Carter Shannon
Portfolio/AI & Automation
Work area 01

AI & Automation

Automation first, AI where judgment lives. The routine steps get deterministic automation; AI is added only where rules stop working.

Process automation auditWorkflow automation buildAI at judgment stepsAgentic system design
Focus area 1 of 4

Process automation audit

A two-week style mapping of where the hours actually go. I document each workflow, score it for automation fit, and rank the roadmap by payback instead of gut feel.

What I built

  • A process map of the workflows that absorb the most manual hours
  • Each workflow scored for automation fit, effort, and payback
  • A ranked automation roadmap with build sequence and implementation notes

How I approach it

  1. Week one: shadow the work, pull the numbers, and map the workflows
  2. Week two: score and rank every workflow, then pressure-test the assumptions with operators
  3. Delivery: the roadmap, the reasoning, and the implementation path
Proof: The SMB automation deck
Focus area 2 of 4

Workflow automation build

Deterministic automation for the routine steps: invoicing, data entry, scheduling, reporting, onboarding. Rules-based automation is fast, auditable, and cheap to run, which is why it comes before any AI. The build is modular, so intelligence can layer on later without rework.

What I built

  • Working automations in production, not recommendations on a slide
  • An audit trail for every automated step
  • Documentation and operating notes so the result can keep running

How I approach it

  1. Start from the audit roadmap, highest payback first
  2. Ship the first automation quickly, then expand workflow by workflow
  3. Handoff: monitoring in place and the operating owner trained to run it
Proof: The SMB automation deck
Focus area 3 of 4

AI at judgment steps

Most process steps are rules. Some need judgment: classifying a messy request, drafting a reply, triaging what matters. This focus area adds AI to exactly those steps and nowhere else, with human checkpoints where the cost of a wrong answer is real.

What I built

  • AI on the steps where rules stop working: classification, drafting, triage
  • Human checkpoints designed into the flow, not bolted on
  • Clear measurement of what the AI step catches and what it hands off

How I approach it

  1. Identify the judgment steps inside an automated flow
  2. Add AI to one step at a time and measure it against the human baseline
  3. Expand only what earns it; keep checkpoints where stakes are high
Focus area 4 of 4

Agentic system design

Multi-agent systems that carry real knowledge work from a one-line instruction to a finished, quality-checked result. The design principle is separation of duties: agents that produce are never the agents that grade, and every output passes a defined quality bar before it ships.

What I built

  • An agent workflow designed around a real work product
  • Quality gates: review and revision loops with defined ship criteria
  • A system an operating team can run, monitor, and extend

How I approach it

  1. Define the work product and the quality bar it must clear
  2. Design the agent roles and the review loop between them
  3. Pilot on real work, tune the gates, then document the operating model
Proof: DeckForgeProduct Team Loop
Where this appears in my work These pages document the methods, systems, and examples behind my portfolio.
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