Onboarding and operations
Client onboarding
Turns a new client request into a repeatable checklist, workspace setup, and team notifications.
See code on GitHubAI Automation Specialist
Practical AI systems that help teams work better.
Five automation highlights, five agent patterns, and the public code behind them. Simple enough to understand quickly; structured enough to review seriously.
Sanitized public examples
Public repositories explain the system and show safe code or patterns. Production credentials, private records, client names, and live endpoints are not included.
AI Automation
Five highlights.
Each one starts with a repeated task, connects the right tools, and leaves the important judgment with a person.
Content and SEO
Content and SEO handoff
Collects research and prepares a working document so the next person can review instead of rebuilding the work.
See code on GitHubReports and notifications
Reports and notifications
Turns a scheduled event or connected record into the right report or message for the right person.
See code on GitHubOperations
Client offboarding
Moves closing steps through one visible process so access, records, and handoff are not forgotten.
See code on GitHubIntegrations
Data sync and cleanup
Keeps connected tools aligned and reduces duplicate records, repeated updates, and manual checks.
See code on GitHubWant the full automation library?
The public GitHub library contains 80+ sanitized workflow descriptions organized by need, trigger, action, and result.
Explore the libraryAI Agents
The same idea, with more context.
Agents are useful when they have a clear job, useful context, boundaries, and a human handoff.
Reporting
Reporting agent
Turns recurring reporting work into a guided process with clear inputs, outputs, and human review.
See code on GitHubPersistent context
Executive assistant
Keeps business context, rules, decisions, and reusable skills in one version-controlled home.
See code on GitHubOrchestration
Sub-agent delegation
Breaks heavy work into smaller tasks with their own context, then brings the useful result back.
See code on GitHubGovernance
Human-in-the-loop review
Lets the model prepare work while a person keeps the decision, approval, or publication control.
See code on GitHubKnowledge systems
Knowledge operating system
Connects files, procedures, and decisions so an assistant can use the right context at the right time.
See code on GitHubWhat makes an agent trustworthy?
The model does not own the whole process. Deterministic code handles rules and integrations; the person stays responsible for approval, sensitive decisions, and final publication.
AI-built, technically managed
The tool matters. The delivery discipline matters too.
The CRM, AI content production system, syndicator, and this website were built with AI-assisted development. I present them as technical projects because the work also includes scope, architecture, integrations, risk controls, testing, documentation, and handoff.