Build a useful AI agent workflow
A practical guide to sources, permitted actions, human review and acceptance checks.
1. Start with a business outcome
Define one measurable task: answer known support questions, prepare a CRM draft or route an appointment request. Specify what a person should receive at the end.
2. Choose the source of truth
Use an approved knowledge base or business dataset. Know its owner, update process and access rules. If the source does not support an answer, route to a person.
3. Define the permitted actions
Keep reads, drafts and external writes separate. A sample preview can prepare a draft; production writes need permission, validation, logs and failure handling.
4. Put a person at the review gate
A reviewer should see the input, relevant source and proposed action. Changes to the request invalidate an old approval. Escalate ambiguous or unsupported requests.
5. Test the complete path
Check normal inputs, missing context, provider failure, retries and duplicate submissions. Agree acceptance criteria and costs before connecting production systems.
6. Compare sample and production
The KK Cyber builder is a local rule-based simulation. A production AI agent requires a configured model/provider, approved sources, permitted integrations and monitoring. Use the sample to discuss scope, not as a claim that a live model is running.