Map lifecycle logic
Translate your lifecycle stages into explicit entry conditions, branches, waiting rules, exit criteria and ownership of each customer-facing action.
Managed AI staffing
Lifecycle workflows that do what your customer journey calls for.
Turn your lifecycle plan into working marketing operations. Your AI marketing automation specialist prepares workflows, maintains audience logic and tests handoffs, giving your team visibility into how contacts enter, move through and leave each process before changes reach the intended audience.
Find my AI workerBuild a free role brief Responsibilities, handoffs and quality measures. No signup.
The job behind the title
Automation becomes difficult to trust when contact rules overlap or no one remembers why a branch exists. Marketing teams need documented logic, meaningful tests and a clear view of the messages and updates each workflow can trigger.
Responsibilities
We shape these responsibilities around your systems, priorities and decision permissions.
Translate your lifecycle stages into explicit entry conditions, branches, waiting rules, exit criteria and ownership of each customer-facing action.
Build the agreed field updates, assignments and communications using the systems and permissions included in the role plan.
Run representative test cases through the planned logic, checking exclusions, repeat entry, missing fields and transitions between connected workflows.
Document changes, investigate unexpected behavior and prepare reports showing where contacts stall, exit or enter a path that needs review.
A clear handoff
Illustrative workflow
An example of how the work could run, tailored during onboarding. This is not a customer case study.
A software company wants trial users to receive different onboarding guidance based on setup progress. Existing messages are scheduled by signup date and sometimes continue after a customer has converted.
The specialist maps the approved lifecycle events, configures the paths and tests missing-event, completed-setup and converted-customer cases before the team reviews the release.
A required activation event is not consistently recorded. The specialist flags the data dependency and proposes an observable alternative for approval instead of treating absent data as customer behavior.
Onboarding & continued development
We learn the job, your expectations and how your team works. Then we select and configure an AI worker for the role.
We help your bot learn your systems, policies and preferences. Together, we review its work and prepare it for the responsibilities you agree on.
We stay involved, review performance and continue coaching your bot. You have a human Botsource contact when the work needs attention.
We agree on targets and review methods together. These are proposed measures, not claimed results.
Before you get started
The role can document and maintain the workflows you already use, starting with their triggers and customer-facing actions. We identify overlapping rules and dependencies before introducing changes that could affect existing contacts.
We define representative cases for each important branch, including missing information and exit conditions. The specialist records the expected behavior and observed result so the owner can review the change before release.
Your permission model determines which changes can be made directly and which require review. The role plan also covers version history, release checks and how to respond when a workflow behaves unexpectedly.
Start with the job
Tell us what the role needs to accomplish. We’ll talk through responsibilities, systems, onboarding and how you want to measure performance.
You’ll leave the assessment with a clearer role plan and next steps for preparing the right AI worker.
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