Peter Steinberger, the developer behind the viral AI agent Clawdbot (now known as OpenClaw), has revealed he had to step back from development after becoming dangerously obsessed with vibe coding. In a candid interview on the “Behind the Craft” podcast published Sunday, Steinberger described how the practice pulled him into a “rabbit hole” that affected his personal life and mental health.
The developer recounted finding himself vibe coding on his phone during dinner with friends instead of engaging in conversation. “I decided, OK, I have to stop this more for my mental health than for anything else,” he explained. This confession comes as vibe coding—the practice of rapidly building software using AI assistance—continues to surge in popularity across the tech industry.
Clawdbot went viral last month, attracting high-profile supporters including Y Combinator CEO Garry Tan and multiple partners at Andreessen Horowitz. The personal AI agent is designed to run continuously and integrate with consumer apps like WhatsApp and Telegram. Users can deploy it to manage schedules, oversee coding sessions, and even create AI employees. The enthusiasm was so intense that some tech fans purchased Mac Minis specifically to run the AI agent.
However, Steinberger warns that developers can fall into a trap where building increasingly powerful AI tools creates an “illusion of making you more productive” without delivering real progress. While building new tools feels rewarding and fun, it can quietly transform into compulsion. With AI enabling developers to “build everything,” Steinberger emphasizes that ideas and taste matter more than ever. Without clear vision, developers risk creating tools and workflows that don’t actually advance projects. “If you don’t have a vision of what you’re going to build, it’s still going to be slop,” he cautioned.
The vibe coding trend has gained significant momentum, with Anthropic recently announcing it built its new agentic work tool, Cowork, entirely using Claude AI. Product manager Felix Rieseberg revealed that developers manage “anywhere between 3 to 8 Claude instances” simultaneously for implementing features and fixing bugs. Despite this excitement, tech leaders are issuing warnings about limitations. Google CEO Sundar Pichai stated he won’t vibe code on “large codebases where you really have to get it right,” citing security concerns. Boris Cherny, the engineer behind Anthropic’s Claude Code, echoed these concerns, noting that vibe coding works well for prototypes but not for core business software requiring maintainability and careful consideration.
Key Quotes
I was out with my friends and instead of, like, joining the conversation in the restaurant, I was just like, vibe coding on my phone.
Peter Steinberger, creator of Clawdbot, describing how his obsession with vibe coding affected his personal life and social interactions, illustrating the addictive nature of AI-assisted development.
If you don’t have a vision of what you’re going to build, it’s still going to be slop.
Steinberger’s warning that despite AI’s ability to help developers “build everything,” the lack of clear vision and taste results in low-quality output, emphasizing that human judgment remains essential.
Us humans meet in-person to discuss foundational architectural and product decisions, but all of us devs manage anywhere between 3 to 8 Claude instances implementing features, fixing bugs, or researching potential solutions.
Felix Rieseberg, Anthropic’s product manager, describing how the company built Cowork using Claude AI, revealing the scale at which developers are now deploying multiple AI instances simultaneously.
You want maintainable code sometimes. You want to be very thoughtful about every line sometimes.
Boris Cherny, engineer behind Anthropic’s Claude Code, cautioning that vibe coding is appropriate for prototypes but not for core business software that requires careful consideration and long-term maintenance.
Our Take
The Clawdbot creator’s confession reveals an uncomfortable truth about AI development tools: they can be as addictive as they are productive. This represents a fascinating paradox where the builders of AI agents are themselves becoming captive to the very workflows these tools enable. The industry’s rapid embrace of vibe coding mirrors historical patterns with new technologies—initial euphoria followed by necessary recalibration.
What’s particularly striking is the convergence of warnings from leaders at Google, Anthropic, and independent developers. This suggests the tech community is collectively recognizing that AI-assisted coding requires guardrails and intentionality. The emphasis on “vision and taste” points to an emerging consensus: AI amplifies human capabilities but cannot replace human judgment. As vibe coding becomes mainstream, we’re likely to see new best practices emerge around when to use AI assistance versus when traditional, deliberate coding is essential. This story may mark the beginning of a more mature, nuanced approach to AI development tools.
Why This Matters
This story highlights a critical inflection point in AI-assisted software development as the industry grapples with the psychological and practical implications of vibe coding. As AI tools become more powerful and accessible, the line between productivity enhancement and compulsive behavior is blurring, raising important questions about developer mental health and sustainable work practices.
The warnings from Steinberger and other tech leaders signal that the AI development community is beginning to recognize the limitations of rapid AI-assisted coding. While vibe coding can accelerate prototyping and experimentation, the emphasis on vision, taste, and intentionality suggests that human judgment remains irreplaceable in creating meaningful software products.
For businesses investing heavily in AI development tools, this serves as a reminder that speed doesn’t equal value. The distinction between throwaway code and production-ready software matters more than ever as companies rush to integrate AI into their workflows. This conversation also reflects broader concerns about AI’s impact on work-life balance and the potential for technology to create new forms of digital addiction, even among the developers building these tools.