Why Vibe-Based Coding Fails: The Hidden Product Crisis
Your engineering team is crushing it. They're shipping features every sprint, closing tickets, hitting velocity targets. The Jira board is a beautiful gradient of green. Everyone's feeling productive.
Then you check the analytics. The feature that took three sprints? 2% adoption. The "game-changing" API refactor? Breaking changes that pissed off half your integration partners. That mobile redesign? Support tickets up 40%.
Welcome to vibe-based coding. Where engineers build what feels right instead of what matters.
The Vibe Economy
I've watched this pattern destroy otherwise competent teams. An engineer gets excited about a technical approach. They convince themselves users need it. They build it beautifully. Nobody uses it.
The problem isn't skill. It's that most development decisions happen in a vacuum. You're three layers deep in a React component when you decide to add a feature. It feels like the right move. The code is right there. Why not make it better?
Because "better" is subjective. Your idea of better might be technically elegant but completely disconnected from what users actually need.
Here's what vibe-based coding looks like in practice:
The "While I'm Here" Feature: You're fixing a bug in the checkout flow. You notice the UI could be cleaner. Two days later, you've rebuilt the entire component with better animations. Users now complain the new flow is confusing.
The Premature Abstraction: You see similar code in three places. Your engineer brain screams "DRY!" You build an abstraction layer. Six months later, each use case has diverged, and now you're fighting your own abstraction.
The "Trust Me" Architecture: A senior engineer convinces everyone to migrate to a new framework. The migration takes six months. The new framework doesn't solve any actual user problems. But hey, it's more modern.
The common thread? Decisions driven by what feels right to the person writing the code, not what the product actually needs.
The Product Disconnect
Most engineers never see the full product picture. They shouldn't have to—that's not their job. But when nobody connects code to actual requirements, you get features that solve problems that don't exist.
I talked to a PM at a Series B startup last month. Their team built a sophisticated recommendation engine for their e-commerce platform. Impressive ML work. Clean architecture. Deployed without issues.
Problem: Their users were small businesses managing 20-30 products. They didn't need recommendations. They needed better inventory management. The data showed it clearly—customers were churning because they couldn't track stock levels, not because they couldn't find products.
The engineering team had optimized for a problem that didn't exist at their scale. Why? Because recommendations felt like the next logical feature. Every major e-commerce platform has them. It was technically interesting. And nobody explicitly told them not to build it.
This happens constantly. Engineers make reasonable assumptions about what matters. Those assumptions are wrong. By the time someone notices, you've burned weeks of development time.
The Spec-Code Gap
The classic solution is "write better specs." But specs rot faster than produce at a farmers market.
You write a detailed spec. It gets reviewed and approved. Engineering starts building. Two weeks in, someone realizes the spec missed an edge case. A customer request changes priorities. A competitor ships something adjacent. The market shifts.
The spec is now outdated. But the code keeps growing based on the original requirements. The gap widens. Eventually, you ship something that was perfect six weeks ago but irrelevant today.
Most teams handle this with "agile" meetings. Daily standups. Sprint planning. Retros. More meetings to discuss the meetings. Everyone stays aligned for exactly as long as the meeting lasts.
The fundamental problem: requirements live in docs and Notion pages. Code lives in repositories. There's no mechanical connection between them. When requirements change, the code doesn't know. When code grows, the requirements don't update.
Glue actually solves this by treating requirements as first-class citizens in your codebase. It discovers what features exist from your actual code, maps them to specs and competitive intelligence, and shows you the gaps in real-time. You can see which features are over-engineered and which critical requirements have no code backing them up.
The Competitive Blind Spot
Here's a fun exercise: Ask your engineers what features your top competitor has that you don't.
They'll struggle. Not because they're not smart—because they're focused on code, not competitive positioning. They know what they're building. They might know what's in the backlog. They probably don't track what competitors shipped last month.
So you get surprised. A competitor launches a feature your customers immediately ask for. Your team scrambles. You rush something to market. It's half-baked because you're playing catch-up.
Or worse: you build features your competitors deprecated months ago because they didn't work.
One team I worked with spent two months building a complex multi-tenant permission system. Beautiful work. Granular controls. Role-based access. The whole nine yards.
Their main competitor had shipped the same thing a year earlier. Then simplified it dramatically after user research showed customers wanted three roles, not thirty. All that information was public in their changelog and user forums.
The team built the complicated version because it felt more complete. They didn't check if complicated was actually better. Now they're maintaining a system that's too complex for their users, just like their competitor discovered.
This is vibe coding at scale. You're building blind, guided by what feels professional instead of what actually works.
The Knowledge Trap
The worst part? The people who know what matters aren't the ones writing code.
Your PM knows which features are actually moving metrics. Your support team knows which bugs are costing you customers. Your sales team knows which features close deals.
Your engineers know which components are brittle and which APIs are clean.
These groups rarely talk in detail. When they do, it's in meetings where context gets compressed into action items. The nuance disappears.
An engineer asks "Should we build feature X?" The PM says "Sure, but prioritize Y first." The engineer hears "Build both eventually." The PM meant "X is not important right now and might never be."
Multiply this across every decision and you get codebases full of features that made sense in a meeting but don't make sense in production.
The Metrics Illusion
Teams try to solve this with metrics. Sprint velocity. Story points completed. Lines of code. Deployment frequency.
These measure activity, not value. You can ship ten features in a sprint and move exactly zero business metrics. You can have perfect velocity while building a product nobody wants.
The metrics that actually matter—user adoption, retention, revenue impact—live in analytics tools. Disconnected from code. You ship something, then wait weeks to see if it mattered. By then, you've already started building the next thing.
This delay is deadly. It means you're always operating on outdated information. You're building today based on what seemed important last month, which was decided based on data from two months ago.
Glue surfaces this in real-time by connecting your code to actual usage data and product KPIs. You can see which features are over-invested (lots of code, low usage) and which are under-invested (high usage, accumulating tech debt). It's like having a product health dashboard that actually talks to your codebase.
The Fix Isn't More Process
The standard response to vibe coding is more process. More planning meetings. More detailed specs. More approval gates. More documentation.
This doesn't work. More process means more overhead, slower shipping, and frustrated engineers who feel micromanaged. The vibe coding doesn't stop—it just gets hidden better.
The real fix is mechanical connection. Code should know what it's for. Features should trace back to requirements. Requirements should update when reality changes.
This isn't about process discipline. It's about tooling that makes the right information available at decision time. When an engineer is considering a refactor, they should see which features depend on that code and how often users actually use them. When a PM is writing a spec, they should see what code already exists that could be extended versus what needs building from scratch.
Most teams have all this information. It's just scattered. Usage data in Mixpanel. Code in GitHub. Specs in Notion. Competitor intel in random Slack threads. Nobody connects them because connecting them manually is impossible at scale.
What Actually Works
Stop treating code as separate from product strategy. Every line of code is a product decision. Every feature is an investment with opportunity cost.
The teams that get this right don't have more meetings. They have better information flow. Engineers know which features matter and why. PMs know what code exists and what's feasible. Everyone works from the same map of reality.
This requires infrastructure. You need systems that:
Map code to features automatically, not through manual tagging
Connect features to product requirements and competitive intelligence
Surface which code is actually used versus which is maintenance burden
Show knowledge gaps (who knows what and what's at risk if they leave)
Update in real-time as code and requirements change
Glue does this by indexing your entire codebase and product surface area—files, symbols, API routes, database schemas—and using AI agents to discover what features actually exist. Not what your docs claim exists, but what the code does right now. Then it connects those features to specs, competitive gaps, and usage patterns. You get a living map of your product that's always current.
The difference this makes is immediate. Engineers stop building features that sound good and start building features that matter. PMs stop writing specs that get ignored and start working from what actually exists. Everyone argues about priorities based on data instead of vibes.
The Real Cost
Vibe-based coding costs way more than wasted engineering time. It costs market fit.
Every feature you build wrong is a feature you're not building right. Every sprint chasing what feels important is a sprint not chasing what actually matters. Every engineer solving interesting problems instead of user problems is compounding your competitive disadvantage.
Your competitors aren't necessarily better engineers. They might just have better information flow. They know what to build because they've connected code to reality.
You can keep running on vibes. Keep trusting that smart people making reasonable assumptions will somehow converge on the right product. Sometimes it works. Usually it doesn't.
Or you can build the infrastructure that makes vibe coding impossible. Make product context accessible at code time. Make code reality visible at planning time. Stop treating them as separate domains that occasionally sync up in meetings.
The choice is mechanical, not cultural. You can't meeting your way out of this. You need systems that make the right information available when decisions happen. Everything else is just hoping the vibes are right.