# When did AI solve my issue?

> Source: <https://dev.to/a0m0rajab/when-did-ai-solve-my-issue-1gpp>
> Published: 2026-08-30 21:00:00+00:00

In the last two blogs, I shared how AI failed to solve a few issues in programming and the value of self-search; today, I am going to share the opposite. The main goal is to show how you can learn from AI and use it as effectively as possible.

This all started when I was using trigger.dev and got the following error:

`Node.js 21 detected without native WebSocket support. Suggested solution: For Node.js < 22, install "ws" package and provide it via the transport option: import ws from "ws" new RealtimeClient(url, { transport: ws }) using trigger.dev`

The error clearly asks me to either install the ws package or update Node.js. But since I did not have a full experience with trigger.dev I could not figure out how to do that.

My approach to debugging is based on methods:

With this error, I went with AI first, asking ChatGPT about it; then I tried Googling it (which used to work before the AI age), but I could not find any data.

With ChatGPT, I gave it two extra points to help it get the right answer; I shared that I am using trigger.dev, added the web resources, and asked for a solution based on my tech stack.

By giving ChatGPT context and a web search, it was able to find the [config page on trigger.dev](https://trigger.dev/docs/config/config-file#node-js-versions) and get the results I wanted.

With this experience and the ones I had before, the most important thing when using AI was the context and knowledge I had to provide. The in-depth knowledge can help the user and AI to find the optimal solution, yet going blindly might lead you to a black hole without knowing how to return.