Vibe Coding
For decades, programming has meant laboriously typing code by hand, hunting down syntax errors, and spending countless hours on Stack Overflow. That era is ending. We’re living through a fundamental shift in software development that is redefining how we code, who can code, and what is possible to build.
Vibe coding lets you build things faster, be more ambitious about what you can build, build things more autonomously, have more fun, and explore more options. This is what we’re calling FAAFO (or sometimes “the good FAAFO,” to contrast it with certain other kinds).
Being able to work autonomously or alone on a task or project eliminates two expensive taxes: It reduces the coordination costs (scheduling meetings, aligning priorities, waiting for availability) and the communication challenges (where teammates cannot read each other’s minds but must still create a shared goal and vision of what to build and how).
Astronaut Frank Borman once said, “Superior pilots use their superior judgment to avoid situations which require the use of their superior skill.”
It can take both vigilance and good judgment to recognize when you’re being led down a rabbit hole and need to change course. Vibe coders must learn to notice when AI is heading confidently down a wrong path and decide when to redirect or abandon unproductive approaches.
Building cool things is addictive. Vibe coding, especially with agents, turns your keyboard into a slot machine. You “pull the lever,” and out comes a payout—a chunk of working code, a generated test, or a refactoring. Each little payout delivers a tiny dopamine hit, a neurochemical reward that makes us feel good and encourages us to pull the lever again.
Dr. Andrew Ng, one of the founders of Google Brain and now at Stanford University, said, “AI won’t replace people, but maybe people [who] use AI will replace people [who] don’t.”4
Get ready for a world where software becomes another form of creative expression, and where the millions of little features that someone needs, languishing in a bug backlog, can be built and implemented by anyone.
Thus, it’s essential to: Create fast and frequent feedback loops for validation and control. Create modularity to reduce complexity, enable parallel work, and explore options. Embrace learning in a world where everything changes fast. Master your craft to thrive in an environment where all knowledge work will be changing in a short timeframe. Learning these techniques will be critical for everyone in knowledge work, not just developers and vibe coders.
Vibe coding enables creating great specifications that are testable and actionable. Here are some things you might ask your AI collaborator to do: Write acceptance tests before you write code (true test-driven development), which we’ll use to validate the AI-generated implementation. (We’ll describe how in the next section.) Generate behavior-driven development scenarios in given-when-then format that trace directly back to your user stories and acceptance criteria. Create test datasets that systematically exercise boundary conditions, edge cases, and error scenarios. Generate comprehensive regression test suites whenever you modify existing functionality.
Many developers are asking: “How can you trust AI-generated code that you never personally inspected?” The answer is going to involve a lot of testing. This situation closely resembles how we use open-source libraries. We rarely examine every line of code in those either. Libraries are usually treated as black boxes, and we build trust with them through testing. TDD is a fantastic way to achieve trust with AI, and it helps keep it from going off-track because it’s providing the specification up front.
Tokens are cheap—at least compared to your time and attention. Time can neither be created nor stored, making it a precious resource that you must manage most frugally.
Many developers underestimate the huge return that comes from investing in your own workflow automation.
Escoffier’s brigade de cuisine (kitchen brigade) system represented a game-changing Layer 3 breakthrough, and it’s still how kitchens operate today. Its invention ranks up there with Henry Ford’s assembly line and Taiichi Ohno’s Toyota Production System, revolutionizing the coordination of complex work. Escoffier served in the French army during the Franco-Prussian War, where he learned how specialized units could coordinate complex operations through clear hierarchies and standardized protocols.
diner. This highlights a potential problem with vibe coding. When anyone can generate working code, we may accidentally sever a critical feedback path that links creation to consequences.
Through rigorous statistical analysis, the team identified four key metrics that consistently differentiated high-performing organizations from their peers: Deployment frequency: How often application changes are deployed to production. Deployment Lead Time: The time it takes for a code commit or change to be successfully deployed to production. Deployment Failure Rate: The percentage of deployments that cause failures in production, requiring hotfixes or rollbacks. Failed Deployment Recovery Time: The time it takes to recover from a failed deployment.