Best Practices for Building Great Agents
Building an effective AI agent isn’t just about technology—it’s about creating conversations that feel natural and helpful. Follow these proven best practices to build agents your customers will love.1. Keep Responses Short & Conversational
The Problem: Long-winded agent responses frustrate users and make them abandon the chat. Best Practice: Aim for 1-2 sentences maximum per response. Users want quick, actionable answers. Examples: Good:- “Your order #12345 shipped today! Check the link for tracking info.”
- “We’re open 9am-6pm EST. How can I help?”
- “Thank you for inquiring about our order status. We are delighted to inform you that your order number 12345 has been processed through our fulfillment center and has been dispatched with our carrier. The tracking information is available at the following link…”
- Mobile users skim, not read
- People expect instant responses
- Short = easier to understand
- Users can ask follow-ups if needed
2. Guide Users with Buttons & Clear Options
The Problem: Open-ended questions confuse users and lead to poor agent responses. Best Practice: Use buttons to guide users through logical conversation paths. Examples: Good flow:- Agent: “What can I help with?” + [View Orders] [Track Shipment] [Return Item] buttons
- User clicks [Track Shipment]
- Agent: “Enter your order number or email”
- User provides info
- Agent: “Order #12345 shipped on 12/10, arrives 12/15” + [Get Tracking Link] button
- Agent: “What do you want?”
- User types something unclear
- Agent: “I don’t understand”
- User gives up
- Reduces misunderstandings
- Faster conversations
- Users know what options exist
- Lower support burden
3. Handle “I Don’t Know” Gracefully
The Problem: If agent can’t answer, users get frustrated and abandon chat. Best Practice: Always have helpful fallback responses for things outside the agent’s knowledge. Examples: Good fallback responses:- “I’m not sure about that. Let me connect you with our team. They’ll respond within 2 hours.”
- “That’s a great question! Our experts can help better than I can. Here’s a link to contact them.”
- “I don’t have that info right now. What’s your email? I’ll send you an answer within 2 hours.”
- “I don’t know”
- “That’s not in my system”
- “I can’t help with that”
- Maintains user trust
- Converts failed conversation to lead
- Provides value even when agent can’t answer
- Users feel heard, not ignored
4. Personalize When Possible
The Problem: Generic responses feel robotic and impersonal. Best Practice: Use customer names, remember context, and tailor responses. Setup:- Capture name early: “What’s your name?”
- Use it in responses: “Thanks Sarah, let me find that for you”
- Remember order history: “I see you ordered a blue widget last month. Looking for something similar?”
- Reference previous messages: “Earlier you asked about shipping—it arrives tomorrow”
- Store customer data (email, phone, preferences)
- Reference account history
- Make recommendations based on past purchases
- Offer loyalty rewards they’ve earned
- People respond better to personalization
- Increases trust and engagement
- Higher conversion rates
- Users feel valued
5. Test Everything Before Going Live
The Problem: Bugs in live agents damage your reputation and lose customers. Best Practice: Thoroughly test all conversation paths before deploying. Testing checklist:- ✅ Test all button flows (where do they lead?)
- ✅ Test common questions customers ask
- ✅ Test edge cases (what if user types weird input?)
- ✅ Test on mobile (does it look good on phone?)
- ✅ Test with actual Knowledge Base (does agent find right info?)
- ✅ Test integrations (do Stripe/Shopify/Zendesk connections work?)
- ✅ Test typos (if user misspells something, does agent still understand?)
- ✅ Test rapid clicking (what if user clicks 10 times fast?)
- Use Chatlab (your private testing environment)
- Ask colleagues to try conversations naturally
- Test on different devices (phone, tablet, desktop)
- Test in different browsers
6. Monitor Analytics & Keep Improving
The Problem: You build an agent, deploy it, then never improve it. Best Practice: Track what users ask and continuously improve responses. What to monitor:- Most asked questions - Users asking same thing? Add better KB content.
- Conversation drop-off - Where do users leave? Fix that step.
- Low satisfaction - Are users rating responses poorly? Update answers.
- Unresolved conversations - Where does agent fail? Add fallbacks.
- Most used buttons - People prefer this option? Make it more prominent.
- Review analytics weekly
- Identify patterns in failed conversations
- Update Knowledge Base with missing info
- Adjust agent responses based on feedback
- Re-test changes before deploying
7. Keep Knowledge Base Current
The Problem: Agent gives outdated information = customer frustration + support tickets. Best Practice: Regularly update your agent’s knowledge and responses. What to update:- Prices - Change immediately when pricing changes
- Policies - Update return/shipping policies promptly
- Product info - When products launch or are discontinued
- Team info - New team members, changed hours
- Outdated content - Remove blog posts/info that’s no longer relevant
- Monthly Knowledge Base review
- After any business change
- After customer complaints
- Before big announcements
- Set calendar reminder for monthly KB review
- Enable auto-recrawl for website (pulls latest content)
- Create process: when something changes in business → update agent
- Test changes in Chatlab before deploying
8. Match Your Brand Voice
The Problem: Agent sounds nothing like your company = confusing experience. Best Practice: Make your agent sound like your brand. Examples: Friendly startup:- “Hey! 👋 Let’s get that sorted for you.”
- “You got it! Shipping today 🚀”
- “Thank you for reaching out. Here’s the information you requested.”
- “We appreciate your inquiry and will respond promptly.”
- “Yep, we’ve got that in stock!”
- “Boom! Order confirmed 🎉”
- Define your brand voice - Write 3-5 brand voice guidelines
- Tell the agent - Include these in agent personality settings
- Train it - Give examples of good/bad responses
- Test it - Read responses aloud—does it sound like you?
- Keep it consistent - All channels, all responses
9. Use Follow-Up Questions Strategically
The Problem: Agent answers question but doesn’t help user move forward. Best Practice: End responses with helpful next steps or questions. Examples: Good:- “Your order ships tomorrow. [Track It] [View Similar Items] [Contact Support]”
- “We have the blue widget in stock. Size S or L?” with size buttons
- “Your password has been reset. [Sign In] [Need More Help?]”
- “OK” (no next steps)
- “Your order shipped” (but doesn’t tell them what they actually want—tracking)
- “That’s available” (but doesn’t make it easy to buy)
- Guides conversation forward
- Reduces user friction
- Increases conversions
- Helps agent resolve more issues
10. Document Everything
The Problem: You build an agent, then forget how it works 3 months later. Best Practice: Keep simple documentation of your agent setup. Document:- Agent purpose and goals
- List of main conversation flows
- Knowledge Base structure
- Integrations connected (Stripe, Shopify, etc.)
- Custom settings and rules
- Who owns/maintains the agent
- Simple Google Doc or Notion page
- Update when you make changes
- Share with team
Next Steps:
- Start with 1-2 of these best practices
- Build your first agent following these rules
- Check out Common Scenarios for real-world examples
- Monitor your agent’s performance and iterate