The Next Wave of AI in New Zealand Marketing

Artificial intelligence is no longer a futuristic concept for New Zealand businesses; it is a present-day reality driving tangible results. Across the country, AI adoption is accelerating, with 82% of businesses reporting some level of use. The impact is clear: an overwhelming 95% of New Zealand small and medium businesses (SMBs) using AI say it boosts their revenue. Marketers are at the forefront of this shift, already using AI tools for optimising campaigns, creating content, and deploying automated service chatbots. While AI has been an effective assistant for writing and analysing, a new practice called vibe coding is emerging that allows marketers to move from using AI to building with AI.

This guide explores how NZ marketers can use vibe coding to create the custom tools, interactive landing pages, and bespoke automations that were once the exclusive domain of development teams. The timing for this evolution is ideal. AI adoption in New Zealand workplaces has largely been a grassroots movement. Research from May 2025 shows that while 44% of white-collar workers use AI tools like ChatGPT daily, only 13% have received any formal training from their employers. This indicates a workforce comfortable with experimentation and independently finding solutions. For a marketer who has mastered prompting an AI for ad copy, the next logical question is, "What if I could get it to build a tool for me?" Vibe coding answers that question, and this report provides the strategic framework to do it effectively and safely.

· We devote a full lesson to Vibe Coding in our Vital NZ Marketing Skills for 2026 online training course. Click here for more details.

2.0 What is Vibe Coding? A Plain English Guide for Marketers

To harness this new capability, it is first necessary to understand what "vibe coding" is and, just as important, what it is not. The term itself is casual, but the practice has significant implications for how marketing teams can operate.

2.1 Defining the Trend: From Andrej Karpathy to Your Workflow

The term "vibe coding" entered the lexicon in February 2025, coined by esteemed AI researcher Andrej Karpathy. He described it as a new development style where you "fully give in to the vibes, embrace exponentials, and forget that the code even exists". At its heart, vibe coding is a software development practice that uses artificial intelligence to generate functional code from natural language prompts. It is the practical application of Karpathy's 2023 observation that "the hottest new programming language is English," suggesting that large language models (LLMs) have become so capable that humans can command computers using conversational language instead of specialised code.

For a marketer, this abstract concept becomes very concrete. It means you can describe a desired outcome in plain English—for example, "build a landing page with a lead capture form" or "create an internal tool to calculate campaign ROI"—and have an AI coding assistant handle the technical implementation.

2.2 How It Works: Guiding AI to Build with Natural Language

The process of vibe coding is not a single command but an iterative, conversational loop. The marketer's role shifts from being a manual creator of code to a director or guide, focusing on the final outcome rather than the complex syntax required to achieve it. The workflow typically follows four steps, repeated until the desired result is achieved:

Describe the goal: You begin with a clear, high-level prompt in natural language. For instance, a marketer might ask, "Create a simple web form that captures a user's name and email address and saves the entry to a new row in a Google Sheet."
AI generates code: The AI tool interprets the request and produces the initial block of code required to build the form and its connection.
Execute and observe: You run the generated code to see if it works as intended. Does the form appear correctly? Does the data populate the spreadsheet?
Provide feedback and refine: If the output isn't quite right or an error occurs, you provide corrective feedback in plain English. For example, "That works, but add a confirmation message that says 'Thank you for subscribing!' after the user clicks submit."

This conversational loop continues, allowing the marketer to build and refine a functional tool without writing a single line of code by hand.

2.3 Vibe Coding vs. Vibe Marketing vs. Traditional Coding

The emergence of new AI-related terms can create confusion. It is important to distinguish vibe coding from other concepts, particularly for marketers who may encounter these terms in different contexts.

Vibe Coding vs. Traditional Coding

Traditional software development is a precise, manual process requiring deep knowledge of programming languages and syntax. Vibe coding lowers this barrier to entry, allowing those without formal coding skills to build software. The core difference lies in the input: traditional coding requires meticulously written code, while vibe coding uses natural language prompts and feedback.

Vibe Coding vs. Vibe Marketing

This is a critical distinction for any marketing professional. The two concepts are related by their use of AI but have different objectives and outputs. "Vibe marketing" refers to using AI to automate and enhance marketing campaigns—generating ad copy, defining a brand's voice, or drafting a content strategy. The output is marketing content and strategic plans. "Vibe coding," in contrast, is about using AI to build software and digital tools. The output is functional code. In short, vibe coding builds the car; vibe marketing plans the road trip.

"Pure" Vibe Coding vs. Responsible AI-Assisted Development

Karpathy's original, provocative definition of vibe coding implies a level of blind trust in the AI's output. This "pure" form is best suited for rapid prototyping or what he called "throwaway weekend projects," where speed is the only goal. However, for any business application, a more disciplined approach is required. Programmer Simon Willison clarifies this distinction: if an LLM writes all your code but you review, test, and understand it, that is not pure vibe coding but responsible AI-assisted development. This responsible model is the recommended approach for marketers.

The casual name "vibe coding" can be misleading. While the feeling of empowerment and speed is part of the "vibe," the practical application in a business setting demands a structured and methodical process to avoid creating technical problems down the line. To succeed with vibe coding, a marketer must adopt a project manager's mindset, focusing on clear goals, step-by-step instructions, and rigorous testing.

3.0 Why Vibe Coding is a Must-Know for NZ Marketers

Understanding the concept of vibe coding is one thing; appreciating its strategic importance for the New Zealand market is another. This practice offers tangible advantages that align with the current business environment and address common challenges faced by marketing teams across the country.

3.1 Beyond Automation: Gaining a Competitive Edge in the NZ Market

The conversation around AI in New Zealand has rightly focused on productivity. With 93% of NZ businesses reporting that AI makes workers more efficient, the benefits are well-established. Vibe coding represents the next stage of this efficiency gain. It allows marketing teams to move beyond simply automating existing tasks and start building new solutions.

One of the most common frustrations for marketers is the "dev queue" bottleneck, where great ideas for new tools or landing pages are stalled waiting for developer availability. Vibe coding empowers marketers to bypass this queue for smaller projects, enabling a culture of rapid experimentation that is central to modern growth marketing. This is particularly relevant for New Zealand's SMBs, many of whom report that keeping pace with changing technology is a challenge. By using vibe coding, smaller, more agile marketing teams can create custom solutions and compete with larger organisations without needing a significant development budget.

3.2 The Core Benefits: Speed, Agility, and Independence

For a marketing workflow, vibe coding delivers three transformative benefits:

Speed: Development timelines can be dramatically reduced, from weeks or months to days or even hours. For instance, one marketer reported using an AI tool to build a functional browser extension in about three minutes, a task that would have previously been a multi-day project. This speed allows teams to react to market opportunities much faster.
Agility: The ability to quickly build and test prototypes for new ideas is a significant advantage. A marketer can vibe code a new landing page design, an interactive quiz, or a campaign-specific microsite to test its viability with a live audience before committing major resources. This supports a "test and learn" culture and reduces the risk associated with new marketing initiatives.
Independence: Perhaps the most empowering benefit is the independence it grants to marketers. Anyone on a marketing team who has ever said, "I wish I had a tool that just did X," now has a direct path to creating it. This reduces reliance on over-stretched engineering departments and gives marketers greater ownership and control over the tools they need to succeed.

This newfound capability can also help address a specific challenge within New Zealand businesses. While AI adoption is high, 50% of NZ SMB employees state they lack the time to master all the different technologies their company uses. This points to a "productivity paradox" where the sheer number of complex tools creates its own friction. Because vibe coding's primary interface is natural language—a skill everyone already possesses—it lowers the barrier to creating solutions. Instead of forcing a marketer to learn yet another complex software platform, it allows them to simply describe the problem they want to solve. In this way, vibe coding is not just another tool to learn; it is a way to build simpler, bespoke tools that can reduce the overall cognitive load and solve the problem of tool fatigue.

4.0 Vibe Coding in Action: Real World Examples for Marketing Teams

The potential of vibe coding becomes clearest when looking at concrete examples of what marketers and other non-developers are already building. These projects, which range from lead magnets to internal automations, demonstrate how natural language prompts can be translated into valuable marketing assets.

4.1 Example: Building a Custom Lead Magnet (e.g., an SEO Calculator)

Project: An interactive SEO calculator designed to function as a high-value lead magnet. The tool answers a prospect's questions, provides immediate value, and captures their details for the marketing funnel.
Tool Used: Cursor.
Process: This real-world example comes from Tim Metz, the Director of Marketing at Animalz. He used Cursor to build the tool. A marketer could replicate this by first defining the calculation logic (e.g., input keywords, search volume, and difficulty to estimate potential traffic). Then, they would prompt the AI to build the user interface with input fields for the data and a display area for the results. A final prompt would add a lead capture form that appears before the results are shown, effectively turning a helpful utility into a lead generation machine.

4.2 Example: Automating Repetitive Workflows (e.g., a PR Pitch Assistant)

Project: An AI agent that automates the time-consuming task of responding to journalist requests for expert quotes, a common tactic for earning media mentions and backlinks.
Tool Used: Zapier Agents.
Process: This workflow can be built with natural language instructions. The marketer would define a trigger, such as a new email arriving in a specific folder from a media request service. The AI agent is then instructed to read the email, understand the journalist's query, and search a knowledge base of the company's existing blog posts and articles to find relevant information. The agent then drafts a pitch based on this content and posts it to a dedicated Slack channel for the marketing team to review, edit, and send.

4.3 Example: Creating an Interactive Landing Page for a Community

Project: A simple, on-brand landing page with an email subscription form to launch a new community, such as a Slack or Discord group.
Tool Used: Lovable.
Process: To build this, a marketer can provide the AI tool with their brand's style guide—including colours, fonts, and logo usage. They then use prompts to describe the page structure: "Create a landing page with a hero section, a short paragraph explaining the community, and an email sign-up form." This approach allows for rapid creation of campaign assets and helps overcome the "decision paralysis" that can slow down design projects.

4.4 Example: Prototyping a Simple Internal Tool (e.g., a SOW Generator)

Project: An embeddable Statement of Work (SOW) generator to standardise and simplify a tedious administrative task for the marketing or sales team.
Tool Used: v0 by Vercel.
Process: A marketing manager could take an existing SOW template or an internal document outlining the required components and feed it to the AI. They would then prompt the tool to turn that logic into an interactive form. For example: "Create a tool with fields for client name, project scope, timeline, and deliverables. Include a button that generates a formatted SOW document based on the inputs." This creates a low-risk, high-impact tool that improves internal efficiency.

4.5 Example: Developing a Writing Assistant Chrome Extension

Project: A custom Chrome browser extension that acts as a writing assistant, providing suggestions based on a company's unique style guide and tone of voice.
Tool Used: Bolt.
Process: A content marketing manager could use a tool like Bolt to codify their team's writing rules into a functional extension. They could prompt the AI with instructions like, "Build a Chrome extension that, when activated, checks selected text for our list of forbidden words and suggests alternatives from our brand voice guide." This turns individual expertise into a scalable asset that can be used by the entire team directly within their writing environment, such as Google Docs or a CMS.

4.6 Example: Building a Suite of AI Tools to help marketers

We wouldn't want you to think that all we're doing is writing about this stuff. We've also been using vibe coding to develop a suite of AI tools to help Kiwi marketers, with our Marketing Accelerator project.

Project: What is the Marketing Accelerator project? A suite of AI software programs designed to help NZ businesses market their operations more effectively:

Identify your target customers through Ideal Customer Profiles (ICPs) and their pain points
Develop insights about how your products or services can help with those pain points
Create monthly content calendars customized for your products/services and your ICPs
Identify the best-ranking related keywords
Brainstorm content ideas based around those pain points and insights
Write SEO/AEO-optimised rich, long-form articles based on your best content ideas
Write compelling social posts & create images that will make your prospects stop scrolling
Slice and dice your content to share across our Accelerator Network and elsewhere
Create lead magnets such as ebooks, presentations and videos based on your content

Check out the details, and add yourself to the waitlist, by clicking here.

5.0 Your Vibe Coding Toolkit: The Best AI Tools for Marketers

Getting started with vibe coding requires choosing the right tool for the job. The ecosystem is expanding quickly, but a few key platforms have emerged as favourites among marketers and non-developers. The "best" tool is context-dependent; a marketer's needs are diverse, ranging from a quick script one day to a full user interface the next. The most effective approach is to think of these platforms as a portfolio of specialised tools, each suited for a different type of project.

The following table provides a breakdown of the leading vibe coding tools, helping NZ marketers match their goals to the right platform.

Tool	Best For...	Key Features for Marketers	Learning Curve
Cursor	The Power Editor	Building more complex projects like lead magnets or internal tools where more control is desired.	AI chat within the code editor, understands context across multiple files, allows switching between AI models (e.g., GPT-4, Claude) for different tasks.
Replit	The All-in-One Playground	Building and hosting simple web apps or scripts entirely in a web browser, with no local setup needed.	Fully browser-based environment, includes an AI pair programmer, offers one-click deployment and hosting for finished projects.
Lovable / v0 by Vercel	The UI Specialists	Quickly creating visual front-ends, interactive landing pages, and embeddable widgets for a website.	Purely prompt-to-UI workflow, excellent for visual prototyping and turning ideas into interactive components without touching backend code.
Bolt	The Speed Builder	Generating full-stack code for campaign-specific microsites or landing pages in seconds.	Pure prompt-to-code generation, designed for maximum speed to get a project from idea to live application as quickly as possible.
Zapier Agents / Gumloop	The Automators	Creating AI-powered workflows that connect different applications and automate multi-step marketing tasks.	Uses natural language instructions to build agents, connects to thousands of third-party apps (e.g., Slack, Google Sheets, CRMs).

6.0 How to Start Vibe Coding: A Practical Workflow for Your First Project

Embarking on your first vibe coding project can feel intimidating, but a structured approach can demystify the process and set you up for success. By blending best practices from various expert guides, the following workflow provides a clear, step-by-step path from idea to a finished product.

Step 1: Identify a High-Impact, Low-Risk Problem

The key to a successful first project is to start small. Instead of attempting to build a complex, mission-critical application, choose a simple problem where a solution would provide genuine value. Good candidates for a first project include:

Automating a repetitive task: Think about manual processes that consume time each week, like compiling a report, researching social media content, or generating UTM tracking links for campaigns.
Building a simple internal tool: A basic calculator, a checklist generator, or a simple dashboard that pulls data from a Google Sheet can be a great starting point.

By selecting a low-risk project, you give yourself room to experiment and learn the process without the pressure of a high-stakes deployment.

Step 2: Choose Your Tool and Prepare Your Resources

Refer back to the toolkit in the previous section to select the platform that best matches your project's goal. Once you have chosen your tool, the next critical step is to prepare your resources. Do not underestimate the importance of creating a "robust training library" for the AI. A well-prepared set of inputs is essential for getting a high-quality, on-brand output. This library should include:

Brand assets: Your brand style guide, including HEX codes for colours, font names, and logo files.
Example content: Samples of existing copy that reflect your desired tone of voice.
Templates: Any existing HTML or document templates you want the AI to replicate.
Clear file organisation: Use logical names for your files and folders, as the AI uses this structure to understand context.

Step 3: Prompting in Steps: How to Guide the AI Effectively

Avoid the temptation to write a single, massive prompt asking the AI to build the entire project at once. This approach often leads to confusion and poor results. Instead, break the project down into a checklist of small, sequential tasks.

For example, instead of a vague prompt like "Build me a website," use a series of specific instructions:

"Using the provided style guide, create a single-page HTML file with a responsive layout."
"In that file, add a hero section with the H1 'Welcome to our community' and the body copy from copy.txt."
"Below the hero section, add a three-column feature grid. Use the icons and text provided in features.csv."

It is also important to set clear boundaries to prevent the AI from making unrequested changes. Use phrases like, "Do not go outside the scope of what I'm asking for," with your prompts to keep the AI focused on the specific task at hand.

Step 4: The Iterative Loop: Testing, Debugging, and Refining

Vibe coding embraces a "code first, refine later" mindset. After each step, run the code generated by the AI and observe the result. When something inevitably breaks or does not work as expected, that is part of the process.

Debugging with AI: Copy the full error message and paste it back into the chat with the AI, along with a prompt like, "I ran the code and got this error. Please fix it". The AI can often diagnose and correct its own mistakes.
Reviewing Changes: Before accepting and committing any changes from the AI, review them carefully. Most tools will highlight new code in green and deleted code in red. Be particularly wary of large deletions, and ask the AI to justify why the removal is necessary.
Using Checkpoints: Get into the habit of saving stable versions of your project. Many tools have a "checkpoint" or version control feature that allows you to roll back to a previously working state if a new change breaks everything.

7.0 The "Vibe Check": Challenges and Risks NZ Marketers Must Consider

While the potential of vibe coding is significant, it is accompanied by real-world risks. A purely "vibe"-driven approach without discipline can create more problems than it solves. Understanding these challenges is essential for using the technology responsibly and protecting your business from common pitfalls.

7.1 The Scalability Trap: When a Quick Fix Becomes a Long-Term Problem

One of the most significant risks is the scalability trap. A tool that is vibe-coded to solve an immediate, specific problem often lacks the robust architecture needed to scale with a growing business. These tools are frequently described as a "Notion/Retool/Zapier Frankenstein"—a clever assembly of parts that works for one person but becomes a maintenance nightmare when handed off to a larger team.

These quick-fix tools were not built to handle new features, increased user traffic, or evolving business requirements. When the marketing team's needs change, the vibe-coded tool may be unable to adapt, and the original builder may have moved on to other projects, leaving a poorly documented and fragile system behind.

7.2 Common mistakes and avoidance strategies

The 70% completion trap affects most beginners - basic functionality works perfectly, but polishing proves increasingly difficult. Combat this by planning iterative releases rather than pursuing perfection initially. Deploy minimum viable versions, gather user feedback, then enhance based on actual usage patterns.

Scope creep in prompts represents another frequent pitfall. Asking for complete applications in single prompts typically produces poor results. Instead, use vertical slice methodology - build individual features completely before adding complexity.

For example, start with user registration, then add login functionality, then profile management. This approach ensures each component works properly before integration challenges emerge.

Context window overload occurs when feeding too much information to AI systems simultaneously. Start fresh conversations for new features and maintain separate discussions for different project components. This prevents confusion and improves response quality.

7.3 Security, Quality, and Compliance: The Need for Human Oversight

Relying solely on AI-generated code for any application that handles sensitive data or is public-facing carries substantial risks:

Security Vulnerabilities: AI-generated code can contain hidden security flaws that may not be apparent on the surface. Without a thorough review by a human expert, these vulnerabilities could be exploited, creating significant risks.
Code Quality and Performance: While the code may be functional, it might not be efficient or performant. This can lead to slow-loading pages or tools that break under pressure, resulting in a poor user experience.
License Compliance: LLMs are trained on vast amounts of data from the internet, including open-source code. An AI tool might incorporate a code snippet that is subject to a restrictive open-source license without declaring its origin. This could expose an organisation to legal and compliance issues.

For these reasons, the "responsible AI-assisted development" model is paramount. For any project that goes beyond a personal utility or a disposable prototype, the code must be vetted by an experienced human developer.

7.4 The Solution: Adopting a "Build With, Not For" Mindset

To mitigate these risks, marketers should adopt a collaborative and strategic approach to building internal tools. As consultant Naomi West advises, the mantra should be to "build with, not for". If an internal tool is necessary, the process should involve pairing the builder with the end-users (the marketing team) from the start. The project must include thorough documentation and a clear plan for ongoing maintenance and support.

An even better approach for marketers is to use vibe coding not to build the final product, but to create a high-fidelity, functional prototype. This prototype can then be presented to the professional development team to show them exactly what is needed. This process removes ambiguity from requirement documents, clarifies the vision, and accelerates the professional development cycle. In this model, the developer's role shifts from a "wizard with secret knowledge" to a "shepherd" who can guide the marketer's well-defined prototype into a secure, scalable, and production-ready application.

8.0 The Future of Marketing in New Zealand: Connecting Vibe Coding to Broader Trends

Vibe coding does not exist in a vacuum. It is a capability that directly supports and accelerates several key digital marketing trends taking shape in New Zealand for 2025 and beyond. By understanding these connections, marketers can use vibe coding not just as a novelty but as a strategic enabler for their future marketing efforts.

8.1 Fuelling Your Answer Engine Optimisation (AEO) Strategy

A significant shift is occurring in the world of search, moving from traditional Search Engine Optimisation (SEO) to Answer Engine Optimisation (AEO). This trend, identified by NZ digital agencies, involves optimising content to directly answer questions for AI-powered search engines like Google's AI Overviews and conversational assistants like ChatGPT.

Vibe coding is a powerful tool for an AEO strategy. While a blog post can answer a question, an interactive tool can provide a much richer and more valuable experience. Marketers can use vibe coding to quickly build custom calculators, quizzes, data visualisers, or configuration tools that directly answer a user's query. These interactive content pieces are highly valuable for AEO, as they are more likely to be featured and referenced by AI search results, driving high-intent traffic.

8.2 Aligning with today’s NZ Digital Marketing Landscape

Vibe coding also aligns perfectly with several other dominant trends in the New Zealand digital marketing landscape:

Hyper-Personalisation at Scale: Delivering tailored content and experiences is a top priority for 2025. Vibe coding allows marketers to create bespoke landing pages, personalised recommendation tools, or custom-generated reports for different audience segments without requiring a massive engineering effort.
The Creator Economy: As influencer marketing evolves towards more authentic, long-term partnerships, brands are looking for new ways to collaborate. A marketer could use vibe coding to build a simple, unique tool or microsite as part of a creator campaign, providing something of tangible value for the creator's audience to engage with beyond a simple discount code.
The Need for First-Party Data: With the phase-out of third-party cookies, building direct relationships and collecting first-party data is essential for effective marketing. Vibe coding enables the rapid creation of compelling lead magnets—like the calculators and quizzes mentioned above—that serve as an excellent mechanism for a value exchange, where users provide their data in return for a useful and interactive experience.

9.0 Conclusion: Your Next Move in AI-Powered Marketing

Vibe coding represents a genuine shift in capability for New Zealand marketers. It moves them from being passive users of AI tools to active builders of their own solutions. This practice offers the power to accelerate campaigns, automate workflows, and bring new ideas to life with unprecedented speed. It empowers marketing teams to become more independent, agile, and experimental.

However, this power must be wielded with discipline. The most effective path forward is not to replace professional developers but to augment their work. For marketers, the sweet spot for vibe coding lies in building prototypes to clarify vision, creating internal tools to boost efficiency, and launching low-risk campaign assets to test new ideas. For anything business-critical, a structured, collaborative approach that includes human oversight is not just recommended; it is required.

The journey into vibe coding begins with a single step. The best way to start is to identify one small, repetitive task in your daily workflow that causes friction. Then, using the guidance and tools outlined in this report, try to build a simple solution. This hands-on experience will be the most valuable teacher, opening the door to a new and more powerful way of marketing.

Frequently Asked Questions (FAQ)

Q: What is the difference between vibe coding and vibe marketing?

A: Vibe coding uses AI to build software like apps and tools from natural language prompts. Vibe marketing uses AI to create marketing campaigns, content, and strategy. Think of it as building the car (vibe coding) versus planning the road trip (vibe marketing).

Q: Do I need coding knowledge to start vibe coding?

A: No, you don't need to know how to write code to get started. The core idea is to use plain English to describe what you want. However, a basic understanding of how web applications work can be helpful for debugging and refining the AI's output.

Q: Is vibe coding safe for business-critical applications?

A: It is not recommended for mission-critical applications without rigorous review by an experienced human developer. For such projects, it's best used for creating a prototype. The risks of security flaws, scalability issues, and poor performance are too high for un-vetted, AI-generated code in a production environment.

Q: How much do vibe coding tools typically cost?

A: Costs vary. Many tools like Replit, Cursor, and Lovable offer a free tier with limitations, which is perfect for getting started. Paid plans for more advanced features or higher usage typically range from $10 to $50 USD per month, with enterprise plans being more expensive.

Q: Can I use vibe coding to build a full mobile app?

A: While you can prototype the functionality and user interface of a mobile app, building a native, production-ready mobile app for the App Store or Google Play is still a complex task that typically requires professional development tools and expertise. Vibe coding is currently best suited for web applications, internal tools, and automations.