Publishing, Sharing, and Iterating on Your Chatbot

Your chatbot is built and tested. Now it is time to get it into the hands of real users, collect feedback, and make it better. This final lesson covers publishing options, sharing strategies, and the iteration process that turns a good chatbot into a great one.

Publishing on Custom GPTs

Custom GPTs offer three visibility levels:

Visibility	Who Can Access	Best For
Only me	Just you	Personal assistants, work-in-progress bots
Anyone with the link	Anyone you share the URL with	Team tools, client-facing bots, beta testing
Everyone	All ChatGPT users via the GPT Store	Public tools, marketing, building an audience

How to Publish

1. Open your GPT in the GPT Builder
2. Click Save (or Update if editing)
3. Choose your visibility level
4. Click Confirm

For "Everyone" visibility, your GPT appears in the GPT Store where users can discover it by searching or browsing categories.

GPT Store Tips

If you publish to the GPT Store:

• Write a clear description: Users decide to try your GPT based on the description
• Choose the right category: Pick the most relevant category so users find you
• Use a professional profile image: First impressions matter in a marketplace
• Include conversation starters: They help new users get started immediately
• Respond to early feedback: The first users will reveal issues you missed

Sharing Claude Projects

Claude Projects have more limited sharing options:

Plan	Sharing Options
Claude Pro	Personal use only (no sharing)
Claude Team	Share with team members
Claude Enterprise	Share across the organization

How to Share (Team/Enterprise)

1. Open your project
2. Click the Share button or project settings
3. Add team members by email
4. Set permissions (view or edit)

Since Claude Projects cannot be shared publicly, they work best as internal team tools rather than customer-facing chatbots.

Sharing Gemini Gems

Gemini Gems can be shared via link:

1. Open your Gem
2. Click Share
3. Copy the shareable link
4. Send it to anyone with Gemini Advanced access

Getting Feedback

Real user feedback is more valuable than your own testing. Here is how to collect it effectively:

Method 1: Direct Observation

Watch someone use your chatbot for the first time without helping them. Note:

• Where do they get confused?
• What questions do they ask that the bot handles poorly?
• Do they understand the conversation starters?
• How long does it take them to get a useful answer?

Method 2: Ask Specific Questions

After someone uses your chatbot, ask:

1. "Did you get the answer you were looking for?"
2. "Was anything confusing or unexpected?"
3. "What would you want it to do that it cannot do now?"
4. "Would you use this again?"

Method 3: Review Conversation Logs

For Custom GPTs, you can review conversations in the GPT Builder analytics. Look for:

• Questions that got poor responses
• Conversations where users gave up
• Unexpected use cases you did not plan for
• Patterns in what users ask most

The Iteration Cycle

Improving your chatbot is an ongoing cycle:

Build → Test → Publish → Collect Feedback → Improve → Repeat

Iteration 1: Fix Obvious Issues (Week 1)

After the first few users, you will likely find:

• Instructions gaps: The chatbot does not handle a common question type
• Tone mismatches: Responses are too formal or too casual
• Missing knowledge: Users ask about topics not covered in your files
• Boundary failures: The chatbot discusses topics it should avoid

Fixes:

• Add specific handling for the most common missed questions
• Adjust tone language in instructions
• Upload additional knowledge files
• Strengthen boundary instructions

Iteration 2: Refine and Expand (Weeks 2-4)

Based on more usage data:

• Add example responses in your instructions for tricky questions
• Expand knowledge base with documents that cover user questions
• Improve conversation starters based on what users actually ask
• Add edge case handling for unusual but recurring questions

Iteration 3: Optimize (Month 2+)

Once the chatbot handles most questions well:

• Streamline instructions by removing rules that are never triggered
• Update knowledge files with current information
• Consider adding capabilities (web browsing, code interpreter) if users need them
• Track satisfaction over time to ensure quality stays high

Common Iteration Patterns

User Feedback	What to Change
"It did not answer my question"	Add knowledge files covering that topic
"The answer was too long"	Add length constraints to instructions
"It was not specific enough"	Add more detailed documents or example responses
"It went off topic"	Strengthen boundary instructions
"It made something up"	Add "only answer from knowledge files" instruction
"The tone was wrong"	Add explicit tone examples in instructions
"I did not know what to ask"	Improve conversation starters and opening message

Version Control for Chatbots

Keep track of changes you make:

Measuring Success

Track these metrics to gauge your chatbot's effectiveness:

Metric	What It Tells You	How to Measure
Usage frequency	How often people return	GPT Builder analytics or conversation count
Conversation length	Whether users engage deeply	Average messages per conversation
Task completion	Whether users get what they need	Direct feedback or follow-up surveys
Repeat usage	Whether the chatbot provides ongoing value	Returning user count
Escalation rate	How often users need human help after using the bot	Track support tickets

Advanced Tips

Tip 1: Create Specialized Versions

Instead of one chatbot that does everything, build specialized versions:

• A chatbot for new employee onboarding
• A separate chatbot for benefits questions
• Another for IT helpdesk questions

Focused chatbots perform better than general ones.

Tip 2: Use Your Chatbot Yourself

Be a daily user of your own chatbot. You will notice issues faster than waiting for user feedback.

Tip 3: Keep Instructions Under Control

Instructions should be clear and concise. If they grow beyond two pages of text, consider simplifying. Overly complex instructions can confuse the AI and lead to inconsistent behavior.

Tip 4: Schedule Regular Reviews

Set a monthly reminder to:

• Review and update knowledge files
• Check for outdated information
• Test the chatbot with recent user questions
• Update instructions based on accumulated feedback

Course Summary

In this course, you have learned to:

1. Understand the landscape: Custom GPTs, Claude Projects, and Gemini Gems each offer no-code chatbot building with different strengths
2. Plan effectively: A clear purpose, defined tasks, boundaries, and conversation design are the foundation
3. Build on Custom GPTs: Using the GPT Builder's Configure mode to set up instructions, starters, and capabilities
4. Build on Claude Projects: Using project instructions and the large context window for document-heavy chatbots
5. Add knowledge bases: Preparing, uploading, and maintaining files that make your chatbot an expert
6. Publish and iterate: Sharing your chatbot, collecting feedback, and continuously improving

The best chatbot is the one you keep improving. Start simple, get it into users' hands, listen to their feedback, and make it better. You now have the skills to build AI chatbots on multiple platforms—without writing a single line of code.