Vibe Coding Is Killing Your Software

By Lorde Astor West 8/13/2025

First it was “move fast and break sh*t.” Then “fail fast.” Now it’s “vibe coding” — the practice of leaning on AI to generate code without structure, rationale, or long-term stability.

The Illusion of Progress

Every few years, startup culture invents a new way to justify fragility. First it was “move fast and break things.” Then “fail fast.” Now it’s “vibe coding” — the practice of leaning on AI to generate code without structure, rationale, or long-term stability.

On the surface, vibe coding feels like progress: instant prototypes, features shipped overnight, tickets closed at record speed. But the gains are often an illusion. Developers spend an average of 33% of their time dealing with technical debt (CIO.com/Stripe), a figure already straining budgets before generative AI entered the picture. With AI’s tendency to hallucinate non-existent functions, APIs, or libraries, that time sink is only growing.

Studies show 70% of startups fail between their second and fifth years (Embroker, DemandSage, FF.co) — exactly the moment when traction requires scale. These failures are typically attributed to surface-level causes: no market need (42%), running out of funding (29%), wrong team (23%), being outcompeted (19%), pricing mistakes (18%), poor product (17%), poor marketing (14%), ignoring customers (14%), or mistimed launches (10%).

But beneath those numbers lies a more systemic pattern — what we call the Invisible Cliff.

The Invisible Cliff

The Invisible Cliff describes the point where early traction collides with brittle technology. Founders who survive year one are often celebrated for having “muscle” or grit. They ship an MVP, land investors, maybe even grow revenue. But when demand increases, the same architecture that fueled their early success begins to collapse.

At this stage, startups face the impossible task of rebuilding their software while keeping investors and customers satisfied. It’s the classic paradox: “building the plane while flying it.” Except here, you’re building the plane as it falls out of the sky.

Historically, this cliff emerged from cultural conditioning. Founders were told to:

• Fail fast — prioritize speed over resilience.

• Build fast, break sh*t — embrace chaos as innovation.

• Make it up as you go — improvise instead of engineer.

That ethos rewarded fragility. Founders learned that shipping something, anything, was the surest path to funding. Whether the foundation could survive scale was someone else’s problem — often a Series B investor’s or a new CTO’s.

Enter Vibe Coding: Accelerant on the Fire

Vibe coding doesn’t solve the cliff — it accelerates the fall.

• Illusion of productivity: AI-generated code creates a sense of momentum, but hallucinations and brittle modules accumulate technical debt at exponential rates. A GitHub Copilot study found developers completed tasks 55.8% faster with AI, but that figure ignores time later spent fixing or stabilizing the output.

• Security risks: Hallucinated package names or phantom APIs create fertile ground for supply-chain attacks. USENIX researchers warn that malicious actors can hijack builds by exploiting hallucinated components.

• Team strain: Forrester predicts that by 2026, 75% of technology leaders will face moderate to severe technical debt. That burden forces engineering teams into firefighting mode, burning morale and widening founder-team conflicts.

• Competitive disadvantage: While one startup rebuilds its brittle AI-generated scaffolding, a rival with stronger infrastructure absorbs its churned customers.

The result is an ecosystem where startups appear to move faster — until they hit the cliff harder and earlier.

How the Cliff Connects to Classic Failure Modes

Every major startup failure reason is amplified by fragile, disconnected infrastructure - vibe coding is making this worse:

• No Market Need (42%) → Teams confuse shipping speed with validation. Building quickly is not the same as solving a problem.

• Ran Out of Funding (29%) → Rebuilds drain cash at the exact moment growth capital is hardest to secure.

• Wrong Team (23%) → Developers become debt-managers, not innovators, leading to burnout and founder conflict.

• Outcompeted (19%) → Competitors with sturdier systems scale faster and poach customers.

• Pricing/Cost Issues (18%) → Tech debt consumes margins, making pricing models unsustainable.

• Poor Product (17%) → Hallucinations and weak framing create buggy user experiences, driving churn.

• Poor Marketing (14%) / Ignoring Customers (14%) → Teams buried in firefighting stop listening externally.

• Mistiming (10%) → Launching too early with fragile scaffolding leads to outages; launching too late happens when rebuilds devour runway.

The common thread: startups don’t fail because their idea is bad. They fail because the foundation is too fragile to survive scale.

Beyond the Cliff: What Comes Next

The economic stakes are enormous. Estimates place the cost of poor-quality software and technical debt in the hundreds of billions annually (McKinsey, Stripe). Some early analysts argue vibe coding could push that burden toward $1.5 trillion by 2027 (Goenka, Medium). Whether or not the number proves accurate, the trajectory is clear: fragility is becoming systemic.

Yet the solution is not abandoning AI. Used well, AI can augment disciplined engineering practices, accelerate repetitive tasks, and reduce entry barriers. But used as a crutch, it locks founders into the very death cycle they thought they were escaping.

Startups don’t need more disposable apps. They need foundations that scale without rebuilds. Infrastructure that absorbs growth instead of collapsing under it. Tools that give founders ownership, continuity, and resilience — not illusions of speed.

The Final Word

The Invisible Cliff has always been there. It’s where fragile MVPs, “fail fast” cultures, and “build fast, break sh*t” mantras collide with the demands of real customers. Vibe coding hasn’t removed that cliff — it’s made it steeper.

If we want to see startups survive past year five, we don’t need faster vibes. We need stronger foundations.n of Progress

Every few years, startup culture invents a new way to justify fragility. First it was “move fast and break things.” Then “fail fast.” Now it’s “vibe coding” — the practice of leaning on AI to generate code without structure, rationale, or long-term stability.

On the surface, vibe coding feels like progress: instant prototypes, features shipped overnight, tickets closed at record speed. But the gains are often an illusion. Developers spend an average of 33% of their time dealing with technical debt (CIO.com/Stripe), a figure already straining budgets before generative AI entered the picture. With AI’s tendency to hallucinate non-existent functions, APIs, or libraries, that time sink is only growing.

Studies show 70% of startups fail between their second and fifth years (Embroker, DemandSage, FF.co) — exactly the moment when traction requires scale. These failures are typically attributed to surface-level causes: no market need (42%), running out of funding (29%), wrong team (23%), being outcompeted (19%), pricing mistakes (18%), poor product (17%), poor marketing (14%), ignoring customers (14%), or mistimed launches (10%).

But beneath those numbers lies a more systemic pattern — what we call the Invisible Cliff.

The Invisible Cliff

The Invisible Cliff describes the point where early traction collides with brittle technology. Founders who survive year one are often celebrated for having “muscle” or grit. They ship an MVP, land investors, maybe even grow revenue. But when demand increases, the same architecture that fueled their early success begins to collapse.

At this stage, startups face the impossible task of rebuilding their software while keeping investors and customers satisfied. It’s the classic paradox: “building the plane while flying it.” Except here, you’re building the plane as it falls out of the sky.

Historically, this cliff emerged from cultural conditioning. Founders were told to:

• Fail fast — prioritize speed over resilience.

• Build fast, break sh*t — embrace chaos as innovation.

• Make it up as you go — improvise instead of engineer.

That ethos rewarded fragility. Founders learned that shipping something, anything, was the surest path to funding. Whether the foundation could survive scale was someone else’s problem — often a Series B investor’s or a new CTO’s.

Enter Vibe Coding: Accelerant on the Fire

Vibe coding doesn’t solve the cliff — it accelerates the fall.

• Illusion of productivity: AI-generated code creates a sense of momentum, but hallucinations and brittle modules accumulate technical debt at exponential rates. A GitHub Copilot study found developers completed tasks 55.8% faster with AI, but that figure ignores time later spent fixing or stabilizing the output.

• Security risks: Hallucinated package names or phantom APIs create fertile ground for supply-chain attacks. USENIX researchers warn that malicious actors can hijack builds by exploiting hallucinated components.

• Team strain: Forrester predicts that by 2026, 75% of technology leaders will face moderate to severe technical debt. That burden forces engineering teams into firefighting mode, burning morale and widening founder-team conflicts.

• Competitive disadvantage: While one startup rebuilds its brittle AI-generated scaffolding, a rival with stronger infrastructure absorbs its churned customers.

The result is an ecosystem where startups appear to move faster — until they hit the cliff harder and earlier.

How the Cliff Connects to Classic Failure Modes

Every major startup failure reason is amplified by fragile, disconnected infrastructure - vibe coding is making this worse:

• No Market Need (42%) → Teams confuse shipping speed with validation. Building quickly is not the same as solving a problem.

• Ran Out of Funding (29%) → Rebuilds drain cash at the exact moment growth capital is hardest to secure.

• Wrong Team (23%) → Developers become debt-managers, not innovators, leading to burnout and founder conflict.

• Outcompeted (19%) → Competitors with sturdier systems scale faster and poach customers.

• Pricing/Cost Issues (18%) → Tech debt consumes margins, making pricing models unsustainable.

• Poor Product (17%) → Hallucinations and weak framing create buggy user experiences, driving churn.

• Poor Marketing (14%) / Ignoring Customers (14%) → Teams buried in firefighting stop listening externally.

• Mistiming (10%) → Launching too early with fragile scaffolding leads to outages; launching too late happens when rebuilds devour runway.

The common thread: startups don’t fail because their idea is bad. They fail because the foundation is too fragile to survive scale.

Beyond the Cliff: What Comes Next

The economic stakes are enormous. Estimates place the cost of poor-quality software and technical debt in the hundreds of billions annually (McKinsey, Stripe). Some early analysts argue vibe coding could push that burden toward $1.5 trillion by 2027 (Goenka, Medium). Whether or not the number proves accurate, the trajectory is clear: fragility is becoming systemic.

Yet the solution is not abandoning AI. Used well, AI can augment disciplined engineering practices, accelerate repetitive tasks, and reduce entry barriers. But used as a crutch, it locks founders into the very death cycle they thought they were escaping.

Startups don’t need more disposable apps. They need foundations that scale without rebuilds. Infrastructure that absorbs growth instead of collapsing under it. Tools that give founders ownership, continuity, and resilience — not illusions of speed.

The Final Word

The Invisible Cliff has always been there. It’s where fragile MVPs, “fail fast” cultures, and “build fast, break sh*t” mantras collide with the demands of real customers. Vibe coding hasn’t removed that cliff — it’s made it steeper.

If we want to see startups survive past year five, we don’t need faster vibes. We need stronger foundations.

Every few years, startup culture invents a new way to justify fragility. First it was “move fast and break things.” Then “fail fast.” Now it’s “vibe coding” — the practice of leaning on AI to generate code without structure, rationale, or long-term stability.

On the surface, vibe coding feels like progress: instant prototypes, features shipped overnight, tickets closed at record speed. But the gains are often an illusion. Developers spend an average of 33% of their time dealing with technical debt (CIO.com/Stripe), a figure already straining budgets before generative AI entered the picture. With AI’s tendency to hallucinate non-existent functions, APIs, or libraries, that time sink is only growing.

Studies show 70% of startups fail between their second and fifth years (Embroker, DemandSage, FF.co) — exactly the moment when traction requires scale. These failures are typically attributed to surface-level causes: no market need (42%), running out of funding (29%), wrong team (23%), being outcompeted (19%), pricing mistakes (18%), poor product (17%), poor marketing (14%), ignoring customers (14%), or mistimed launches (10%).

But beneath those numbers lies a more systemic pattern — what we call the Invisible Cliff.

The Invisible Cliff

The Invisible Cliff describes the point where early traction collides with brittle technology. Founders who survive year one are often celebrated for having “muscle” or grit. They ship an MVP, land investors, maybe even grow revenue. But when demand increases, the same architecture that fueled their early success begins to collapse.

At this stage, startups face the impossible task of rebuilding their software while keeping investors and customers satisfied. It’s the classic paradox: “building the plane while flying it.” Except here, you’re building the plane as it falls out of the sky.

Historically, this cliff emerged from cultural conditioning. Founders were told to:

• Fail fast — prioritize speed over resilience.

• Build fast, break sh*t — embrace chaos as innovation.

• Make it up as you go — improvise instead of engineer.

That ethos rewarded fragility. Founders learned that shipping something, anything, was the surest path to funding. Whether the foundation could survive scale was someone else’s problem — often a Series B investor’s or a new CTO’s.

Enter Vibe Coding: Accelerant on the Fire

Vibe coding doesn’t solve the cliff — it accelerates the fall.

• Illusion of productivity: AI-generated code creates a sense of momentum, but hallucinations and brittle modules accumulate technical debt at exponential rates. A GitHub Copilot study found developers completed tasks 55.8% faster with AI, but that figure ignores time later spent fixing or stabilizing the output.

• Security risks: Hallucinated package names or phantom APIs create fertile ground for supply-chain attacks. USENIX researchers warn that malicious actors can hijack builds by exploiting hallucinated components.

• Team strain: Forrester predicts that by 2026, 75% of technology leaders will face moderate to severe technical debt. That burden forces engineering teams into firefighting mode, burning morale and widening founder-team conflicts.

• Competitive disadvantage: While one startup rebuilds its brittle AI-generated scaffolding, a rival with stronger infrastructure absorbs its churned customers.

The result is an ecosystem where startups appear to move faster — until they hit the cliff harder and earlier.

How the Cliff Connects to Classic Failure Modes

Every major startup failure reason is amplified by fragile, disconnected infrastructure - vibe coding is making this worse:

• No Market Need (42%) → Teams confuse shipping speed with validation. Building quickly is not the same as solving a problem.

• Ran Out of Funding (29%) → Rebuilds drain cash at the exact moment growth capital is hardest to secure.

• Wrong Team (23%) → Developers become debt-managers, not innovators, leading to burnout and founder conflict.

• Outcompeted (19%) → Competitors with sturdier systems scale faster and poach customers.

• Pricing/Cost Issues (18%) → Tech debt consumes margins, making pricing models unsustainable.

• Poor Product (17%) → Hallucinations and weak framing create buggy user experiences, driving churn.

• Poor Marketing (14%) / Ignoring Customers (14%) → Teams buried in firefighting stop listening externally.

• Mistiming (10%) → Launching too early with fragile scaffolding leads to outages; launching too late happens when rebuilds devour runway.

The common thread: startups don’t fail because their idea is bad. They fail because the foundation is too fragile to survive scale.

Beyond the Cliff: What Comes Next

The economic stakes are enormous. Estimates place the cost of poor-quality software and technical debt in the hundreds of billions annually (McKinsey, Stripe). Some early analysts argue vibe coding could push that burden toward $1.5 trillion by 2027 (Goenka, Medium). Whether or not the number proves accurate, the trajectory is clear: fragility is becoming systemic.

Yet the solution is not abandoning AI. Used well, AI can augment disciplined engineering practices, accelerate repetitive tasks, and reduce entry barriers. But used as a crutch, it locks founders into the very death cycle they thought they were escaping.

Startups don’t need more disposable apps. They need foundations that scale without rebuilds. Infrastructure that absorbs growth instead of collapsing under it. Tools that give founders ownership, continuity, and resilience — not illusions of speed.

The Final Word

The Invisible Cliff has always been there. It’s where fragile MVPs, “fail fast” cultures, and “build fast, break sh*t” mantras collide with the demands of real customers. Vibe coding hasn’t removed that cliff — it’s made it steeper.

If we want to see startups survive past year five, we don’t need faster vibes. We need stronger foundations.