🛠️ AI, Vibe-Coding, and the Illusion of Speed
What prepping #VirtualCTOAdvisor for open source taught me about platform responsibility, product thinking, and business risk
While prepping Virtual CTO Advisor for open source, I had AI-assisted tools review the codebase.
The results?
Let’s just say: AI doesn’t take shortcuts — it takes fast paths. And fast ≠ safe.
Cursor, for example, consistently hand-crafted functionality where existing, battle-tested libraries were available. The code worked — until it didn’t. These weren’t bugs. They were design decisions made without context or guardrails.
I call this “vibe-coding” — code that feels right, but isn’t grounded in architectural thinking or platform strategy. It's clever, but not correct.
The Business Risk Behind Clever Code
Here’s the real cost: these hand-rolled solutions introduced fragility into the system.
A simple UI refactor broke multiple answer-rendering paths, all because custom functions weren’t written with composability in mind. I’ve spent the past week untangling bespoke logic — logic that never should’ve been bespoke in the first place.
This isn’t just technical debt — it’s business risk.
🔓 Security: More code = more attack surface.
🔁 Maintainability: Hard-coded logic slows down iteration.
📉 Agility: When every change breaks something, velocity dies.
🛑 Continuity: We've experienced downtime in #VirtualCTOAdvisor due to seemingly small edits surfacing brittle code paths.
If I were running this in production for a client, that fragility could mean customer impact. If this were a regulated industry, those shortcuts could become audit findings.
Platform as a Product (and AI as a User)
Here’s where platform teams come in — and where your Platform-as-a-Product strategy matters.
The platform isn’t just enabling humans anymore. It’s enabling AI.
When an AI agent like Cursor generates code, it behaves like a junior developer with unlimited speed and zero experience. If your platform doesn’t provide paved roads, the AI will happily wander off into the woods — fast.
This is why platforms need to be:
🔋 Batteries-included – sensible defaults, secure patterns, golden paths
🔁 Replaceable – extensible when the defaults don’t fit
🛣️ Opinionated – strong conventions that reduce choice fatigue and complexity
The market often criticizes PaaS (Platform-as-a-Service) for being “too rigid.” I argue that rigidity is a feature when AI is involved. With clearly defined rails, AI-assisted development becomes not just fast — but safe, sustainable, and secure.
This aligns with principles I’ve talked about before around “developer experience as product” and the value of enforcing architecture through enablement, not enforcement.
Lessons from AI Code Review
AI doesn’t understand “production-grade.”
It doesn’t know your threat model.
It doesn’t care about long-term cost.
It only knows what you ask for — and what your platform enables.
That means it’s on us — platform engineers, architects, and technical leaders — to:
Design platforms that guide all developers, including AI
Embed golden paths and guardrails in the developer workflow
Treat architectural decisions as first-order UX concerns
Align AI enablement with business continuity and security posture
Because when you open source a project, or ship it to production, clever-but-fragile code isn’t a flex — it’s a liability.
TL;DR
🤖 AI coding tools move fast — often without context or discipline.
💥 The illusion of speed hides real fragility, especially when custom logic replaces standard patterns.
🛠️ Platform teams must treat AI like a user and design accordingly.
🚧 Rigid platforms aren't bad — they're exactly what AI needs to stay on track.
📉 Left unchecked, AI-generated “vibe code” becomes a silent drag on business agility.
💬 What’s your experience?
If you’ve reviewed AI-generated code and found clever solutions that failed under pressure, reply or drop a comment. I’d love to feature a few examples in a follow-up post on building AI-aware platforms.