Autoblocks V2 represents a complete reimagining of the platform, designed to deliver a dramatically improved experience for both technical and non-technical stakeholders. We’ve streamlined workflows, enhanced performance, and introduced powerful new capabilities that make building, testing, and deploying AI applications faster and more intuitive than ever before.
Before you begin, contact us to get access to the V2 platform.You will also need to set the AUTOBLOCKS_V2_API_KEY environment variable to your V2 API key.
Autoblocks V2 introduces a completely overhauled tracing system built on top of OpenTelemetry, providing industry-standard observability for your AI applications. This new architecture offers enhanced performance, better integration capabilities, and more comprehensive insights into your AI workflows.Key improvements in V2 tracing include:
OpenTelemetry Integration: Native support for OpenTelemetry standards
Enhanced Performance: Faster trace collection and processing
Better Debugging: More detailed span information and error tracking
AI-Specific Instrumentation: Automatic tracing of LLM calls with token usage and performance metrics
To get started with the new tracing system, see our comprehensive documentation:
Testing in Autoblocks V2 remains largely unchanged from V1, with only minor updates required for migration. The core testing framework and API stay the same, making this one of the smoothest transitions in your migration process.What’s Changed:
Import Updates: Update your imports to use the V2 client
Tighter Tracing Integration: Testing is now more closely integrated with the tracing system for better observability
Migration Requirements:
Update Imports: Change your import statements to use the V2 client package
Initialize Tracer: You’ll need to initialize the tracer to take advantage of the improved testing and tracing integration
What Stays the Same:
Test case structure and format
Evaluator API and functionality
Test suite configuration
CI/CD integration patterns
For detailed setup instructions and examples, see our testing documentation:
Prompt Management in Autoblocks V2 maintains the same core functionality you know from V1, but is now organized around an app-based structure for better organization and scalability. The API and workflow remain familiar, making migration straightforward.What’s New:
App-Based Organization: Prompts are now structured and organized by application
Enhanced Type Safety: Improved autocomplete and type checking across TypeScript and Python
Better Scalability: Cleaner organization for managing prompts across multiple projects
What Stays the Same:
Core prompt management API and functionality
Version control and deployment patterns
Template rendering and parameter handling
CI/CD integration capabilities
The migration process is smooth since the underlying prompt management concepts remain unchanged - you’ll primarily need to adapt to the new app-based organization structure.For detailed setup and migration instructions, see our prompt management documentation:
Datasets in Autoblocks V2 provide flexible test case and data management with enhanced schema versioning and organization capabilities. The system supports both programmatic and web-based management approaches.For comprehensive information on working with datasets, including schema management, dataset splits, and integration options, please refer to our API reference documentation:
Human Review in Autoblocks V2 maintains the familiar experience you know from V1, while introducing powerful new capabilities for better customization and collaboration.What Stays the Same:
Core human review workflow and interface
Review job creation and management
Evaluation and scoring processes
What’s New and Improved:
Configurable UI Fields: Customize which fields are displayed in the review interface for a cleaner, more focused experience
Multiple Rubrics per App: Create and manage multiple evaluation rubrics within a single application for different review scenarios
Multi-Person Assignment: Assign review jobs to multiple reviewers simultaneously for collaborative evaluation and consensus building
These enhancements make human review more flexible and scalable while preserving the intuitive workflow that teams already know and rely on.