"I vibe code every day. It's definitely a productivity boost. For debugging or small tasks, I sometimes treat it like a lottery. Maybe it will produce something amazing. Sometimes, it does. Vibe coding helps me brainstorm what the solution could look like, even if I don't adopt the final solution it proposes. Vibe coding also speeds up the time spent rewriting code when you realize a requirement wasn't covered."
"When I vibe code, it's always iterative. I give it the basic information it needs, it produces a version, then I check it - similar to a code review with coworkers. I might say, "You missed this part" or "You missed that part." The AI sometimes fixes issues but introduces something new. You have to keep an eye on it. For complex tasks, you need more double-checking. But even with the extra checking, it's still faster."
"I was working with a partner team and ran into complex locking issues. Without an LLM, I might have taken a day to research possible solutions, especially since it was relatively new to me. Within 15 minutes, I brainstormed with the LLM about possible solutions. I pointed out weaknesses in its suggestions and asked it to improve them. In 15 minutes, I had a proposal to send to the team."
Anni Chen is a tech lead at Amazon responsible for deploying large-scale generative AI and LLM-driven systems and focuses on memory that powers personalization. She vibe codes daily and finds it a productivity boost for debugging, small tasks, and brainstorming potential solutions. Vibe coding is iterative: provide basic information, accept an AI-generated version, and then review and correct introduced issues. It speeds up rewriting and can reduce research time dramatically, illustrated by resolving complex locking issues and producing a team proposal within 15 minutes. Vibe coding requires double-checking, technical knowledge, and is not recommended for production use or large-scale deployment.
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