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.
Top comments (2)
Spot on about the "who can build" shift. I vibe-coded 4 apps over 3 months as a weekend side project - stuff that would've taken me a year with traditional approaches. The democratization is real.
But the security gap is what keeps me up at night. AI-generated code tends to reach for convenience patterns - hardcoded secrets, broken auth flows, missing input validation. The code works, passes the demo, and ships with vulnerabilities baked in.
The worst part? Most vibe coders (myself included at first) don't even know what to look for. You can't catch what you can't recognize. That's where I think the tooling needs to catch up - automated security scanning specifically tuned for AI-generated code patterns, not just traditional SAST rules.
This is the cleanest take I’ve seen on vibe coding in a minute: it changed who can build, not what it takes to build something that survives reality.
The line that hit hardest is basically “the expensive problems don’t show up in demos.” Because yeah — you can vibe your way to a prototype, but you can’t vibe your way around requirements clarity, security boundaries, latency budgets, testing strategy, and all the unsexy non-functionals that show up the moment users + money get involved.
I also like that you didn’t go full “vibe coding bad” elitism. It’s clearly a legit tool for exploration. The problem is when teams mistake “it works on my laptop” for “it’s engineered.”
The MAS point is interesting too, and I agree with the warning: without orchestration, you’re not scaling engineering — you’re scaling chaos. Multi-agent setups only become useful when there’s an actual coordination layer that enforces sequencing, verification, and fallbacks (planner → builder → reviewer → tester, etc.)… basically turning the AI from a hype machine into a workflow.
If anything, the “middle ground” I’m betting on is: fast prototyping + ledgered decisions. Like, capture constraints and architectural choices as first-class artifacts while you move fast, so you don’t wake up 3 weeks later with a working mess and zero explanation.
Curious question for you: what’s the smallest “orchestration layer” you think is worth it for a solo dev? Like the minimum set of gates that turns vibe coding into something you can maintain without hiring Future You as an unpaid firefighter.