Hands-On Session #1: Working with Agents

In this lab we'll get started on the Ascend platform to understand how the architectural frameworks we've discussed come together in an agentic platform. We'll also work with Ascend's AI agent, Otto, to build your first data pipeline.

Step 1: Sign up for a free trial

tip

The Ascend free trial lasts for 14 days or 400 Ascend Credits, whichever comes first. To continue using Ascend beyond these limitations, you can select a plan to subscribe to. Free trial credits do not roll over so we recommend waiting until you are near your limits. If your limits are reached, the Instance will be locked — you can still subscribe to a plan at this point to unlock and continue using Ascend.

Submit the form

Go to https://app.ascend.io/signup and fill out the form to start your free Developer plan trial.

Accept your invite

Navigate to your email inbox and look for a message from Ascend (support@ascend.io). Click to accept the invite.

Click to accept the invite. Then create your password or sign in with Google SSO.

tip

Email support or ask a bootcamp instructor for help if you do not receive the verification email within a few minutes.

Step 2: Sign in to Ascend

Sign in to your Ascend Instance. You'll see Otto on your home screen.

Step 3: Build your first pipeline with Otto

Click Create a pipeline.

Select From Otto's Expeditions data to use Ascend's built-in sample dataset.

Hit Send.

note

You can also copy/paste this prompt:

Help me create my first data pipeline. Use the synthetic Otto's Expeditions data, specifically the `goats.csv` file. Create a new Flow named `goats_demo` with 3 components: 
- a file reader
- a SQL Transform
- a Python Transform

Iterate until the Flow run ends to end. 

Then, create a visualization for me to explore the data.

Watch Otto work!

tip

Otto may make mistakes along the way! We recommend letting him iterate and fix issues on his own; agentic development loops tend to converge toward success. You'll end up with a working data pipeline you can visualize, explore, and build on.

Here's what's happening under the hood:

1. Otto receives a prompt to build a data pipeline, which acts as a Trigger for the agent to begin working.

2. It gathers Context from the prompt itself as well as the Workspace and Project, looking at existing files and resources to build the pipeline. Context also includes system instructions and rules that define Otto's behavior and capabilities. To see how this context comes together, you can view this example prompt trace.

3. Otto has access to a Tool set of functions that can be used to build the pipeline. In this case, Otto uses functions to read, create, and edit files in the Workspace. It also uses functions to run pipelines, query data, and build visualizations, and more. Tools are what enable agents to not just understand the context of the user's request, but also to take action on it.
   
   Additionally, you can give agents access to external tools and services via the MCP servers, empowering agents to work across your tool stack from GitHub to Slack to Grafana to PagerDuty and more.

More prompts to try

Here are some more prompts you can try after Otto creates your first data pipeline.

Navigate me to my Workspace.

What tools do you have access to?

Give the artifact a dark mode switcher.

Email me a link to the artifact.

Explain how I'd automate this pipeline on a schedule and deploy it to production in Ascend.

Step 4: Tour the platform

Now that Otto has built your first pipeline, let's explore the key areas of the Ascend platform.

Otto - Your AI data engineering agent

Otto is the AI agent that helps you build your data pipelines. You can access Otto from the homepage, by clicking the sparkles icon in the top right of your screen, or by using the Ctrl + I keyboard shortcut.

Workspaces

The Workspace is your central hub for building and managing your data pipelines. From here you can:

• Build - Create and manage Flows
• Test - Run your Flows and Components in a development environment
• Deploy - Deploy data pipelines to run in production

Super Graph

The Super Graph is your high-level view of all Flows in your Workspace. From here you can see:

Double-click on any Flow to drill into its Flow Graph.

Flow Graph

The Flow Graph shows all Components within a single Flow:

• Read Connectors - Ingest data from external sources
• Transforms - Process and transform data using SQL or Python
• Write Connectors - Send data to external destinations
• Task Components - Run custom code using Python or SQL

Click on any Component to view the code, run history, and data.

Toolbar

The Toolbar on the right side of your screen provides quick access to:

• Resources - Browse all resources in your Workspace
• Files - View and edit configuration files
• Worksheets - Run ad-hoc SQL queries
• Build - Monitor build status and logs

Deployments

Deployments are used to run your data pipelines in production. They operate on a different branch of your Git repository and write to a different environment in your data warehouse. This allows you to test and validate your data pipelines in a development environment before deploying them to production.

tip

Your new trial Instance of Ascend does not include a Deployment by default. We will create a Deployment in an upcoming session and discuss safe and effective agentic Data Operations with CI/CD workflows.

Settings

Access the Settings menu by clicking your profile icon in the top right corner of your screen. It allows you to manage your account, Workspace, and preferences.

Navigation tips

• Use Cmd+K (Mac) or Ctrl+K (Windows) to quickly search and navigate anywhere in the platform
• Use Ctrl+I to open Otto chat from anywhere

Congratulations! You've successfully completed Hands-On Session #1!

By the end of this session, you should have:

• Created an Ascend account
• Signed in to the platform
• Built your first data pipeline with Otto

Need help?

Ask a bootcamp instructor or reach out in the Ascend Community Slack.

Next steps

Continue to the Breakout Session with Snowflake, BigQuery, or MotherDuck to learn about how to leverage AI within these platforms. You'll also connect Ascend to your data warehouse to run your data pipelines and store the data there.