You know that feeling when you’re driving somewhere new and you just kind of vibe your way there? No strict directions, just following your instincts and the general direction? That’s where most of us are with Vibe Coding today – we’re telling AI what we want in broad strokes and hoping it gets us close enough.
But what if we could actually steer this process with precision while keeping that creative flow? That’s where Vision Steering comes in, and frankly, it’s changing everything about how we build software.
Let me break it down: traditional programming was like giving turn-by-turn directions. Early Vibe Coding was like saying “drive me to California.” Vision Steering? It’s like having a co-pilot who understands not just where you want to go, but why you’re going there, what scenery you’d enjoy along the way, and when you need to stop for coffee.
I’ve been experimenting with this approach for months, and the results are mind-blowing. Instead of just telling AI “build me a customer dashboard,” I’m now describing the user experience I want to create, the business outcomes we’re targeting, and the constraints we need to work within. The AI isn’t just writing code – it’s co-creating with me, understanding the vision behind the requirements.
This aligns perfectly with what I see as the future of software development. Remember that principle from Qgenius about Code is Capability, Intentions and Interfaces are Long-term Assets? Vision Steering takes this to the next level. We’re not just writing disposable code anymore – we’re crafting durable intentions that guide AI systems over time.
Here’s what’s fascinating: when you focus on steering the vision rather than micromanaging the implementation, something magical happens. The AI starts making intelligent decisions you wouldn’t have thought of. It suggests alternative approaches, identifies edge cases you missed, and even anticipates future requirements. I’ve had AI systems recommend architectural patterns I hadn’t considered, simply because they better aligned with the long-term vision I described.
But here’s the catch – and this is crucial. Vision Steering requires us to be crystal clear about our intentions. Vague prompts get vague results. Specific, well-articulated visions? They produce software that feels almost prescient. I’ve seen teams cut development time by 70% while producing higher quality systems, simply because they invested time upfront in defining their vision with precision.
This approach also transforms how we think about software maintenance. Instead of constantly tweaking code, we’re refining our vision statements. When requirements change, we update the vision, not the implementation. The AI handles the heavy lifting of translating vision changes into code changes. It’s like having an architect who can instantly redraw blueprints based on your evolving needs.
Now, I know what some of you are thinking: “This sounds great, but does it actually work in the real world?” Let me share a quick example. A fintech startup I advised was building a fraud detection system. Instead of specifying algorithms and thresholds, they described their vision: “We want to catch fraudulent transactions with 99% accuracy while minimizing false positives for legitimate customers, and we need the system to adapt as fraud patterns evolve.” The AI-generated system not only met these goals but identified novel fraud patterns the team hadn’t anticipated.
Vision Steering isn’t just about better prompts – it’s about a fundamental shift in how we approach software creation. We’re moving from being code writers to being vision crafters. Our value isn’t in how many lines of code we can write, but in how clearly we can articulate what needs to be built and why.
As we embrace this approach, we’re seeing the emergence of what I call “intention portfolios” – collections of well-crafted vision statements that become the true assets of software organizations. These are the golden contracts that Qgenius talks about, and they’re becoming more valuable than any specific implementation.
So here’s my challenge to you: next time you’re working with AI to build something, don’t just tell it what to do. Share your vision. Describe the experience you want to create, the problems you’re solving, the constraints you’re working within. You’ll be amazed at how much more intelligent and helpful your AI partner becomes.
The future of software isn’t about writing better code – it’s about having better visions. And honestly, isn’t that what we should have been focusing on all along?