OpenClaw and the Word That Started a War
OpenClaw is not just a tool — it is proof that AI-powered coding, when done with real skill and discipline, can produce software that shakes the entire tech industry to its core.
Peter Steinberger, the developer behind OpenClaw, has become one of the most talked-about names in AI engineering circles, not just because of what he built, but because of what he said about how he built it.
He called “vibe coding” a slur.
That single statement, delivered during an appearance on OpenAI’s “Builders Unscripted” podcast, sent ripples through the developer community and forced a much-needed conversation about what AI-assisted development actually requires from the people doing it.
As a teacher of modern development practices, what Steinberger laid out in that conversation is something every person serious about building with AI tools needs to hear, internalize, and apply — starting right now.
And if you are someone who creates, flips, or grows digital products using AI, flipitai is the kind of platform that puts everything Steinberger is talking about into a practical, usable framework for real people doing real work.
Table of Contents
What Is OpenClaw and Why Does It Matter So Much Right Now
OpenClaw is a viral AI agent that Peter Steinberger built using OpenAI’s Codex, and its original name, Clawdbot, was a direct nod to Claude Code, one of the most powerful AI coding assistants available today.
The product caught fire almost immediately after its release, pulling in attention from some of the biggest names in the technology world, including Meta’s Mark Zuckerberg, who personally reached out to Steinberger to share his own experiences testing it.
What makes OpenClaw so significant is not just the product itself, but the philosophy behind it.
Steinberger did not build OpenClaw by feeding prompts into a chatbot and hoping for the best.
He built it through a deeply skilled, intentional process that treats AI code generation the same way a seasoned musician treats an instrument — with respect, with practice, and with a serious investment of time to understand what the tool is actually doing underneath the surface.
OpenClaw represents what is possible when a developer stops treating AI as a shortcut and starts treating it as a craft.
That distinction is everything, and it is exactly what the broader conversation about “vibe coding” gets so dangerously wrong.
Tools like flipitai are built for people who understand this distinction — those who want to use AI with precision and purpose, not just convenience.
Why “Vibe Coding” Has Become a Misleading and Damaging Term
The Slur That Minimizes a Real Skill
When Steinberger called “vibe coding” a slur, he was not being dramatic.
He was pointing to something that educators and practitioners have seen happen time and time again across industries — when something that requires real skill gets a casual, breezy label, it signals to the outside world that anyone can do it without effort.
“There are these people that write software the old way, and the old way is going to go away,” Steinberger said clearly on the podcast, before drawing the hard line: “They call it ‘vibe coding.’ I think vibe coding is a slur.”
The word “vibe” carries with it a sense of casual ease, of going with the flow, of not needing to think too hard.
When applied to software development — even AI-assisted software development — that framing is not just inaccurate, it is actively harmful to the people trying to learn and grow in this field.
It makes serious, practiced engineering look like something a teenager could do on a Sunday afternoon without breaking a sweat.
Steinberger’s pushback on this term is a form of professional respect, not just for himself, but for the thousands of developers who are putting in genuine work to master AI-assisted coding at a high level.
If you are building digital products with AI and want tools that match the seriousness of the craft, flipitai is designed for exactly that level of intentional work.
Other Industry Leaders Are Pushing Back Too
Steinberger is not alone in his frustration with the term “vibe coding.”
Former Google Brain scientist Andrew Ng, one of the most respected figures in the AI education space, described the term as “unfortunate” and “misleading,” which carries particular weight coming from someone who has spent years teaching machine learning concepts to hundreds of thousands of students around the world.
Even Andrej Karpathy, the former Tesla AI head who is widely credited with coining the term “vibe coding” in the first place, has since shifted his position.
Karpathy now believes that “agentic engineering” is the more accurate and forward-looking description of where this field is heading, which suggests even the person who popularized the phrase recognizes that it no longer serves the conversation well.
Collins Dictionary named “vibe coding” the word of the year for 2025, which tells us that the term has reached mainstream cultural saturation.
But mainstream recognition does not mean professional accuracy, and the gap between those two things is exactly where bad habits and shallow thinking take root in a fast-moving industry.
Understanding the real nature of AI-assisted coding is not just an academic debate — it directly affects how well people build, how much they can ship, and whether the products they create are actually reliable.
flipitai exists to support creators who are building with that kind of rigor and intentionality, not just vibes.
The Guitar Analogy That Changes Everything About How to Think About AI Coding
Skill Is Not Optional — It Is the Entire Point
Steinberger used a beautifully simple analogy to explain what AI-assisted development actually feels like from the inside: learning to play the guitar.
When someone first picks up a guitar, the instrument does not make music by itself.
The strings are there, the body resonates, the potential for sound is enormous — but none of it comes together without the player developing real technique, real feel, and real understanding of how their fingers interact with the frets.
The same is true of working with AI code editors like the ones Steinberger used to build OpenClaw.
The AI is the instrument.
The developer is the musician.
And mastery comes only after consistent, deliberate practice that builds a deep intuition for what the tool will produce, how to guide it toward quality output, and when to step in and redirect it when it drifts off course.
“They don’t understand that it’s a skill,” Steinberger said plainly, and that line deserves to be read slowly and taken seriously by anyone who thinks they can build production-quality AI-generated software on day one without putting in the hours.
For creators and flippers who want to develop that skill inside a structured, supportive environment, flipitai offers the kind of ecosystem where serious builders can grow.
Shipping Code Without Reading It Is Not Laziness — It Is Earned Confidence
One of the most striking moments in Steinberger’s conversation was when he confirmed that he now ships AI-generated code without even reading it line by line.
To someone who does not understand the depth of experience behind that statement, it sounds reckless.
To someone who does understand it, it sounds exactly like what an expert sounds like.
“Most code is boring,” Steinberger said. “I have a pretty good understanding of what it writes.”
This is the point where mastery becomes visible — not when someone reads every line with equal attention, but when someone has developed such a thorough mental model of how their tools behave that they can make confident, informed decisions about what needs scrutiny and what does not.
A surgeon with twenty years of experience moves through a procedure differently than a first-year resident, not because they care less, but because their pattern recognition has been trained so thoroughly that routine elements are handled automatically.
Steinberger’s ability to ship without reading is not a product of carelessness — it is a product of having put in thousands of hours developing a calibrated intuition for what OpenAI’s tools produce.
That level of trust in your tools only comes from sustained, intentional practice, and it is what separates a skilled AI engineer from someone who is genuinely just vibing.
Platforms like flipitai are built to help creators reach that kind of calibrated confidence in their own work.
What Managing a Team Taught the OpenClaw Creator About Working With AI
Letting Go of Perfectionism Is a Leadership Skill
One of the most practically useful insights Steinberger shared was rooted in his past experience as a team leader before he became the developer behind OpenClaw.
“I led a team before,” he said. “I had a lot of software engineers under me. That also required accepting that they will not write exactly the same code that I want.”
This is a masterclass in the kind of mental flexibility that AI-assisted development demands.
When a developer works alone with traditional tools, every decision passes through their own hands, their own preferences, their own standards.
But when you introduce AI into the workflow — or when you manage a team of human engineers — you have to develop the ability to evaluate output against the standard of “does this work well and achieve the goal” rather than “does this look exactly like what I would have written myself.”
That shift in perspective is not a lowering of standards.
It is a maturation of judgment that allows a developer to move faster, ship more, and build bigger than they ever could by doing everything by hand.
Steinberger brought that management mindset into his AI coding workflow and it became one of his most powerful competitive advantages when building OpenClaw.
For anyone building and flipping digital products through flipitai, developing this same flexibility in how you evaluate and iterate on AI-assisted output is one of the most valuable skills you can invest in.
The Journey From PSPDFKit to OpenClaw and What It Tells Us About AI’s Future
One Developer, Multiple Chapters, One Clear Direction
Before OpenClaw became a viral sensation and before Sam Altman was calling him a “genius with a lot of amazing ideas about the future of very smart agents,” Peter Steinberger had already built a serious software company called PSPDFKit.
PSPDFKit was a PDF processing tool that became widely used across enterprise environments, which means Steinberger came into the AI coding world not as a hobbyist experimenter but as someone with years of professional software development experience already behind him.
That background matters enormously because it means the skills he brought to OpenClaw were not learned on the fly — they were the product of a long career that gave him both the technical foundation and the professional instincts to use AI tools at a genuinely high level.
After building OpenClaw, Steinberger’s interactions expanded rapidly across the AI industry.
Anthropic asked him to rename his chatbot, which had originally been called Clawdbot as a reference to Claude Code.
Mark Zuckerberg reached out personally to discuss his own experiences testing the product.
Zuckerberg even explored bringing Steinberger to Meta, but OpenAI moved faster, and Steinberger accepted their job offer, joining one of the most prominent AI companies in the world.
For creators on flipitai who are building and scaling with AI tools, Steinberger’s trajectory is a powerful reminder that skill, consistency, and a serious approach to craft will always find its audience — and often its reward.
What This Means for Anyone Building With AI Tools Today
The Future Belongs to the Skilled, Not the Casual
The single most important takeaway from Steinberger’s story and from the rise of OpenClaw is that AI coding is not a shortcut around skill.
It is a new domain where skill is required just as urgently as it ever was — the tools have simply changed, the learning curve has a different shape, and the ceiling of what one person can produce has risen dramatically.
The developers, creators, engineers, and builders who understand this right now are the ones who will define what the next decade of software looks like.
OpenClaw is a proof of concept for what is possible when someone takes AI-assisted development seriously, treats it as a craft, and invests the time to develop genuine mastery rather than surface-level fluency.
If “vibe coding” is the slur, then serious, intentional, skilled AI engineering is the standard — and that standard is worth building toward every single day.
Whether you are developing apps, building digital products, or flipping AI-generated assets, flipitai is the ecosystem designed to help you do it at the level that actually matters.
Conclusion: OpenClaw Is the Blueprint — Now It Is Your Turn to Build
The story of OpenClaw and the developer behind it is more than a technology headline.
It is a lesson about what serious, skilled, intentional work with AI tools looks like when it is done right — and a clear signal that the era of casual, undisciplined AI use is already giving way to a new standard of professional AI engineering.
Peter Steinberger did not stumble into building one of the most talked-about AI agents of 2026 by vibing his way through a few prompts.
He brought years of professional experience, a management mindset, a musician’s discipline, and a deep respect for his tools to every line of code OpenClaw ever produced.
That is the model worth following.
That is the skill worth developing.
And for every creator, builder, and digital entrepreneur ready to work at that level, flipitai is where the serious work begins.
We strongly recommend that you check out our guide on how to take advantage of AI in today’s passive income economy.
