Common Training Mistakes and How to Avoid Them

Training an AI assistant doesn’t require technical skills, but there are a few common mistakes that can reduce answer quality. The good news? They’re easy to fix once you know what to look for.

Below are the most frequent training mistakes we see in AiFaqChat — and exactly how to avoid them.

1. Relying Only on Automatic Scanning

Automatic website scanning is powerful, but it can’t always capture context, intent, or edge cases.

Why this is a problem:

• Important internal knowledge may be missing
• Marketing pages don’t always answer real user questions
• Some content may be too generic

How to avoid it:

• Add manual training content for FAQs and edge cases
• Review scanned content and edit where needed
• Use both automatic and manual training together

2. Writing Vague or Overly Generic Rules

Rules guide how the AI behaves. When they’re too vague, the assistant may respond inconsistently.

Common examples:

• “Be helpful”
• “Answer clearly”

How to avoid it:

• Be specific about tone and behavior
• Include examples if needed
• Write rules in clear, simple language

Example: “Answer in short paragraphs. Use bullet points when listing steps. If the answer is unknown, say you don’t have that information.”

3. Mixing Outdated and New Content

Old content can confuse the AI if it contradicts new information.

Why this happens:

• Website content changed, but AI wasn’t updated
• Manual training was added without cleaning old data

How to avoid it:

• Rescan your website after major updates
• Fully retrain the AI if content changed significantly
• Remove outdated manual training entries

4. Adding Too Much Content at Once

More content isn’t always better. Large blocks of unfocused text can reduce answer quality.

How to avoid it:

• Split content into smaller, focused entries
• Use clear headings and structure
• Keep each training entry topic-specific

5. Not Reviewing Real User Questions

The best training data often comes from real conversations.

Common mistake:

• Training once and never reviewing results

How to avoid it:

• Review chat history regularly
• Identify repeated or unanswered questions
• Add or refine training content based on real usage

6. Retraining Too Often (or Not Enough)

Retraining resets the AI’s knowledge. Doing it too often can be unnecessary, while never retraining can leave outdated knowledge.

Best practice:

• Rescan for small updates
• Retrain only after major content changes

Quick Checklist for Better Training

• Combine automatic and manual training
• Write clear, specific rules
• Keep content up to date
• Review real user questions
• Use retraining strategically

Avoiding these mistakes will dramatically improve the quality and reliability of your AI assistant.

Want to improve your setup? Add manual training content, retrain your assistant.