A little autonomy goes a long way
A workflow follows a predefined route. An agent can choose actions dynamically based on a goal and observations. Anthropic’s guide to effective agents distinguishes predefined workflows from more autonomous systems and recommends starting with the simplest approach that works. Translation: not every form submission needs a tiny project manager.
A fixed route might extract fields, validate them and create a draft. An agent loop might inspect a problem, choose a tool, read its result and decide what to do next. The diagram above is a conceptual loop, not a measured architecture. Both approaches can use models. The useful difference is who chooses the next step and how much freedom that choice creates.
The boring route can be the premium one
Our recommendation: use deterministic steps when the task and rules are well defined. Add model judgment only where it solves a real ambiguity. Use an agent when the path genuinely cannot be specified in advance and you can constrain its actions. LangGraph’s overview describes stateful orchestration; a framework can make state visible, but it cannot decide your business’s risk tolerance.
For a support request, an automated system could classify the topic and draft a response. Issuing a refund is a different permission. Reading an account is not authorization to change it. Keep the approval boundary before the irreversible step. This is our risk-control recommendation, informed by NIST’s risk-management framework, not a claim that a particular product enforces it by default.
Give the loop a budget and an ending
Define maximum steps, spending, allowed tools and a stopping condition before the run begins. “Keep going until done” sounds efficient until an unclear goal becomes a subscription to retries. A useful stop can be success, missing evidence, a tool error, a budget limit or a required human decision. Anthropic’s agent guidance discusses tool design, feedback and guardrails for this kind of system.
Log what the agent chose, what the tool returned and what changed. Do not store secrets casually in the trace. If the system repeats a write after a timeout, the business may see two actions even though the model thought it was trying once. Design writes to be safe to retry and keep an audit trail.
Check the permission slip
Exercise: An agent can research vendors and draft a comparison. Should it also be able to purchase the winner?
Answer: Not without a separately authorized purchase workflow, limits and review. Research access and spending authority are different capabilities. This is an illustrative design exercise; no purchase or platform test happened here.
The takeaway: autonomy is a dial, not a badge. Turn it up only after you know what the system can change, what it costs and how it stops.