Agentflow
A meta-framework for composing multi-step, tool-using agents with routing, memory, and validation built in.
Agentflow (e.g., LangGraph-style graphs) models agent systems as stateful workflows with nodes for planning, tool use, reflection, and routing. It replaces ad-hoc loops with defined state transitions.
In operations, Agentflow is used to orchestrate retrieval, tool calls, critique loops, and human escalation. State is carried explicitly, making runs debuggable and resumable.
It fits between orchestration and model calls, giving teams a reproducible graph for agent behavior. The impact is fewer runaway loops, better observability, and faster iteration on agent logic.
Frequently Asked Questions
How is Agentflow different from a simple agent loop?
It makes each step explicit—nodes for plan, act, evaluate—so you can branch, retry, or escalate deterministically instead of relying on free-form prompting.
When should I use Agentflow?
When agents need multiple tools, branching, or human checkpoints. It shines in workflows that must be debuggable and replayable.
How do I keep Agentflow runs safe?
Add guardrails at tool nodes, cap iterations, use idempotent actions, and enforce budgets for time and cost.
Can Agentflow include humans?
Yes—add human approval/review nodes with SLAs. Pass full state so reviewers can decide quickly.
How do I test an Agentflow graph?
Use fixtures for inputs, simulate tool responses, and assert on state transitions. Replay past traces to catch regressions.
What monitoring should I add?
Track node-level latency, success/fail reasons, loop counts, and tool costs. Alert on stalled or runaway runs.
How do I handle failures mid-graph?
Define fail-safe branches, retries with backoff, and DLQs for bad tool outputs. Persist state so runs can resume.
Does Agentflow work with any model?
Yes—it's model-agnostic. You can route to different models per node based on cost/quality needs.
How do I evolve an Agentflow safely?
Version the graph, run canaries, and compare metrics before full rollout. Keep rollback paths ready.
Agentic AI
An AI approach where models autonomously plan next steps, choose tools, and iterate toward an objective within guardrails.
Agentic Workflow
A sequence where an AI agent plans, executes tool calls, evaluates results, and loops until success criteria are met.
Agent Handoff
A pattern where one AI agent passes context and state to another specialized agent to keep multi-step automation modular.
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