Basics
Understanding how workflows execute in TradingGoose is key to building efficient and reliable automations. The execution engine automatically handles dependencies, concurrency, and data flow to ensure your workflows run smoothly and predictably.
How Workflows Execute
TradingGoose's execution engine processes workflows intelligently by analyzing dependencies and running blocks in the most efficient order possible.
Concurrent Execution by Default
Multiple blocks run concurrently when they don't depend on each other. This parallel execution dramatically improves performance without requiring manual configuration.
For example, if a Start block connects to both a Customer Support agent and a Deep Researcher agent, both agent blocks execute simultaneously, maximizing efficiency.
Automatic Output Combination
When blocks have multiple dependencies, the execution engine automatically waits for all dependencies to complete, then provides their combined outputs to the next block. No manual combining required.
For example, a Function block connected to two upstream agent blocks will wait for both to finish, then receive their combined outputs for processing.
Smart Routing
Workflows can branch in multiple directions using routing blocks. The execution engine supports both deterministic routing (with Condition blocks) and AI-powered routing (with Router blocks).
For example, a workflow might branch after an initial block into a Condition block (which evaluates a logical expression) and a Router block (which uses AI to choose a path). Each resulting branch executes independently.
Block Types
TradingGoose provides different types of blocks that serve specific purposes in your workflows:
Triggers
Starter blocks initiate workflows and Webhook blocks respond to external events. Every workflow needs a trigger to begin execution.
Processing Blocks
Agent blocks interact with AI models, Function blocks run custom code, and API blocks connect to external services. These blocks transform and process your data.
Control Flow
Router blocks use AI to choose paths, Condition blocks branch based on logic, Loop blocks iterate over items or counts, and Parallel blocks handle concurrent iterations.
Utility Blocks
Response blocks format final outputs for APIs and chat interfaces. Variables blocks manage workflow-scoped data. Wait blocks pause execution for a duration. Evaluator blocks assess and score outputs.
All blocks execute automatically based on their dependencies - you don't need to manually manage execution order or timing.
Execution Triggers
Workflows can be triggered in several ways, depending on your use case:
Manual Testing
Click "Run" in the workflow editor to test your workflow during development. Perfect for debugging and validation.
Scheduled Execution
Set up recurring executions using cron expressions. Great for regular data processing, reports, or maintenance tasks.
API Deployment
Deploy workflows as HTTP endpoints that can be called programmatically from your applications.
Webhook Integration
Respond to events from external services like GitHub, Stripe, or custom systems in real-time.
Chat Interface
Create conversational interfaces hosted on custom subdomains for user-facing AI applications.
Learn more about each trigger type in the Triggers section of the documentation.
Execution Monitoring
When workflows run, TradingGoose provides real-time visibility into the execution process:
- Live Block States: See which blocks are currently executing, completed, or failed
- Execution Logs: Detailed logs appear in real-time showing inputs, outputs, and any errors
- Performance Metrics: Track execution time and costs for each block
- Path Visualization: Understand which execution paths were taken through your workflow
All execution details are captured and available for review even after workflows complete, helping with debugging and optimization.
Key Execution Principles
Understanding these core principles will help you build better workflows:
- Dependency-Based Execution: Blocks only run when all their dependencies have completed
- Automatic Parallelization: Independent blocks run concurrently without configuration
- Smart Data Flow: Outputs flow automatically to connected blocks
- Error Handling: Failed blocks stop their execution path but don't affect independent paths
- State Persistence: All block outputs and execution details are preserved for debugging
Next Steps
Now that you understand execution basics, explore:
- Block Types - Learn about specific block capabilities
- Logging - Monitor workflow executions and debug issues
- Cost Calculation - Understand and optimize workflow costs
- Triggers - Set up different ways to run your workflows