Start with a goal you can check.
A person defines the outcome, scope, constraints and acceptance criteria. For example: explain a service failure and prepare a recovery proposal, with read-only access during investigation.
HOW AGENTIC WORKFLOWS WORK
A goal. A plan.
A governed path forward.
An agentic workflow lets an AI system choose useful next steps, use tools and adapt to what it discovers. Engineering makes those steps bounded, observable and reviewable.
Give the agent relevant context.
Read approved documentation, current project notes and system evidence through scoped tools. Record where information came from and when it was checked.
Turn findings into a bounded next step.
The agent produces a proposed change, assumptions, risks and verification plan. A second review can challenge the proposal before a person decides.
Make authority explicit.
A person reviews the evidence and grants a specific action where required. A task comment or an agent-generated plan is never a substitute for an enforceable permission boundary.
Close the loop with evidence.
Check the result against acceptance criteria, capture failures and save a durable handoff. A successful tool response is only one part of proving the intended outcome.
WHERE THIS CAN HELP
Useful work. Measurable outcomes.
Operational investigation
Assemble logs, recent changes and runbooks into a diagnosis with source references. People review the proposed remediation.
Change preparation
Draft configuration or code changes alongside a verification and rollback plan. Deployment remains a separate, authorised step.
Engineering knowledge
Reconcile documentation with accepted evidence, identify gaps and prepare a handoff another engineer or agent can use.
CHOOSE THE RIGHT LEVEL OF AUTOMATION
Agentic where it helps.
Predictable where it matters.
Fixed processes often suit conventional automation. Agents are useful when interpreting context, investigating ambiguity or preparing options. The strongest workflow can combine both, with explicit escalation when evidence is missing or a boundary is reached.
AN ENGINEERING EXAMPLE
An integration stops.
The investigation moves forward.
Imagine an overnight integration has stopped delivering expected files. The team needs an explanation and a safe recovery proposal. This is an illustrative workflow, rather than a claim about a deployed customer system.
- 01
Gather the relevant evidence
The agent reads approved job logs, the runbook and recent change records. It records timestamps and references so a reviewer can distinguish current observations from older documentation.
- 02
Explain the likely failure
It compares the observations with the expected process and identifies missing evidence. If the cause is uncertain, it asks for the next useful check instead of presenting a guess as a finding.
- 03
Prepare a recovery proposal
The proposal describes the intended action, its scope, possible duplicate processing, rollback and verification. The responsible engineer decides whether that action is appropriate.
- 04
Verify the business outcome
After an authorised recovery, check that the expected files reached the intended destination and were processed correctly. A job returning success does not establish that downstream outcome by itself.
MEASURE THE USEFULNESS
Judge the result
against the real task.
A pilot can track time to a reviewable diagnosis, the number of unsupported claims, and the amount of correction a reviewer needs to make. Include the time people spend checking the result, as well as the time the agent spends generating it.
Look for a handoff another engineer can use: clear sources, known uncertainties, a decision record and verification evidence. Those qualities make a workflow useful even when the right next step is to escalate to a person.
LET’S FIND YOUR FIRST WORKFLOW