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AI agents vs AI workflows
The two words get used interchangeably and they describe genuinely different architectures. The distinction is simple: an agent chooses its own next step at run time, and a workflow's next step was chosen when someone wrote it down.
The short version
Where the decision about "what next" is made
AI agents
An AI agent is a model given tools and a goal. Each turn it decides which tool to call, reads the result, and decides again, until it judges the goal met. Nobody enumerated the path, which is exactly why it copes with situations nobody enumerated.
Murmurator
An AI workflow is a defined sequence with model calls inside it. The order, the branches and the actions are written down; the model is asked specific questions at specific points. You know before it runs what it can reach and roughly what it will do.
Neither is a more advanced version of the other. They trade the same currency in opposite directions: flexibility at run time against knowability beforehand.
Be honest about this bit
When autonomy is worth it
Autonomy is not a compromise you make — for some work it is the only thing that works.
- The input is unpredictable enough that no fixed sequence covers it
- The task is exploratory: investigate this, find out why, work through this codebase
- You cannot list the steps in advance because discovering them is the task
- The work is read-mostly, or reversible, so an unexpected path is inexpensive
- A person is reading the result and will catch a wrong turn
A good rule of thumb: if you could write down the steps, you probably should. If writing them down would take longer than the task, an agent is doing something a workflow cannot.
Where we fit
When structure is worth it
Structure buys a specific set of properties. If you need them, no amount of prompt engineering substitutes.
- Repeatability: two runs of the same input take the same route
- Reviewability: someone can read what will happen before it happens
- Bounded authority: what it may touch is a scoped connection, not a sentence in a prompt
- Auditability: the record of a run answers what happened, with evidence
- Shared ownership: the process belongs to the organization rather than to its author
- Cost control: tokens, money and wall-clock time have ceilings that are enforced, not requested
The shape of it
The two shapes
Agent
The loop is the architecture. Every arrow after the goal was chosen by the model while it was running.
Workflow with AI steps
The arrows were chosen by whoever wrote it. The model answers a specific question at a specific point, and what happens to the answer is already decided.
A workflow with an agent step
These are not mutually exclusive. An agent can be one node in a workflow, with its tool list, turn limit and budget declared by the definition around it — autonomy inside a boundary somebody drew on purpose.
A model decides here The definition decides here
Side by side
What each one gives you
How to read this table. The Murmurator column is checked against this product's own documentation. The AI agents column is marked only where the answer is a stable, documented property; everywhere else it says varies and describes the shape of the answer, because their product is theirs to change and we would rather send you to their docs than guess. There are no scores here, and no winner. Both columns describe architectures rather than specific products, so neither is a feature list.
| Property | Murmurator | AI agents |
|---|---|---|
| Handles input nobody anticipated | Inside its model steps. The structure around them does not adapt, and that is deliberate. | The defining strength. |
| Same route every run | The route is the definition. | The route is a run-time decision. |
| Knowable before it runs | Read the definition and you know what it can reach and which branch runs when. | You know the goal and the tool list, not the path. |
| Bounded authority | Per-step, and declared. Each step reaches one scoped connection. | Usually the union of everything its credentials allow. |
| Easy to change safely | A diff, an author and a version. The change is visible before it runs. | Editing a prompt changes behaviour in ways that are hard to predict or review. |
| Effort to a first version | Someone has to decide what the steps are — which is often the useful part. | Low. A goal and some tools. |
| Fits work nobody has defined yet | A workflow is a process you already decided on. | This is what agents are for. |
| Cost predictability | Bounded by the number of steps, and by explicit budgets. | Bounded by the loop limit, which is a much looser bound. |
More on how this fits together
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