Vibe Coding for PPC: How Marketers Are Building Custom Tools Without Writing Code

Every PPC marketer knows the feeling. You need a tool that doesn't exist-a seasonality analyzer tuned to your client's budget cycle, a search term scrubber that flags wasted spend across six accounts at once, a persona scorer that tests ad copy against ten audience segments before a dollar is spent. The options have always been the same: file a ticket with engineering, wait weeks, or cobble something together in a spreadsheet that breaks when someone adds a column. That bottleneck is dissolving. Vibe coding-a software development practice where you describe a task in natural language and an AI generates the source code-has moved from a novelty coined by Andrej Karpathy in February 2025 to a working method adopted by PPC practitioners at every level.

Frederick Vallaeys, who spent 10 years at Google building tools like Google Ads Editor and another decade as CEO of Optmyzr, is now building custom tools in minutes, not days or months, with AI. When someone with that pedigree shifts how they work, the rest of the industry should pay attention. This isn't about replacing developers or pretending that prompt-driven code is production-grade enterprise software. It's about the moment a PPC practitioner realizes they can stop waiting and start building-and what happens next.

What Vibe Coding Actually Means (And What It Doesn't)

Vibe coding refers to the practice of prompting AI tools to generate code rather than writing code manually. You describe what you want in plain language. The AI writes the code. You test the output, provide feedback, and iterate. As Karpathy originally framed it, pure vibe coding means "forgetting that the code even exists"-making it best suited for rapid ideation or what he called "throwaway weekend projects."

That distinction matters enormously for PPC. Some commentators argue that the defining characteristic is a lack of knowledge about the code itself. Programmer Simon Willison put it bluntly: if you've reviewed, tested, and understood every line, "that's not vibe coding-that's using an LLM as a typing assistant." For PPC practitioners, the practical sweet spot sits between those poles. You're building tools to solve workflow problems-not shipping SaaS products. The tools powering this shift include general-purpose LLMs like Claude and ChatGPT, plus purpose-built platforms. Replit, Lovable, Cursor, Bolt, and v0 focus on translating natural language descriptions into deployable software.

For PPC-specific data work, Claude is particularly effective for data analysis and custom calculators with CSV files, while ChatGPT's Code Interpreter excels at quick visual data analysis.

A critical nuance: vibe coding is not no-code. No-code is a spectrum stretching from drag-and-drop builders to AI-assisted development. Vibe coding sits at the far end-you focus on outcomes, not syntax. No-code tools limit you to predefined components. Vibe coding generates custom code, which gives you more flexibility but also more potential for breakage.

Why PPC Is Uniquely Ripe for This Shift

Google Ads scripts were supposed to solve this problem. Introduced in 2012, they gave marketers a way to automate tasks using JavaScript snippets that run directly inside the platform. In theory, powerful. In practice, limited adoption.

About 19% of advertisers don't use any scripts, and an additional 63% use between one and five scripts-despite Google allowing 250 scripts per account. The barriers were real: JavaScript knowledge was required, execution was capped at 30 minutes (limiting work with large accounts), and ongoing maintenance reduced their time-saving potential.

When Vallaeys asks audiences who writes their own scripts, only three to five out of 100 raise their hands. Most people copy and paste scripts because they don't know how to code. That's the gap vibe coding fills. It takes the spirit of scripts-solving real problems without waiting on engineering-and removes the technical roadblocks. Instead of code, you describe the outcome, and the AI handles the syntax.

But the opportunity goes beyond replacing scripts. Vibe coding eliminates platform constraints-you can analyze data from Google Ads, Meta, Amazon, or any CSV file. Getting ad data into the tool is still harder than analyzing it once it's there, but once you have it, vibe coding opens doors that scripts never could.

PPC is now less about individual actions and more about how well you design and oversee the systems doing the work. And that's the context in which vibe coding and scripts play a role-they're a means to guide automation, a way to add your own logic instead of relying only on what the platform gives you.

Real PPC Tools Practitioners Are Building Right Now

The most convincing argument for vibe coding isn't theoretical. It's the speed at which PPC people are building functional tools.

Audience and Creative Analysis

Vallaeys demonstrated building a persona scorer in Lovable by prompting: "Build me a persona scorer for an ad that shows how well it resonates with five different audiences." In less than 20 seconds, the AI responded with its design vision, features, and approach-and he could immediately adjust it to ten audiences instead of five. No mockups. No development sprint. Just a working tool.

Seasonality and Forecasting

Vallaeys asked someone on his team who had never coded to build a seasonality analysis tool. She fed PPC Town Hall podcast videos into Claude. The process was simple: gather resources, write a prompt, give it to AI, and test it in the browser. No installation required. The team iterated on the fly, asking for different plots and forecasting methods. In minutes, they had advanced enhancements.

Google Ads Scripts via LLMs

One PPC practitioner reports building dozens of high-performing Google Ads scripts without writing code-simply using Claude to generate them. The workflow is straightforward: describe the problem, paste it into Claude or ChatGPT, copy the generated code into Google Ads, preview and debug, and iterate until it works-usually two to three rounds.

Chrome Extensions and Utility Tools

For customer demos, Vallaeys needed to blur sensitive numbers with multiple options. He built a Chrome extension with all those options using simple prompts. Mike Rhodes, a Google Ads expert with over 20 years of experience, built 8020 Brain-a tool that simulates a council of PPC experts and lets users ask them questions -by feeding publicly available information into Claude.

Landing Pages at Scale

Kelsey Libert, co-founder of Fractl, individually built 12 landing pages in two days using Cursor. What used to take a marketing manager, copywriter, designer, developer, and weeks of production was handled in a fraction of the time by a single expert within one platform.

A Practical Workflow: From Problem to Prototype

Building a PPC tool through vibe coding follows a consistent pattern. The biggest mistake practitioners make is jumping straight to prompting without preparation.

1. Build Your Resource Library First

The first step is developing a solid resource library that the AI can learn from. Libert's setup included an HTML file of the template to replicate, image files, a CSV with agent names and functionality, a brand style guide with HEX colors, and an expert persona for writing tone. The more context you front-load, the fewer iterations you'll burn.

2. Prompt with PPC Language, Not Technical Jargon

Tell the AI your data structure ("I have a CSV with columns: Date, Clicks, Cost") and your business context ("We're B2B SaaS with Q4 budget cycles"). Clear prompts lead to clearer insights.

Use specific PPC terminology: say "seasonality tool" instead of "time series analysis." The AI makes better assumptions and may suggest approaches you hadn't considered.

3. Pick the Right Tool for the Task

Not every tool suits every job. When vibe coding in Cursor, experienced practitioners recommend o4-mini for planning and project framework, GPT-4.1 for writing new code, Claude 3.5 Sonnet for editing complex code, and Gemini 2.5 Pro as a strong all-around free option. For quick prototypes, start with Claude or ChatGPT for data analysis, calculators, and quick visualizations, then move to Lovable, V0.dev, Replit, or Bolt for apps needing databases or login systems.

4. Iterate in Conversation

Ask the AI questions: "How did you approach this?" or "Where do you store data?" Use chat mode to explore alternatives without changing the code-ask for three approaches, pick one, go deeper, then say "Execute that." Each round sharpens the output. Nils Rooijmans, a leading Google Ads scripts expert, emphasized starting small and building incrementally rather than trying to create something perfect from the start.

Where Vibe Coding Stops and Engineering Begins

This is where most vibe coding content falls short. The enthusiasm is warranted, but the guardrails matter just as much.

Security Is Not Optional

Research shows that 40–62% of AI-generated code contains security vulnerabilities, and developers sometimes spend more time debugging than they would writing code themselves.

A December 2025 analysis by CodeRabbit of 470 open-source GitHub pull requests found that AI co-authored code contained approximately 1.7 times more "major" issues-including misconfigurations 75% more common and security vulnerabilities 2.74 times higher.

For PPC tools handling campaign data, this risk is manageable but real. Hobby applications and internal enterprise tools operate under completely different risk profiles. A prototype that displays mock data has one set of constraints. An internal admin tool with access to customer databases has another. The biggest difference is production data access-when a vibe-coded app connects to real databases, the blast radius of any vulnerability expands dramatically.

The Prototype-to-Production Trap

The problem starts when a prototype becomes the production app. AI code generators optimize for functionality, not security. They produce code that works, but "works" and "works safely" are very different things.

Where teams tend to run into trouble is when an experiment quietly becomes infrastructure.

A Decision Framework

Use vibe coding for exploration, prototypes, and throwaway experiments. Use structured development for production features, security-sensitive code, and anything that needs long-term maintenance.

As Vallaeys himself noted, his vibe-coded tools are "still relatively low risk. This is not changing budgets and multi-million dollar ad campaigns." That honesty is instructive. The person most publicly championing vibe coding in PPC still draws a clear line.

The Right Mindset: Think in Tools, Not Tasks

The deeper shift here isn't technological. It's cognitive. As Vallaeys framed it at SMX Munich 2026: instead of asking how you complete a task, start asking whether you could spend thirty minutes building a tool that does it for you permanently.

Vallaeys suggests rethinking meetings entirely. Instead of seeing client meetings as more work, treat them as prompt-engineering sessions. With a mindset shift, the meeting becomes the prompt that tells AI what to execute. That reframe changes everything about how PPC teams operate.

Traditionally, marketers automated quick, frequent tasks like reviewing search terms and long, infrequent tasks like monthly reporting. Vallaeys advises not to limit automation to what you already do. Think about what you wish you could do more often but haven't because it's too time-consuming.

Consider what this means for competitive advantage. Over time, many advertisers will rely on the same algorithms, campaign types, and AI agents. When that happens, competitive advantage will depend less on tooling and more on strategy-positioning, value propositions, and the proprietary insights you encode into custom tools.

Choosing Your Entry Point

Not everyone needs to start building full web applications. The on-ramp matters. If you've never vibe coded before, start with Google Ads scripts generated through Claude or ChatGPT. You don't need to know how to code-just copy, paste, and configure. Ask an LLM to write a script that exports search terms with more than $50 in spend and zero conversions to a Google Sheet. Preview it, debug any errors by pasting them back into the AI, and iterate. If you're comfortable with prompting, move to platforms like Lovable or V0.dev to build standalone tools. In testing by G2, Lovable delivered the strongest overall result for non-developers, while ChatGPT was fastest for prototyping. Replit offered the most control, Gemini the most structured approach. Start by building something you'd actually use-a budget pacing dashboard, a competitor creative analyzer, or a quality score monitoring tool. If you want a structured learning path, dedicated courses like Vibe Coding for Marketers teach how to build landing pages, websites, dashboards, and marketing tools using AI-powered development-with no coding experience required-across 13 modules.

The sequencing matters. Start with basic data analysis and then add functionality. Build a tool that does one thing well. Expand from there. Don't try to build an all-in-one PPC command center on day one.

What This Looks Like in 12 Months

The pace of change in this space is measurable. The global AI coding assistant market is estimated at $8.5 billion by 2026 , and 84% of developers now use or plan to use AI tools, with 51% of professional developers using AI daily. These aren't developer-only numbers anymore-the fastest-growing segment is non-technical builders.

The shift is most visible in the adoption of agentic coding tools, which have turned marketing departments into hubs for "citizen developers." Technical SEOs are reducing 40-hour manual audits to 15-minute automated processes, while PPC managers are deploying self-healing bid management scripts. That trajectory points toward a near future where every PPC team has at least one person who can translate workflow problems into working software through conversation with an AI.

Matt Beswick of aira pushed this further at SMX Munich, noting that the traditional T-shaped marketer is genuinely at risk because AI closes knowledge gaps faster than people can develop them. What AI still can't do is connect marketing activity to real business outcomes, exercise judgment when data is ambiguous, or show empathy in client relationships.

That's the real takeaway. Vibe coding doesn't eliminate the need for PPC expertise. It amplifies it. The marketer who understands budget pacing, match type strategy, and creative testing at a deep level can now build tools that encode that knowledge-instantly, repeatedly, and at zero marginal cost. The marketer who only pushes buttons in the Google Ads interface is the one who should be worried. The gap between "I wish this tool existed" and "I built it this morning" has closed. What you do with that gap is now the competitive question.