Vibe Coding Is Here to Stay: A Leaders’ Guide to Secure AI Development

In this article, we'll explore why 'Vibe coding or vibing' - thats when developers orchestrate AI coding agents with natural language; is transforming software development, examine what Gartner says about this trend and show you a practical approach to adopting this practice to enhance productivity while integrating security into the process. We'll also step through a secure Vibe coding demonstration using Anthropic's Claude Code assistant and provide actionable guidance for leaders to enable their teams to adopt this technology safely.

Vibe coding is here to stay, whether we like it or not. Microsoft, Google and Meta have have publicly stated that 25 - 50% of their new code is targeted or already being written by AI assistants. Meanwhile, Gartner predicts By 2028 40% of new enterprise production software will be created with Vibe coding techniques and tools.¹. This isn't a distant future scenario - it's happening in development teams across the globe right now.

Yet many business leaders find themselves caught between the undeniable productivity gains from AI-assisted coding and legitimate security concerns about letting AI write business-critical code.

The common response is to either ban it entirely or ignore it due to lack of knowledge about the impact on business risk and productivity. Unfortunately, both approaches can prove counterproductive. Ban it and developers will find ways to use these tools regardless of policy, often through shadow IT that creates even greater security risks. Ignore it and your team may not harness the power of AI-assisted coding that could give your business the competitive edge and dramatically improve speed to market.

The question isn’t if your team will adopt AI coding - it’s whether you will enable them to do it securely, without turning your business into a target.

Vibe Coding or Vibing - What and How?

Vibe coding represents a fundamental shift in how software gets built. Rather than developers writing code line by line, they interact with AI assistants through natural language, describing what they want to build and letting the AI generate the implementation - Demo coming up below.

The developer's role changes from "doer" to "orchestrator" - they provide direction, review outputs, and make strategic decisions whilst the AI handles much of the actual code writing. This can range from generating small functions to building entire features or applications.

Tools like Cursor, GitHub Copilot, Claude Code, and ChatGPT have made this approach accessible to any developer with an internet connection. The barrier to entry is now essentially zero, which explains why adoption has been so rapid.

The Security Dilemma

The security concerns about AI-generated code aren't theoretical. When AI systems pull patterns from public repositories to generate code, they can inadvertently reproduce security vulnerabilities or even malicious code that was deliberately planted in open source projects.

This risk is amplified by the fact that AI-generated code often appears professional and functions as intended, making security vulnerabilities harder to detect during review. Traditional code review processes are geared towards identifying quality issues and vulnerabilities in human-written code, rather than spotting security flaws unique to AI-generated code or those targeting AI agents.

The Solution: Secure by Design, Not Blocked by Default

Rather than banning Vibe coding, forward-thinking leaders are integrating security directly into the AI-assisted development workflows. This approach recognises that the technology offers genuine competitive advantages while addressing legitimate security concerns through process and tooling.

The key insight is that security scanning and validation can be automated as effectively as code generation. While human-written code relies on established engineering practices, Vibe coding workflows can adopt proven security hygiene to ensure AI-generated code remains free from risk factors and supports teams in embracing this innovative approach to software development.

Here's an example of what secure Vibe coding process could look like in practice:

1. AI-Assisted Code Generation

Developers interact with AI assistants through voice or natural language prompts to generate code. The AI creates functions, scripts, or entire features based on the requirements provided.

2. Automated Security Scanning

Before any AI-generated code moves forward, it undergoes automated or user-triggered security scanning using relevant code scanning tools like:

Static Application Security Testing (SAST) to identify code quality issues and vulnerabilities
Secret detection to catch hardcoded credentials or API keys
Configuration analysis to identify potential misconfigurations
Software Composition Analysis (SCA) to check for vulnerable third-party and open source components, generating a Software Bill of Materials (SBOM) that acts as an inventory of all direct and indirect dependencies included by your AI assistants that becomes a part of your application - this is critical.
LLM Top 10 risk scanning if building AI (LLM powered) applications

3. Human Oversight and Approval

Critical to this approach is maintaining human oversight. Rather than fully automating the process, developers review and approve each step, ensuring they understand what the AI is doing and can catch issues that automated tools might miss.

4. Integration with Existing Workflows

The security-enhanced code then integrates with standard development practices - version control, code review, and deployment pipelines. This ensures security becomes part of the development workflow rather than a separate, burdensome process.

Real-World Impact

This approach isn't theoretical as development teams are already implementing secure Vibe coding workflows successfully. The urgency becomes even clearer when we consider recent AI security incidents. In the first half of 2025 alone, there have been numerous documented security breaches on production AI systems leading to financial and reputational damage to some of the top organisations.

Given the widespread adoption of AI-assisted coding across the industry, it's highly likely that many of these compromised systems contained code written by AI assistants. This reality makes securing AI-generated code not just a best practice, but a business imperative.

The good news is that proven security practices can be effectively extended to cover code written by AI assistants.

📌 Watch this demo of secure Vibe coding flow in action, from AI generated code with embedded security hygiene to seamless CI/CD integration.

The video demonstration showcases a practical implementation using key tools that work together to establish a secure Vibe coding environment. By leveraging popular open source security scanners, it illustrates how security practices can be seamlessly integrated into AI-assisted development workflows, enhancing developer productivity without compromising safety.

Tools featured in this demonstration:

Claude Code - Anthropic's terminal-based coding assistant as our Vibe Coding AI assistant
Trivy Scanner - Open source vulnerability scanner from Aqua Security for comprehensive security analysis
Semgrep - Static analysis tool for identifying security vulnerabilities and code quality issues
GitHub - Version control and collaborative development platform
Terminus - Terminal environment for secure remote development access
Cursor [Optional] - AI-powered integrated development environment (IDE)

Positive Impact of Secure Vibe Coding

When implemented properly, secure Vibe coding delivers significant business advantages:

✅️ Faster Time to Market: Teams can prototype and iterate rapidly, testing ideas with customers sooner and adapting based on feedback. This is particularly valuable for proof of concept development and market validation.

✅️ Improved Code Quality: Automated security scanning catches issues that manual reviews often miss, resulting in more secure and reliable code than traditional development processes.

✅️ Developer Satisfaction: Rather than feeling constrained by security requirements, developers appreciate having security built into their workflow. It removes friction rather than creating it.

✅️ Competitive Advantage: Organisations that master secure AI-assisted development can deliver features faster than competitors whilst maintaining higher security standards.

✅️ Risk Reduction: By building security into the AI coding process from the start, organisations avoid the common pattern of retrofitting security controls after vulnerabilities are discovered.

What Leaders Must Do Now

Understanding the benefits is one thing. Taking action is another. As AI-assisted development continues to mature, leaders must take a strategic approach to capitalise on the opportunity. This requires moving early with a focus on:

➜️ Start with Pilot Projects: Begin with low-risk projects to build confidence and refine processes before expanding to business-critical systems.

➜️ Invest in Tooling: The cost of security scanning tools is minimal compared to the productivity gains from AI-assisted coding, especially when considering the cost of security incidents.

➜ Train Your Teams: Developers need to understand both the capabilities and limitations of AI coding assistants. Security teams need to understand how to adapt existing practices for AI-generated code.

➜️ Establish Clear Policies: Define what types of projects are appropriate for Vibe coding, what security standards must be met, and how human oversight should be maintained.

➜ Monitor and Iterate: Track both productivity gains and security metrics to continuously improve your approach.

The key is recognising that this technology represents a fundamental shift in how software gets built. Organisations that adapt their security practices accordingly will gain competitive advantages, whilst those that simply ban the technology will find themselves falling behind competitors who've learned to use it safely.

The Bottom Line

Vibe coding isn't going away. The productivity gains are substantial, and the technology is so easily accessible that organisations cannot afford to ignore it.

Business leaders and development teams face a pivotal decision:

Embrace Vibe coding securely from the start and harness the productivity gains
Or scramble to add security controls after incidents force your hand

The good news? You don't have to choose between velocity and security. Organisations that integrate security scanning directly into their Vibe coding workflows maintain rapid development cycles whilst exceeding traditional security standards.

The organisations that master secure Vibe coding today will dominate tomorrow. The time to start is now, while you can learn and iterate with minimal competitive pressure.

Need help implementing secure AI development practices in your organisation?

💡 Book a FREE 30-minute consultation with me to discuss how to safely adopt AI-assisted coding whilst maintaining security standards that protect your business and customers.

References

Gartner Report: Hype Cycle for Software Engineering, 2024 | Gartner (courtesy of Semgrep)
Top 5 AI System Breaches for 2025 to date & Lessons learnt | Honestlabs
Claude Code Documentation | Anthropic
Trivy - Open Source Vulnerability Scanner | Aqua Security
Semgrep - Static Analysis for Security | Semgrep
Cursor - The AI-first Code Editor | Cursor