We've integrated GPT into 15+ client workflows over the past year. Here are the three lessons that would have saved us weeks of debugging and client confusion.
Lesson 1: Context Is Everything
The Problem: Our first GPT integration gave inconsistent results. Same input, different outputs. Clients lost trust quickly.
The Solution: Strict context management.
- •**System prompts**: Always include role, tone, and output format requirements
- •**Examples**: Include 3-5 sample inputs and expected outputs in every prompt
- •**Constraints**: Specify exactly what the AI should and shouldn't do
Example: Instead of "Summarize this customer feedback," we now use: "You are a customer success analyst. Summarize this feedback in exactly 2 sentences: one for the main concern, one for suggested action. Use professional tone. Do not include personal opinions."
Lesson 2: Users Need to Understand the AI
The Problem: Clients would blame the AI for everything that went wrong, even unrelated issues.
The Solution: Transparent communication about what the AI does and doesn't do.
- •**Clear labels**: When content is AI-generated, we label it clearly
- •**Confidence indicators**: Show users when the AI is uncertain
- •**Edit capabilities**: Always let users modify AI output before finalizing
The Result: Support tickets about "AI errors" dropped 80% when users understood they were partners with the AI, not passive recipients.
Lesson 3: Graceful Failure Beats Perfect Success
The Problem: We spent weeks trying to handle every edge case. When the AI failed, the entire process broke.
The Solution: Design for failure from day one.
- •**Fallback options**: If GPT can't process something, route it to a human queue
- •**Partial success**: If 8 out of 10 items process correctly, show the 8 successes and flag the 2 failures
- •**Clear error messages**: "The AI couldn't categorize this review. It's been sent to Sarah for manual review."
The Meta-Lesson
GPT integration isn't a technical challenge — it's a user experience challenge. The API is the easy part. Managing expectations, handling errors, and building trust takes 80% of the work.
Focus on the human side first. The technology will follow.