Vibe coding accelerates digital transformation for enterprises. Terms and conditions apply.

This is possible through powerful advancements in Generative AI (GenAI), the underlying Large Language Models (LLMs) and code assistants built on them. Rather than using AI assistants like Copilot to write actual code, developers now use natural written or spoken language to request desired outcomes from the AI tool. They direct AI coding tools on how an application should look, feel and act based on their current intuition, mood or vibe.

It’s an evolution of low-code to no-code software development.

Adapting vibe coding to business needs

AI is accelerating digital transformation for enterprises. It helps to make business processes more efficient, distills relevant knowledge from vast amounts of data and assists content creators in marketing and communications. AI is also enabling better digital experiences for customers through intelligent chatbots and faster service. Software is a key enabler for innovation and transformation, and with vibe coding, its development just gets faster.

Not surprisingly, according to the Wall Street Journal, “Gartner predicts that 40% of new software for businesses will be created with techniques involving AI bots translating plain English prompts into usable code.”

Enterprise-ready yet or just a flash in the pan?

No doubt, vibe coding is a very fast, efficient and easy way to create new apps, capabilities or websites, especially when a developer, team or business starts from scratch with zero lines of code, like a startup.

But enterprises need to make sure their products, services and experiences scale to thousands, even millions of users right out of the gate. They need to make sure their apps and complex processes are secure, unbiased and accessible for all users. Despite shortening product life cycles and faster go to market, they build for longevity, not to move fast and break things. After all reputation, brand equity and existing businesses are on the line.

With that in mind, unchecked deployment of vibe code would accrue huge amounts of technical debt for enterprises. It’s bad news for large code bases. Very soon, developers would spend the time they save with vibe coding on vibe debugging. Enterprises need to have the right culture, skills, frameworks, processes and technologies in place to reduce and prevent risks associated with vibe coding.

The agile culture prerequisite

Over the past two decades, leading-edge businesses have been using various techniques, frameworks and processes to become increasingly responsive to change and accelerate their processes in highly competitive markets. Vibe coding is driving the next phase of this cultural and organizational transformation.

For example, agile culture values responding to change over following a plan. Vibe coding compresses those response times. Scrum promotes inspection and adaption. Vibe coding enables quick prototyping and feedback cycles. Lean managers rely on the principles of build, measure, learn. All this becomes easier and faster with vibe coding. But this also means if your processes and structures are not agile, vibe coding might not be a good fit and may fail to deliver useful results.

Define. Develop. Deploy.

So what are some of the skills required to pull this off?

Developers need to concentrate on precisely defining and breaking down complex problems into smaller, manageable tasks that AI can understand and handle. This demands strong abilities in problem analysis and crafting prompts that effectively steer AI tools to produce relevant and practical code. Integration plays a crucial role, as developers must merge AI-generated code snippets into unified, fully functioning systems while maintaining compatibility and performance.

In essence, vibe coding shifts the focus from traditional coding skills to higher-level thinking, system design, and seamless integration.

Vibe coding has the potential to make software development better, cheaper and faster. But enterprises must have the right processes, frameworks and skills in place to ensure quality, security and scalability.

Driving IT security

Vibe coded applications often skip standard IT processes, risk assessments, and secure deployment pipelines, resulting in hidden and unmanaged attack surfaces that security teams struggle to identify or mitigate. This creates significant security risks as GenAI-produced code relies on learned patterns rather than context-sensitive security practices.

Vibe coding, without human oversight and thorough code review, produces fragile, unclear, or hard-to-maintain code, leading to compliance issues, operational instability, and risks of supply chain attacks from AI-generated malicious packages, known as “slopsquatting”.

Slopsquatting is the act of registering fake software package names that an LLM might hallucinate in its output. Unsuspecting users may copy-paste and install these malicious packages, thinking they are legitimate. This creates risks of attacks and operational instability.

Robust testing processes. Reinforced security measures.

We also recommend incorporating automated security testing tools into the continuous integration pipeline.

• Static Application Security Testing (SAST) tools analyze LLM-generated code without execution to identify vulnerabilities early but may miss runtime issues.
• Dynamic Application Security Testing (DAST) tools test running applications to detect security flaws visible only during execution, such as input handling and authentication problems.
• Combining SAST and DAST provides a layered security approach, addressing both static code flaws and dynamic vulnerabilities in LLM-generated outputs.

However, it is important to conduct regular vulnerability scans, penetration tests, and compliance checks to ensure AI-generated code adheres to secure coding standards.

Agentic AI: Accelerating adoption of autonomous agents

In this volatile environment, Agentic AI plays an increasingly important role. With Agentic AI, businesses can create autonomous systems of agents to automate the software engineering and IT processes. Platforms like Atos Polaris AI provide agentic backends that autonomously execute, test and iterate solutions for integrated, complex code bases. This would be an increasingly overwhelming task with manual processes, even without vibe coding in the mix.

Transforming the future with a vibe

Vibe coding can definitely accelerate a business’ digital transformation and new product creation, particularly when it is used to build quick prototypes and MVP versions at the beginning of software development cycles. Business users will have to watch and test how vibe coding tools and the underlying AI models evolve and improve over time. With future iterations, vibe coding might be useful beyond the early stages of software and digital innovation and may create code that is almost production-ready.

For enterprise-grade vibe coding, businesses need to have the right frameworks and tools in place to ensure security, quality, scalability and responsibility of their final products and services. The combination of vibe coding, Agentic AI and the right frameworks and policies ensures code quality, builds trust with users and stakeholders and showcases ROI.

Good, cheap, fast? It remains a tricky balance, but with vibe coding it may just become a bit better, cheaper and faster.

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