
│   └── configuration.yaml
├── flows/
│   └── {flow_name}/
│       ├── flow_config.yaml
│       ├── steps/
│       │   └── {step_name}.yaml
│       ├── function_steps/
│       │   └── {function_step}.py
│       └── functions/
│           └── {function_name}.py
├── functions/
│   ├── start_function.py
│   ├── end_function.py
│   └── {function_name}.py
├── topics/
│   └── {topic_name}.yaml
└── project.yaml

This structure mirrors the parts of the agent that Agent Studio understands: settings, flows, functions, topics, channel configuration, and supporting resources.

Workflow 1 - CLI workflow

The CLI workflow is the manual developer path. You use the ADK directly, edit the project locally, and push changes back to Agent Studio.

Step 1 - Initialise your project

Link a local folder to an existing Agent Studio project. The agent must already exist in Agent Studio.

poly init
poly init --region <region> --account_id <account_id> --project_id <project_id>

This creates the local project structure and writes the metadata needed to connect the folder to Agent Studio.

Step 2 - Pull remote config and set up the environment

Pull the current configuration into your local project.

poly pull
poly pull -f

At this point, configure any API keys or environment variables needed for the project.

Run commands from the project folder

All CLI commands should be run from within the local project folder, unless you explicitly use the relevant path flag.

Step 3 - Run the agent locally

Start an interactive chat session to confirm the connection works and inspect runtime behavior.

Chat runs against main on Sandbox

poly chat connects to the main branch of your Sandbox environment in Agent Studio — not your local files, and not your current feature branch. At this stage it is useful for confirming the connection works. To chat against your own changes, push and merge your branch in Agent Studio first.

poly chat
poly chat --environment sandbox --channel voice
poly chat --functions --flows --state

Step 4 - Review the docs and understand the SDK

Use the CLI docs command to inspect the available resources and learn how they fit together.

poly docs --all
poly docs flows functions topics

Resource-specific documentation is available for agent settings, voice settings, chat settings, flows, functions, topics, entities, handoffs, variants, SMS templates, variables, speech recognition, response control, and experimental config.

Step 5 - Customise the agent

This is the core build phase. Create a branch, edit resources locally, track changes, and push them back.

Branching

poly branch create my-feature
poly branch switch my-feature
poly branch current
poly branch list

Functions

Create or modify backend functions the agent calls at runtime.

Typical locations include:

  • global functions under the functions directory
  • lifecycle hooks such as start and end functions
  • flow-scoped functions
  • function steps inside flows

Topics

Add or edit knowledge-base topics used for retrieval.

Agent settings

Update the personality, role, and rules that define the agent’s global behavior.

Flows

Build conversation flows, including prompts, step transitions, entities, and function steps.

Channel-specific settings

Adjust greeting messages, disclaimers, and style prompts for voice and chat.

Handoffs, SMS, and variants

Define escalation paths, SMS templates, and per-variant configuration.

ASR and response control

Tune speech recognition and control TTS behavior.

Experimental config

Enable or tune experimental features where needed.

Step 6 - Track and validate changes

Inspect the local changes before pushing.

poly status
poly diff
poly diff <file>
poly validate
poly format
poly revert --all
poly revert <file>

Step 7 - Push changes

Push the local changes back to Agent Studio.

poly push
poly push --dry-run
poly push -f
poly push --skip-validation

Step 8 - Test against sandbox

Once your branch is merged in Agent Studio, test the agent by chatting with it against the Sandbox environment.

Merge before chatting

poly chat connects to the main branch of your Sandbox — not your feature branch. Push your changes with poly push, merge the branch in Agent Studio, then run poly chat.

poly chat --environment sandbox
poly chat --environment sandbox --functions --flows

Step 9 - Iterate on quality

Review, refine, and test again. You can also use the review command to share diffs with teammates.

poly review
poly review --before main --after my-feature

Make test calls, inspect transcripts, refine prompts, flows, and functions, and then re-push.

Step 10 - Deploy to production

Once the changes are pushed and validated, merge the branch in Agent Studio and deploy the project.

Step 11 - Monitor performance

Use Agent Studio analytics to monitor containment, CSAT, handle time, and flagged transcripts. Pull changes back locally as needed and continue iterating.

Workflow 2 - AI-agent workflow

The AI-agent workflow uses a coding tool such as Claude Code to run the same development loop on your behalf.

  • You provide the brief

    Requirements, business rules, integrations, and API documentation.

  • The coding tool generates the project

    It uses the ADK to read documentation, generate files, and push the result.

  • You review and deploy

    Agent Studio remains the place where the work is checked, merged, and deployed.

No manual flow-building required

In this workflow, the coding tool generates the project files. Agent Studio is where the output is reviewed, tested, and deployed.

Step 1 - Gather requirements

Collect the project context before you begin.

Include anything the coding tool will need to produce a working agent:

  • API endpoint URLs
  • business rules
  • use-case descriptions
  • internal notes or emails
  • reference material
  • links to API documentation

The more complete and structured your input is, the less correction the output requires.

Front-load the context

Gather everything up front. Providing context piecemeal produces piecemeal output.

Step 2 - Create a new project in Agent Studio

Open Agent Studio and create a brand-new project.

The project starts empty:

  • no knowledge base
  • no flows
  • no configuration

That blank starting point is intentional. The coding tool populates the project in later steps.

Think of Agent Studio as the deployment target

Agent Studio is where the project lives, but the coding tool generates the actual content.

Step 3 - Start the coding tool via the CLI

Open your terminal and start the coding tool.

At this stage:

  • the ADK must already be installed
  • the Agent Studio project must already exist
  • the coding tool should initialize and link the project using the ADK
poly init --region <region> --account_id <account_id> --project_id <project_id>
poly pull

The ADK acts as the bridge between your local environment and Agent Studio. It lets the coding tool read from and write back to the project.

Step 4 - Give the coding tool its context

Provide the coding tool with the information you gathered earlier.

Include:

  • project-specific requirements
  • the URL to the business’s public API documentation
  • relevant internal context
  • useful patterns or best practices from previous projects

Use the docs command to generate a reference file the coding tool can read:

poly docs --all

Step 5 - Generate the project files

Once the context is in place, the coding tool generates the project files.

This produces the assets the agent needs, including:

  • Conversation flows

    Dialogue logic and routing for the agent.

  • Callable functions

    Backend functions used during calls.

  • Knowledge base entries

    Information the agent can reference when answering questions.

  • API integrations

    Both real API connections and mock endpoints for testing.

The generated files follow ADK structure and are ready to push to Agent Studio.

Step 6 - Push to Agent Studio

Once the files are generated, use the ADK to push them to Agent Studio.

A new branch is created in the project so the generated work can be reviewed safely before anything goes live.

When you switch to that branch in Agent Studio, you should see the generated changes, such as:

  • updated greeting messages
  • new knowledge base entries
  • a built tracking flow
  • real and mock API integrations

Use the branch review step

The branch-based workflow makes it possible to inspect what was generated before merging it into the main project.

Step 7 - Review, merge, and deploy

Review the generated work inside Agent Studio.

Check that the key parts of the agent look correct:

  • flows
  • functions
  • knowledge base entries
  • API integrations

Once everything looks right:

  1. merge the branch into the main project
  2. deploy the project

At that point, the agent is live.

CLI command overview

Command Description
poly init Initialise a new project locally
poly pull Pull remote config into the local project
poly push Push local changes to Agent Studio
poly status List changed files
poly diff Show diffs
poly revert Revert local changes
poly branch Branch management
poly format Format resource files
poly validate Validate project configuration locally
poly review Create a diff review page
poly chat Start an interactive session with the agent
poly docs Output resource documentation

The overall loop

  1. create or connect a project
  2. build locally using the ADK
  3. push to Agent Studio
  4. review, merge, and deploy

Next steps