Categories: FAANG

Announcing prompt management in the Vertex AI SDK

As generative AI applications grow in sophistication, development workflows become more fragmented. Although AI can be a force multiplier, teams may design prompts in one environment, manage versions in spreadsheets or text files, and then manually integrate them into their code. This leads to inefficiencies, versioning chaos, and collaboration bottlenecks. 

Vertex AI Studio is designed to solve this. It offers a powerful collaborative workspace for testing and managing prompts within the Google Cloud console. Today, we are announcing the General Availability (GA) of Prompt Management in the Vertex AI SDK, a new set of capabilities designed to bring control, scalability, and enterprise-readiness to your prompt management workflow. Some key benefits: 

  • Programmatic prompt management: Create, version, and manage prompts directly within the Vertex AI SDK. 

  • Seamless UI-to-SDK experience: Move effortlessly between designing prompts in Vertex AI Studio and managing them at scale with the SDK.

  • Enhanced collaboration: Share and reuse prompts as a team by managing them as a centralized resource within your Google Cloud project.

  • Enterprise-ready: Available for everyone with full support, including CMEK and VPCSC for your security and compliance needs.

Let’s take a look at how you can manage your prompts using the Vertex SDK. 

How it works: prompts as code

The Vertex AI SDK empowers you to treat your prompts as a versioned asset in your application. You can create, retrieve, update, and manage your prompts with just a few lines of Python code, enabling powerful new workflows. 

Whether you prefer the visual interface of Vertex AI Studio or the programmatic power of the SDK within your own environment, your prompts are a managed resource within your Google Cloud project — easy to track, share, and reuse. Design and test a prompt in the Studio UI, and then use the SDK to programmatically manage versions at scale. Furthermore, this GA launch comes with enterprise support, including Customer-Managed Encryption Keys (CMEK) and VPC Service Controls (VPCSC) to help protect your assets. 

Imagine you want to create a new prompt. With the SDK, it’s as easy as this:

code_block
<ListValue: [StructValue([(‘code’, ‘import vertexairnrn# Instantiate a clientrnclient = vertexai.Client(project=PROJECT_ID, location=LOCATION)rnrn# Define a prompt objectrnprompt = {rn “prompt_data”: {rn “contents”: [rn {rn “parts”: [rn {rn “text”: “Hello, {name}! How are you?”rn }rn ]rn }rn ],rn # variables replace templates in a prompt, i.e. {name} in this promptrn “variables”: [rn {rn “name”: {rn “text”: “Alice”rn }rn }rn ],rn “model”: “gemini-2.5-flash”rn }rn}rnrn# Create a prompt in Vertexrnprompt_resource = client.prompts.create(rn prompt=prompt,rn)’), (‘language’, ‘lang-py’), (‘caption’, <wagtail.rich_text.RichText object at 0x7fb50a28a040>)])]>

Prompt management in the SDK unlocks a world of possibilities to streamline your workflow. Work with the latest version of your prompt, easily view a comprehensive list of project prompts, and delete prompts that are extraneous to your team’s work. 

Get started today

It’s time to bring order to your prompt management workflow. With the new prompt management features in the Vertex AI SDK, you can build robust, scalable, and maintainable generative AI applications faster than ever.

To get started, check out the official Vertex AI documentation and explore our code examples.

We are excited to see what you build!

AI Generated Robotic Content

Recent Posts

An Introduction to Loop Engineering

It's tempting to treat loop engineering as something invented in a single week in June,…

20 hours ago

Best practices for applying Amazon Bedrock Guardrails to code generation workflows

This post continues our series on best practices with Amazon Bedrock Guardrails. For the previous…

20 hours ago

The Blueprint: How Voicify makes AI-enabled ordering a delight for customers

Welcome to The Blueprint, a new feature where we highlight how Google Cloud customers are…

20 hours ago

An FDA Panel Just Endorsed These Unproven Peptides

Outside experts—some with a vested interest in peptides—recommended adding a number of the amino acids…

21 hours ago

AI extracts hidden material rules from microscopic data to predict large-scale behavior

Researchers from the National University of Singapore (NUS) have developed artificial intelligence (AI) methods that…

21 hours ago

AI Teammates: how monday.com runs production AI agents on Amazon Bedrock

AI Teammates are agentic AI on Amazon Bedrock, and few engineering organizations run them in…

2 days ago