From Vibes to Steering: The Evolution of AI-Assisted Development
Back in February 2025, Andrej Karpathy posted on X and sent ripples through developer circles: "Don't fight the AI. Just vibe." And with that, Vibe Coding was born.
At first glance, it sounds like a classic tech meme. But digging a little deeper, this seems to be a genuine shift in how we approach coding and software development. The premise is simple: describe what you want in natural language, and the AI writes the code. No manual typing. No diff-checking. Just prompt → generate → test → iterate.
It's like ordering food at a restaurant. You're the customer (the developer), the waiter is your AI interface (Claude, GPT, Copilot, pick your tool), and the chef is the model itself. You don't need to know the recipe or understand the kitchen workflow — you just say what you want, and minutes later, it arrives on a plate.
Sweet.
But Here's the Problem...
Vibe Coding is brilliant for prototyping. It's perfect for quick builds, POCs, and getting ideas off the ground fast. But here's the thing: you wouldn't expect a restaurant customer to design the entire menu. That takes collaboration — chefs, kitchen staff, suppliers, and probably someone from finance arguing about the costs.
Producing production-ready code is no different. You need more than vibes. You need steering.
Enter: Steer Coding
Steer Coding is the middle ground between traditional manual coding and pure AI generation. It's about guiding the AI with human expertise, context, and judgement. You're not passively accepting whatever the model generates — you're actively shaping it, correcting it, and collaborating with it.
It's less "press play" and more "conducting the orchestra."
The AI provides the raw capability and speed. You provide the direction, domain knowledge, and quality control. Together, you build something that works in production.
How We Make Steer Coding Work
Here's what Steer Coding looks like in practice:
1. Documentation is Your Secret Weapon
AI models are trained on static datasets. They don't automatically know about your internal systems, latest framework versions, or a critical change from last Tuesday. The AI needs to be fed with fresh, relevant documentation and watch accuracy skyrocket.
We can use tools like MCP servers and custom context files to give AI agents real-time access to:
- Internal wikis and architecture docs
- API specifications and schemas
- Infrastructure-as-Code templates
- Recent changelog entries
2. Prompting is a Skill
A well-crafted prompt can kickstart an entire project. A lazy prompt gets you... well, lazy code. Be specific. Provide examples. Set constraints. Give context.
Instead of:
"Fix this script"
Try:
"Analyse this Azure provider registration script and enhance it with:
- Error handling for failed API calls
- Progress tracking with counters (processed/total subscriptions)
- Parallel execution using PowerShell jobs
- Summary report of registration status
- Retry logic for transient failures
Maintain the existing logic flow and ensure backward compatibility. Follow PowerShell best practices and add proper inline comments."
See the difference?
3. Understanding Beats Blind Trust
Even if the AI generates code in a language you’re not fluent in, you can use comments, AI-generated documentation, and code review tools to understand the logic. Never deploy what you don’t understand.
Ask questions. Request explanations. Have the AI document its own code. Make it prove its reasoning.
4. Review, Refine, Repeat
AI reviewing AI is fascinating. But human review is still essential for production readiness. Run linters. Check security. Validate against your standards. Test edge cases.
Beyond Just Code
Here's where it gets really interesting: Steer Coding isn't just about writing functions and classes. AI agents can:
- Generate project plans based on requirements docs
- Gather and synthesise documentation from multiple sources
- Handle third-party integrations with minimal manual config
- Audit existing codebases and suggest improvements
The Secret Weapon: Just Ask "Why?"
When the AI generates something that looks weird, suspicious, or just plain wrong — don't silently fix it. Ask why.
"Why did you use this API version instead of the latest stable?"
"Why did you choose this data structure?"
"Why did you filter results this way?"
Nine times out of ten, the AI will explain its reasoning. And often, it'll catch its own mistakes and self-correct. It's not perfect, but it's fast, and it's getting better every single day.
The Future is Steered, Not Just Vibed
Vibe Coding is fun and it feels like magic when it works.
But Steer Coding is the future — because it combines the best of both worlds: AI speed and human wisdom.
We're not replacing developers. We're giving them superpowers to build faster, explore wider, and deliver better.