Vibe Check: Coding in the AI Era

The result was a working honeypot stood up in a fraction of the time, producing meaningful attacker telemetry far faster than a manual approach would have allowed - giving the team a head start on understanding attacker behavior. For a security team, this means the difference between experimenting in theory versus testing in practice.

The emerging risks leaders need to consider

So, how do you avoid the risks of vibe coding that undermine long-term stability while still capturing its upside?

Security and operational risks

Security and operational risks come with unchecked speed. Moving too fast can create brittle architectures and hidden vulnerabilities within an application, and small oversights can compound quickly at scale. Additionally, you have to be careful about the tool itself. While many vibe coding tools have controls for guardrails like access, identity controls, and data protection in generated code, those safeguards are often left to the discretion of the individual, rather than enforced at the organizational level.

This creates uneven practices across teams - what one developer locks down diligently, another may leave exposed. The result is a patchwork of standards that makes it harder to ensure compliance, introduces blind spots in oversight, and increases the risk of misconfigurations that only surface once the code is deployed. At scale, the lack of organizationally enforced standards means security and quality depend too heavily on individual choices rather than on consistent, repeatable processes.

Oversight and quality control

Operational risks open the question of oversight and quality control. Traditional review processes weren't designed for the sheer volume of code AI can generate, they were designed around human output - tens of lines of code a day and changes that are smaller in scope and easier to track back to an individual developer. Vibe coding shifts that equation: Instead of modest, incremental contributions, AI can produce entire modules, integrations, or thousands of lines in a single session. If quality checks can't keep pace with that scale, organizations risk accountability gaps, eroded trust with customers, and limited visibility into what's actually running in production. Addressing this means rethinking review at scale, and finding new ways to sample, stress-test, and monitor AI-driven code so oversight grows in proportion to output.

Talent risks

Over-reliance on copilots could cause core engineering and security skills to atrophy. If developers lose touch with foundational practices, organizations may end up with teams who can generate prompts but can't diagnose failures, troubleshoot root causes, or design resilient systems from the ground up. That's not a workforce you want to depend on when systems are compromised or breached.

On the upside, vibe coding democratizes code for all. This enables teams to scale output by doing more quickly, allowing for experimentation at scale. Teams can fail fast, refine quickly, and uncover innovative solutions that might not emerge with traditional time and budget constraints.

Guardrails and guidance for vibe coding

Security leaders can create the conditions for vibe coding at a safe speed by investing in automated guardrails, clear governance policies, and structured access models that align with developer experience levels.

For example, do not ship vibe-coded products to customers without rigorous code review and testing. The quality bar cannot slip. Leaders should think of stress testing vibe-coded systems as more than just running automated checks. One way to do this is to plant subtle vulnerabilitiesintentionally: small misconfigurations, minor logic errors, or unusual input cases that mimic the types of issues a malicious actor or real-world use case might expose. This approach reveals weaknesses in oversight, exposes hidden blind spots, and helps teams understand where AI-generated code might introduce fragility. Ultimately, while vibe coding can save time upfront, capturing its full benefits requires leaders to invest extra scrutiny on the back end to prevent compromises to security, resilience, and long-term trust.

Intentional innovation for the win

Vibe coding is neither a silver bullet nor a looming catastrophe. It's a new reality in how code is created. The challenge for leaders isn't whether to allow it, but how to shape its use so it strengthens rather than weakens the enterprise. That means distinguishing between low-risk internal experimentation and high-stakes customer-facing applications, and putting the right guardrails around each.

Innovation will accelerate, but so will complexity and accountability. The leaders who succeed will be those who treat vibe coding not as a shortcut, but as a capability that demands the same rigor, oversight, and strategic intent as any other enterprise technology.

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