What is an agentic workflow?
An agentic workflow is a process an AI agent carries out over several steps, deciding what to do next at each one rather than following a fixed script.
"Agentic workflow" is the term teams reach for when automation stops being a flowchart. It names the shift from encoding every branch in advance to *letting a model decide the next step from what it just found*.
Fixed automation vs agentic workflow
| Fixed automation | Agentic workflow | |
|---|---|---|
| Path through the work | Decided at build time | Decided per run |
| Handles unexpected input | Fails, or ignores it | Reasons about it |
| Reading unstructured text | Needs a parser per format | Native |
| Predictability | Total | Bounded, not exact |
| Failure mode | Loud and deterministic | Plausible and quiet |
| Testing | Enumerate the branches | Sample runs and judge |
The last two rows are the trade. You gain the ability to handle input nobody anticipated, and you lose the guarantee that identical input produces identical output.
What "agentic" actually adds
A traditional automation for triaging support mail needs a rule per case: this subject line means billing, this sender domain means enterprise, this phrase means urgent. Every case somebody did not think of falls through.
An agentic version reads the message and decides. It handles the ticket written in the wrong tone, in a second language, describing a problem your rule list has never seen. That is genuinely new, and it is why the category exists.
The cost is that "decides" is not "computes". Two runs on similar input can reach different conclusions, which is fine for classification and unacceptable for arithmetic. The judgement worth making is which parts of a job want a model and which want code.
Agentic workflow, or AI worker?
The two terms overlap heavily and are often used interchangeably. Where they differ is what each one names:
- An agentic workflow names the pattern: multi-step, model-directed work.
- An **AI worker** names the configured thing that does one such job unattended, with its own key, its own app permissions, a schedule and a receipt.
You can have an agentic workflow that you drive by hand in a chat window. You cannot have a worker without the identity, the permissions and the trigger, because those are what "unattended" requires.
WorkerKit's own documentation treats "agentic workflow" as the phrase some teams use for what it calls a worker, which is fair: the same shape, named from the process side rather than the object side.
What one looks like in practice
Meeting Prep Assistant is a clear multi-step example. It reaches calendar, email, meeting notes and CRM, and a single run:
- Lists the meetings on the day's calendar
- For each one, works out who is attending and what matters about them
- Searches email for the relevant recent history
- Pulls the CRM record where there is one
- Reads prior meeting notes for open items
- Writes one prep sheet per meeting
Step 2 changes what steps 3 to 5 look for. That dependency, where the output of one step shapes the next, is what makes it agentic rather than a pipeline. A fixed script would need every branch enumerated in advance.
What it costs to run one
Multi-step means multiple tool calls, and the count scales with what the run finds rather than with a fixed plan:
| Meetings that day | Rough tool calls | Notes |
|---|---|---|
| 2 | ~10 | Two lookups per meeting plus the calendar read |
| 5 | ~22 | Roughly linear in meetings |
| 10 | ~42 | Still inside Free's 500 a day |
That variability is characteristic. A fixed automation costs the same every run; an agentic one costs what the day contained. It is worth knowing before you set a cadence, because a busy day is also the expensive day.
The failure mode
Fixed automation fails loudly: a parser throws, a field is missing, the job stops. You find out because something is red.
An agentic workflow fails plausibly. It produces a prep sheet that reads perfectly and attributes a comment to the wrong person, or classifies a ticket into a category that is defensible but wrong. Nothing is red. The work looks done.
That is why the surrounding machinery matters more than it does for traditional automation: a receipt per run showing what it read and did, hard caps so a confused run cannot loop expensively, and access limited to what the job needs so a wrong decision has a small blast radius.
The reasonable objection
"Non-determinism is disqualifying. I cannot put something in production that gives different answers to the same question."
Right for some jobs, and the honest response is to keep those jobs deterministic. Nobody should compute an invoice total with a model.
The jobs where it holds up are ones where a human was already the non-deterministic component. Two support agents triage the same queue slightly differently; two people summarising a meeting produce different notes. Replacing a human judgement call with a model judgement call does not introduce variance, it changes who is varying, and it makes the variance inspectable through receipts in a way a person's reasoning never was.
When not to reach for one
- The rules are complete and stable. If a flowchart covers every case, build the flowchart. It is cheaper, faster and exact.
- The output must be exact. Money, quantities, identifiers. Use code.
- The job runs once. The setup cost is not recovered.
- Mistakes are unrecoverable. Start where the downside is a nuisance.
The strongest pattern is usually a mix: a model for reading and deciding, code for calculating and committing. A kit is that mix already assembled for one job.
FAQ
What is the difference between an agentic workflow and an AI worker?
An agentic workflow and an AI worker describe the same shape from two angles. "Agentic workflow" names the pattern of multi-step, model-directed work. An AI worker names the configured thing that performs one such job unattended, with its own key, per-app permissions, a schedule or trigger, and a receipt for every run.
How is an agentic workflow different from normal automation?
Fixed automation follows a path decided at build time and fails on input nobody anticipated. An agentic workflow decides the next step from what it just found, so it handles unstructured and unexpected input, at the cost of exact repeatability.
Are agentic workflows reliable enough for production?
For jobs where a human was already the judgement call, generally yes, provided the surrounding controls exist: narrow access, hard caps, and a record of every run. For jobs requiring exact output, such as calculations, use code.
How much does an agentic workflow cost to run?
The cost of an agentic workflow varies with what each run finds rather than being fixed. A multi-step worker might use 10 tool calls on a quiet day and 40 on a busy one. Free allows 500 a day, Pro 5,000, and Team 50,000 pooled, with model tokens billed separately at provider list price with no markup.
Do I need to build an agentic workflow myself?
No. A worker kit is one already built and tested for a specific job, including the instruction, the app permissions and the schedule. Browse the directory to see what exists before writing one.