How do you prevent a custom Gem-bot from hallucinating and stubbornly insisting on incorrect code structures from uploaded files?

Enhancing the Reliability of Custom AI Code Assistants: Strategies to Minimize Hallucinations and Improve Fidelity to Uploaded Files

As AI-powered tools become increasingly integrated into software development workflows, customizing and fine-tuning these models to better understand and adhere to project-specific codebases is an ongoing challenge. Developers practicing ABAP or similar languages often upload their source files for the AI to assist with, but they encounter persistent issues — notably, the AI “hallucinating” code, referencing non-existent fields, or modifying source structures inaccurately.

In this article, we explore practical strategies to minimize such hallucinations, enhance the AI’s fidelity to uploaded files, and improve its utility in detailed development tasks.

Understanding the Challenge

When a custom AI assistant, such as a Gem-bot, is provided with project files manually uploaded outside of version control systems, it may not re-read or interpret these files dynamically during each query. Instead, it often maintains a contextual memory built during training or previous interactions. This can lead to the AI referencing outdated, incorrect, or fabricated code structures — especially if the prompt or instructions do not explicitly enforce source fidelity.

Common symptoms observed by developers include:

• The AI referencing non-existent fields or structures.
• Inconsistent code snippets that deviate from the uploaded definitions.
• The need for multiple corrections and clarifications, reducing productivity.

Strategies for Improving Source Fidelity

While there is no one-size-fits-all solution, several approaches can significantly improve the AI’s adherence to your uploaded source files.

1. Explicit Source Review Prompts

Before requesting code generation, explicitly instruct the AI to “read and verify” the source files. For example:

“Please review the entire source code of the structure ZDT_CUSTOMER_DATA before generating any related code. Use this information as the authoritative reference and do not invent fields or structures not present in the uploaded files.”

This emphasizes source fidelity and primes the model to prioritize your data.

1. Providing Clear Context and File Content

Instead of merely uploading files and asking questions, incorporate relevant code snippets or definitions directly into your prompt. For example:

_”Here is the full definition of ZDT_CUSTOMER_DATA:

abap
TYPES: BEGIN OF zdt_customer_data,
id TYPE i,
name TYPE string,
address TYPE string,
postalcode TYPE string,
END OF zdt_customer_data.

Based on this, please assist with the process_customer method.”_