Designing Agent Workflows: Architecture for AI Automation

Dont start with the prompt. Start with the flowchart.

The Chain vs. The Graph

Most people start with a Chain: Step A - Step B - Step C.

Example: Summarize Email - Extract Tasks - Add to Trello.

This works until Step B fails. If the Extract Tasks step returns nothing, Step C crashes.

Professional Orchestrators build Graphs (specifically, State Machines).

Example: Summarize Email - Extract Tasks - (If Empty: Ask Human) OR (If Success: Add to Trello).

Key Patterns

1. The Router 🔀

The first node categorizes the input.

Is this a billing question? - Billing Agent.
Is this a tech support question? - Support Agent.
Why: Specialized agents outperform generalist agents.

2. The Map-Reduce 🗺️

You have 100 documents.

Map: Send each document to an agent to extract Key Risks. (Parallel execution).
Reduce: Send the 100 lists of risks to a final agent to Summarize Top 5 Risks.
Why: Overcomes context window limits and speeds up processing.

3. The Reflexion Loop 🪞

The agent critiques its own work.

Agent generates draft.
Agent evaluates: Does this meet the requirements?
If No: Regenerate with specific feedback.

Why: Massive quality boost for creative/coding tasks.

The Design Process

Happy Path: Draw the flow if everything goes right.
Sad Path: For every arrow, ask What if this fails?
State Definition: What data MUST pass from node to node?

Conclusion

A workflow is not a script. It is a system. Design it like one.

Next: [Human-in-the-Loop Patterns](/blog/human-in-the-loop-ai-patterns)

How This Article Was Made

This article is a live example of the AI-enabled content workflow we build for clients.

Stage	Who	What
Research	Claude Opus 4.5	Analyzed current industry data, studies, and expert sources
Curation	Tom Hundley	Directed focus, validated relevance, ensured strategic alignment
Drafting	Claude Opus 4.5	Synthesized research into structured narrative
Fact-Check	Human + AI	All statistics linked to original sources below
Editorial	Tom Hundley	Final review for accuracy, tone, and value

The result: Research-backed content in a fraction of the time, with full transparency and human accountability.

Why We Work This Way

Were an AI enablement company. It would be strange if we didnt use AI to create content. But more importantly, we believe the future of professional content isnt AI vs. Human—its AI amplifying human expertise.

Every article we publish demonstrates the same workflow we help clients implement: AI handles the heavy lifting of research and drafting, humans provide direction, judgment, and accountability.

Want to build this capability for your team? Lets talk about AI enablement →