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Auteryn

Best Practices & Patterns

These guides cover writing instructions, preparing Knowledge, testing, and security.

Getting Started

Section titled “Getting Started”
Writing Effective Agent InstructionsHow to write clear, actionable instructions that get the results you want.
Knowledge OptimizationStructure your data for maximum agent performance and accuracy.
Testing & Quality AssuranceTest your agents thoroughly before deploying to production.

By Use Case

Section titled “By Use Case”
Customer Support AgentsSupport agents that answer from Knowledge and hand off the hard cases.
Code Review AgentsPR reviews and issue triage on GitHub Loops.
Data Analysis AgentsScheduled agents that query your data and report back.

Deep Topics

Section titled “Deep Topics”
Security & ComplianceKeep your agents secure and compliant with regulations.

Quick Tips

Section titled “Quick Tips”

Do’s ✅

Section titled “Do’s ✅”
  • Be specific - Clear instructions get better results
  • Test thoroughly - Try edge cases before deploying
  • Start simple - Add complexity gradually
  • Monitor actively - Review conversations regularly
  • Iterate often - Improve based on real usage
  • Document everything - Keep track of what works

Don’ts ❌

Section titled “Don’ts ❌”
  • Don’t be vague - “Be helpful” isn’t enough guidance
  • Don’t skip testing - Production isn’t the place to debug
  • Don’t over-complicate - Simple agents are more reliable
  • Don’t set and forget - Agents need ongoing refinement
  • Don’t ignore feedback - Users tell you what needs fixing
  • Don’t expose secrets - Never put API keys in instructions

Common Patterns

Section titled “Common Patterns”

Pattern 1: Escalation Workflow

Section titled “Pattern 1: Escalation Workflow”

When to use: Support agents that need human backup

1. Agent attempts to answer
2. If the answer isn't in Knowledge, ask clarifying questions
3. If still uncertain, escalate to human
4. Human reviews context and takes over

Pattern 2: Multi-Step Validation

Section titled “Pattern 2: Multi-Step Validation”

When to use: Agents that perform actions (not just chat)

1. Agent proposes action
2. Show user what will happen
3. Get explicit confirmation
4. Execute action
5. Confirm completion

Pattern 3: Knowledge Fallback

Section titled “Pattern 3: Knowledge Fallback”

When to use: Agents with multiple information sources

1. Check primary knowledge
2. If no answer, check secondary sources
3. If still no answer, search web (if enabled)
4. If nothing found, admit uncertainty

Performance tips

Section titled “Performance tips”

Guidelines for evaluating agent quality in your environment:

Metric Starting target Notes
Response time Under a few seconds (Fast mode) Deep mode takes longer by design
Accuracy Validate against your Knowledge Depends on instructions and Knowledge quality
Escalation rate Tune per use case Support agents should escalate when uncertain
Resolution rate Measure in your pilot Track before scaling to production

Learning Path

Section titled “Learning Path”

Week 1: Foundations

  1. Read Agent Instructions Guide
  2. Complete Interactive Quickstart
  3. Build your first agent

Week 2: Optimization

  1. Read Knowledge Optimization
  2. Read Testing Guide
  3. Refine your agent based on testing

Week 3: Production

  1. Read Security Best Practices
  2. Monitor your agent’s performance
  3. Deploy to production with monitoring

Week 4: Scale

  1. Optimize based on usage patterns
  2. Implement error handling strategies
  3. Scale to handle more traffic

Get Help

Section titled “Get Help”

Contributing

Section titled “Contributing”

Have a best practice to share? Email support@auteryn.ai.