Not every piece of AI-driven business logic needs an autonomous agent making decisions. Bedrock Flows gives deterministic, visual control over the path each request follows.
Bedrock Flows is a visual workflow builder that connects prompts, model invocations, Knowledge Bases, Agents, Lambda functions, and conditional logic into an explicitly defined pipeline, in contrast with the more open, self-directed behavior of an Agent that decides its own reasoning path. Where an Agent dynamically decides which tool to use and in what order, a Flow defines that order ahead of time -- useful when the business process is known and you need predictability, traceability, and per-step cost control.
The closest analogy is the difference between a ReAct agent and a Step Functions pipeline: Flows brings the deterministic structure of a workflow, but with native nodes for invoking foundation models, managed prompts, and semantic retrieval, without having to orchestrate that manually in Lambda.
A Flow is made up of nodes connected by arrows representing data flow. Node types include: Input (user input), Prompt (invoking a model with a managed prompt template via Bedrock Prompt Management), Knowledge Base (semantic retrieval), Agent (delegation to a Bedrock Agent), Lambda Function (custom business logic), Condition (branching based on a previous step's result), and Output (the flow's final output).
Bedrock Flows integrates natively with Prompt Management, which lets you define prompt templates with variables, version them, and test them in a playground before publishing to a production Flow. This separates iterating on prompt text from deploying application code -- a product team can adjust and version a prompt without touching the deployment pipeline, and every version stays auditable.
A Flow can combine Bedrock's three pillars in a single process: a Knowledge Base node retrieves document context, a Prompt node synthesizes an initial answer, a Condition node evaluates whether the case needs escalation, and if so, delegates to an Agent node that can execute actions (create a ticket, notify via Lambda). This avoids manually building that orchestration with application code that reimplements what Flows already manages visually and with versioning.
Every Flow has immutable versions and aliases (similar to the version/alias pattern for Lambda functions), letting you test a new flow version in a staging environment pointing at a different alias, and promote to production by switching the alias with no downtime. The visual editor includes a test mode that lets you run the flow with sample input data and see each node's result individually -- invaluable for debugging why a flow took an unexpected branch.
Step Functions remains the right tool for orchestrating general business processes that don't center primarily on foundation model invocations -- order processing, ETL pipelines, microservice coordination. Bedrock Flows is the right tool when the process is predominantly generative AI: classification, synthesis, semantic retrieval, and escalation decisions to an agent. In larger architectures, a Bedrock Flow can be invoked as a step within a broader Step Functions state machine, combining both where each contributes its strength -- general process determinism in Step Functions, and native generative AI orchestration in Flows.
Carlos Montiel is an enterprise AI solutions architect. He implements LLMs, Agents, RAG, and orchestrators for companies across Guatemala and Latin America. Reach out for a consultation.
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