In a recent LinkedIn post, product discovery coach and author Teresa Torres shared her experiences leveraging AI for rapid software development, a process she terms ‘vibe coding.’ Torres detailed how recent advancements in AI models have significantly accelerated her ability to build functional tools, from interview platforms to course management software.
Accelerated Development with AI
Torres highlighted a particularly productive week where she developed several sophisticated AI-powered tools. She described building an ‘AI Interviewer’ capable of conducting interviews, supporting screeners, and processing transcripts. Additionally, she created software for a five-day challenge, complete with scoring systems and leaderboards, and began developing an AI coach for an upcoming course, featuring image-to-text capabilities and integration with a learning management system.
“The two new AI tools will need a lot of iteration to get good. But the scaffolding is all there.”
This sentiment underscores the current state of AI development, where foundational structures can be rapidly generated, with refinement being the subsequent step. Torres emphasized the immediate functionality of the tools, noting:
“All of this code is well-written, follows my coding patterns, uses my preferred tech stack, has full test coverage, and just works.”
According to Torres, the AI model she is using, referred to as ‘Opus 4.5,’ excels at creating standard interfaces and meticulously implementing detailed plans. This contrasts sharply with traditional development cycles, which can often involve lengthy debugging periods.
The Efficiency of ‘Vibe Coding’
Torres attributes this rapid progress to a method she calls ‘vibe coding,’ enabled by advanced AI. She contrasts this with the frustrations of traditional software development:
“No doom cycles of endless bug fixes that don’t get fixed. No spaghetti code. It’s documenting all of its key decisions as it goes. It’s tracking a to do list for the tasks that it needs me to do and it’s doing it so autonomously, I was able to do both of today’s projects in a parallel.”
Torres points out the autonomy and efficiency gained, allowing her to work on multiple projects concurrently. The AI not only generates code but also documents its decision-making process and identifies tasks requiring human input, streamlining the development workflow significantly. She also noted the time efficiency, stating that she was able to complete these substantial projects by mid-afternoon.
The Future of AI in Development
Torres concluded her post by querying her network about their experiences with similar AI tools, suggesting that the latest models represent a substantial leap forward in capability. Her insights suggest a paradigm shift in how software can be created, moving from laborious manual coding to a more collaborative and iterative process with AI assistants.
📝 About This Content
This article is based on insights shared by Teresa Torres on LinkedIn.
📅 Originally posted on December 16, 2025 | View original post on LinkedIn →