Beyond the Vibes: Vibe Coding Changed Who Can Build, Not How Software Should Be Built
In the last few years, vibe coding has taken center stage by changing who can build software, but not what it takes to build it well. It is a development style defined by natural language prompts, rapid iteration, and an emphasis on getting things working fast.
Powered by AI-assisted tools and accessible platforms, vibe coding has genuinely democratized building . Startups, solo devs, and even non-technical founders can now create prototypes in hours, not months. That’s worth celebrating.
But as the hype grows, an important distinction is getting lost in the noise.
We’re starting to confuse vibe coding with software engineering.
And while they both involve code, they serve very different purposes and come with very different risks.
Where Vibe Coding Shines
Vibe coding works best when you’re:
- Testing an idea
- Prototyping fast
- Building internal tools
- Exploring creatively
It accelerates iteration and lowers the cost of experimentation. It’s a massive enabler for innovation, especially in early-stage product work.
The market agrees. According to Roots Analysis, the global vibe coding market is expected to grow from $2.96B in 2025 to $325B by 2040 - a 36.79% CAGR.
But the faster something grows, the more important it becomes to ask:
Is this still the right tool for the job?
The Foundations Vibe Coding Often Skips
What vibe coding often skips, and what experienced developers obsess over, are the foundations that keep systems standing:
- Clear, stable requirements
- Non-functional constraints (scale, security, latency)
- Architectural boundaries
- Testing strategies
- Maintainability
- Long-term risk
The Most Expensive Problems Don’t Show Up in Demos
In vibe coding, it’s easy to build something that feels finished, but ultimately collapses when it’s time to expose it to real users, real load, or when it’s time to scale. We’ve seen projects that look great on the surface but require complete rewrites just to support users, integrate with systems, or handle basic growth.
It’s not a failure of intent but a misunderstanding of complexity.
Traditional Engineering Brings Weight
Professional software development brings structure and, with it, intentional weight:
- It’s more expensive
- It takes longer
- It often requires external talent (agencies, architects, senior engineers)
- And it can feel heavy for early-stage work
But when the goal is durability, this is the discipline that delivers it. You’re building something to last. You need it to handle change, load, integration, regulation - things that don’t show up in a prototype demo.
Still, this is where many builders get stuck: cost and speed.
That's where many builders hit a wall.
A New Middle Ground: Orchestrated Multi-Agent Systems
So, what comes next?
We believe the next evolution isn’t about choosing between speed or structure, it’s about deliberately combining both.
Enter multi-agent systems (MAS). Autonomous agents that specialize in different aspects of the software lifecycle (planning, architecture, coding, testing, optimization).
Without Orchestration, AI Just Scales Chaos
Crucially, the breakthrough isn't the agents themselves. It's in the orchestration layer.
Without orchestration, agents operate in silos.
With orchestration, they act like a coordinated engineering team.
What MAS Orchestration Enables:
- Sequenced collaboration across AI agents (e.g. planner → coder → reviewer → tester)
- Integrated workflows across tools, platforms, and services
- Parallel execution to reduce latency and speed up delivery
- Maintainability through modular agent updates without breaking the system
- Smarter fallback and reliability mechanisms (e.g. retries, circuit breakers, role reassignment)
In short: orchestration turns "vibe" into "system".
We Use This Because We Want To Ship
At Brunelly, we didn’t adopt orchestration as a theory. We use it because we have to ship real systems. Our CTO refers to LLMs as “a slightly messier version of me.” And that is impressive.
If you want to read more about Brunelly’s orchestration, check out our CTO’s Guy Powell’s Substack.
Or if you prefer to test it out for yourself, feel free it’s live!
Three Phases of Modern Software Building
As we move into 2026, here’s the shift we see:
You Don’t Need Extremes. You Need Intent.
You don’t need to abandon vibe coding or overinvest in full-stack teams before you’re ready.
But if you're trying to build something credible and scalable, and you're looking for that elusive balance between speed and structure, multi-agent orchestration may offer a smarter third path.
Final Thought: Speed Is Optional. Clarity Isn’t.
The real question isn’t whether vibe coding is “good” or “bad.”
The question is: What are you building, and what will it take to get it there?
If you're testing the waters, move fast and explore.
If you're building the backbone of a product or company, slow down, think deeply, and choose the right system.
And 2026 is going to reward the teams who can do both intelligently.
This lines up with what we see on the delivery side. The gap isn't really "vibe coding vs. traditional engineering," it's that vibe coding collapses the cost of writing code to near zero while leaving the cost of everything else (architecture decisions, integration, scaling, security review) exactly where it was. That mismatch is what causes the rewrite cycle you're describing. Where this gets practical for founders: an AI-augmented dev team isn't just "vibe coding with adults supervising," it's using the speed of AI-assisted generation for the parts that are genuinely fast (boilerplate, CRUD, first-pass UI) while keeping human judgment on the parts that were never actually the bottleneck, like requirements clarity and architectural tradeoffs. At 6senseHQ that's basically our working model: AI accelerates throughput, but a senior engineer still owns every architecture decision before it ships. The orchestration point you're making is right, the question is just whether the orchestration layer is a multi-agent system or a person who's done this before. Both work. Most teams just haven't decided which one they're actually building.
We’ve been seeing the same that the vibe coding helps generate pipelines quickly, but ensuring they’re production-ready is a different game. Bridging that gap between speed and structure is where a lot of innovation is happening right now.
Interesting take — the “vibe coding” concept has energy, but right now it leans more poetic than practical for founders thinking about outcomes and real product decisions.
To go from nice idea to something that actually shapes behavior, you need sharper examples tied to measurable impact — not just feeling.
Happy to share feedback on how to anchor this in clear, actionable value that gets people genuinely excited (and ready to hire support).
Fair point, and I agree that poetry doesn’t ship products.
The intent of the piece wasn’t to romanticise “vibes,” it was to draw a hard line between prototype velocity and production durability. The measurable impact shows up when you look at rewrite rates, post-launch defect density, security exposure, integration cost, and time-to-scale. Vibe coding optimises time-to-demo. It does not optimise mean-time-to-recovery, SLA compliance, or long-term maintenance burden. That gap is where behavior changes.
When a founder moves from “it works” to “it survives contact with users, load, and integration constraints,” their decision-making changes. They start budgeting for architecture, review gates, validation layers, and orchestration. That’s not aesthetic, that’s operational.
If the article sparked that shift in even a few builders, from chasing speed to designing systems intentionally, then it’s already shaping outcomes.