Build Your First Agent

An AI agent is just a workflow with a clear job, clear inputs, and a clear definition of done. The fastest way to build one is to treat it like a small employee with a tight job description.

Start with one job

Pick a task that can be explained in five steps or fewer. Examples:

• Turn a brief into a draft
• Extract structured data from a page
• Rewrite copy to a specific voice

The smaller the job, the easier it is to test and refine. If you need a practice target, use a guide like Valentine's Day Melbourne 2026 as your input source.

Define inputs and outputs

Inputs are what the agent receives. Outputs are what you can ship. Write them down before you build anything.

• Input: raw text, URLs, or structured fields
• Output: a specific format (JSON, markdown, email, table)

If the output format is vague, the agent will be inconsistent. A fixed schema forces clarity.

Example output schema:

{
  "title": "string",
  "summary": "string",
  "highlights": ["string"],
  "warnings": ["string"],
  "source_url": "string"
}

Build a runbook

Write a short runbook for the agent:

1. Goal in one sentence
2. Required context (what it must know)
3. Output format (exact headings or schema)
4. Quality checks (what makes it unacceptable)

This runbook becomes your prompt and your QA checklist. It also makes handoffs easy when you bring in a teammate or reviewer.

Add guardrails early

Guardrails save you time later. Add them now:

• Word count or format constraints
• Do not guess missing data
• Cite the source section in the output
• Use placeholders like [NEEDS REVIEW] when unsure

Also add a clear rejection rule. For example: "If the input does not mention a location, return a one-sentence request for clarification."