Technical Debt, Vibe Coding and B2B Tech Growth: a Trade-off Variable, Not a Technical Topic

When growth slows, the reactions are often predictable:

• reinforce sales
• adjust marketing
• question the product

These reflexes are understandable.
But they rest on a fragmented reading.

Growth is not corrected in silos.
It depends on the coherence of a system.

In this system, some variables remain underestimated. Not because they are secondary, but because they are poorly qualified.

Technical debt is one of them.

What is technical debt and why does it impact growth?

Technical debt refers to the set of compromises accumulated over time, often to accelerate delivery.

It is now amplified by the rise of generative AI and code assistants.

It is generally treated as an engineering topic.

That is precisely what limits how it is read.

Because its effects are not technical.
They are organizational, economic and strategic.

It shows up as:

• a loss of speed in execution
• a difficulty evolving the offering
• a growing tension between teams
• a progressive increase in costs

👉 It directly impacts code sustainability, and therefore the organization's capacity to sustain its growth over time.

Accelerating time-to-market without controlling TCO: an unmade trade-off

Acceleration has become an objective in itself.

Generative AI now makes it possible to:

• produce faster
• launch earlier
• reduce initial costs

But this movement shifts constraints over time.

• evolutions slow down
• costs accumulate
• complexity increases

👉 The issue is not speed.

👉 It is the nature of the trade-offs made.

Time-to-market and TCO are not independent.
When they are not explicitly arbitrated, they come into tension.

Technical debt and misalignment of the growth system

Technical debt becomes critical when it creates a gap between:

• what is sold
• what is delivered
• what can evolve

This gap builds progressively.

At first, teams compensate.
Then the system becomes strained.

👉 Growth does not disappear. It becomes unstable.

A direct impact on retention

Technical debt materializes on the client side as:

• longer evolution timelines
• inconsistencies in the experience
• promises hard to keep

👉 Retention becomes a direct function of the ability to evolve the offering.

A structural impact on profitability

Technical debt acts as a silent economic constraint.

• increase in marginal cost
• difficulty industrializing
• increased dependency

👉 The model remains viable. But it becomes less and less scalable.

AI, LLM and vibe coding: acceleration or amplification?

AI is profoundly transforming software production.

With the rise of vibe coding, organizations produce faster.

Current debates focus on:

• code maintainability
• LLM performance
• reducing complexity or duplication

But this reading remains partial.

👉 It addresses code quality.

👉 Not its sustainability within a growth system.

Vibe coding does not eliminate technical debt.
It can, on the contrary, accelerate its formation without a clear framework.

👉 The issue is not the model. It is the decision framework within which it is used.

Repositioning technical debt within governance

Technical debt is not solved.
It is arbitrated.

Making it visible

• impact on timelines
• impact on costs
• impact on scalability

Making the trade-offs explicit

• speed vs sustainability
• short term vs TCO
• delivery vs scalability

👉 These trade-offs are rarely made explicit.
Yet they structure the growth trajectory.

Conclusion

The debate on the maintainability of AI-generated code is now widely established.

But it is often still treated as a question of model or performance.

👉 The real issue lies elsewhere: it concerns code sustainability within a growth system.

In some trajectories, what appears to be a profitability or positioning problem is in fact reinforced by an inability to evolve the product quickly.