FAQs

No, not by default. The drupal/ai module is designed with security in mind. It sends only the specific prompts you authorize to the LLM provider. Furthermore, because Drupal is vendor-agnostic, you can choose to connect to "Zero-Retention" enterprise endpoints (like Azure OpenAI) or even run Local LLMs (via Ollama) on your own server, ensuring no data ever leaves your infrastructure.

Yes, absolutely. Drupal relies on cached data (for configuration, route definitions, and class discovery). If a patch modifies PHP code or configuration, the changes will not take effect until the old cached versions are deleted, typically using the 'drush cr' command.

Yes. If you used git apply Drupal to apply the patch, you can usually reverse it using the same command with the -R (reverse) option:

git apply -R my-changes.patch

This is a quick way to undo changes if you find a problem or if the patch was misapplied.

The simplest way to fix conflicts with 'git apply' Drupal is to first run it with the reject option: 'git apply --reject my-changes.patch'. This will leave '.rej' (reject) files showing exactly where the patch failed. You must then manually review the original file and the '.rej' content, manually edit the file to incorporate the change, and then remove the '.rej' file.

• Git apply (used for 'git diff' patches): This command simply applies the file changes described in a patch file to your working directory. 
• Git am (used for 'git format-patch' patches): It applies patches that contain commit metadata (author, date, message) and automatically creates a new commit in your repository for each patch it successfully applies.

Future AI systems will likely become more conversational and emotionally aware, while human agents will focus on higher-value tasks that require empathy and expertise.

Frustration usually occurs when a bot cannot understand queries, repeats the same response multiple times, or makes it hard to reach a human agent.

Yes. AI analyzes customer behavior and preferences to offer tailored recommendations and proactive support.

They often deal with integration complexity, high initial costs, continuous data training needs, and issues related to maintaining customer trust.

AI can automate tasks like ticket routing, call summarization, FAQ responses, password resets, and basic troubleshooting.