Agentic Workflow
By Federico Donatone · Updated October 15, 2026An agentic workflow is a business process in which an AI agent handles some steps on its own: it plans the work, picks which tools to use, checks the result and tries again if it falls short. People define the goal, the limits and the approval points. Fixed automation, by contrast, follows the same steps every time.
Agentic workflow vs traditional automation
| Traditional automation | Agentic workflow | |
|---|---|---|
| Steps | Fixed in advance | Partly chosen by the agent |
| Inputs | Clean, structured fields | Messy text, web pages, transcripts |
| When something unexpected happens | Stops or errors | Tries another path or asks |
| Output | The same every run | Varies, so it needs review |
| Best for | Moving data between tools | Research, drafting, triage |
Most real systems mix the two. A fixed trigger starts the run, an agent handles the part that needs reading and judgment, and a fixed step routes the result to a person for approval. Keep the fixed parts fixed: an agent deciding when to run or where to send things adds risk without adding value.
Common agentic workflow patterns
- Plan, act, check: the agent writes a plan, carries it out with tools and checks the output against a definition of done.
- Reviewer loop: one agent drafts, a second checks the draft against written rules, and the first revises until it passes.
- Router: the agent reads an incoming item, such as an email reply, and sends it down the right path.
- Human in the loop: the agent prepares the work and stops for approval before anything leaves the company.
Real sales workflows often combine several of these. A reply-handling workflow, for example, routes each reply, drafts an answer, checks it against the rules and waits for a rep to approve it.
Agentic workflow examples in sales
- Call preparation: account research and CRM history turned into a sourced brief before each meeting.
- Follow-up: a call transcript turned into a recap and proposed next steps for the rep to approve.
- Inbox triage: incoming replies sorted into categories, with drafts ready for the ones that need an answer.
- List building: companies matched to the target profile, contacts found and emails verified before they reach a sequence.
Each of these ends with a person: a rep reads the brief, approves the recap, sends the reply or accepts the list. The agent saves the preparation time, and the person keeps the judgment and the relationship with the buyer.
How to choose your first agentic workflow
Pick a recurring job with inputs you can reach, an output a person can check and an owner for failures. Our guide to AI sales workflows compares candidates on these factors:
- How often the job runs and how long it takes today.
- Whether the inputs are complete and reachable.
- How long a person needs to review each output.
- How many tools and integrations it depends on.
- What a wrong result would cost.
Then write the definition of done before you build anything: what a finished output looks like, what the agent may never do, and how a reviewer will check it. That one document becomes the agent's instructions and the reviewer's checklist.
Run it on a small set of normal cases and exceptions, record corrections and review time, and expand only when the team can spot a bad result and recover from it. To see how one agent is built from rules, tools and a trigger, read how to build an AI agent with Claude. Once several workflows share files and tools, coordination matters as much as each agent, which we cover in how to manage multiple AI agents.