When did AI solve my issue?
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…
In the latest two blog posts, the author discussed instances where AI failed to resolve programming issues and the importance of self-search. Recently, they encountered a problem on trigger.dev: "Node.js 21 detected without native WebSocket support." The suggested solution was to install the ws package and include it via the transport option in the RealtimeClient setup.
While the error explicitly instructed to install the ws package or update Node.js, the author lacked sufficient experience with trigger.dev to determine the appropriate course of action.
Traditionally, the author's debugging approach involved consulting resources like AI and Google, relying on instincts, and seeking self-driven solutions. In this particular case, they first turned to AI, providing ChatGPT with additional context about their use of trigger.dev, relevant web resources, and their tech stack. By sharing this context and performing a targeted web search, ChatGPT was able to locate the appropriate configuration page on trigger.dev, leading to the desired resolution.
The author emphasizes that the key to successfully utilizing AI lies in providing it with sufficient context and knowledge. In-depth knowledge can guide both the user and AI towards the optimal solution. However, an uninformed approach may lead to unproductive dead ends, highlighting the importance of informed context when engaging with AI.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
