In agentic systems that use parallel execution, Merging Strategies are the specific techniques used during the fan-in phase to combine the outputs from multiple concurrent branches into a single, useful result. Since each parallel branch produces its own output, the orchestrator needs a predefined method for consolidating them before proceeding. The choice of strategy is critical and depends entirely on the nature of the task.
Common merging strategies include:
- Concatenation: The simplest strategy, where outputs are joined together into a single list or document. This is suitable when the outputs are distinct sections of a larger whole, such as different parts of a research report.
- Voting: Used when multiple agents perform the same task to improve reliability. The final answer is determined by a majority vote among the different outputs. This is common in classification or decision-making tasks.
- Structured Aggregation: When parallel tasks are designed to contribute different fields to a single data object. For example, one agent might fetch a company’s revenue, another its employee count, and the fan-in step aggregates these into a single company profile JSON object.
- Synthesis: A more advanced strategy where a dedicated “synthesis” agent receives all the parallel outputs and is tasked with creating a new, higher-level summary or analysis that incorporates the insights from all branches.
The merging strategy must be chosen during the design of the workflow, as it directly influences how the fan-out branches should be structured and what kind of output they are expected to produce.