CrushPress.AI

Tag: Vibe Coding

  • How I Use Vibe Coding to Build Practical SEO Tools

    How I Use Vibe Coding to Build Practical SEO Tools

    Vibe coding for SEO

    I see vibe coding as one of the most accessible ways to create small pieces of software with AI tools like ChatGPT, Cursor, Replit, and Gemini. Instead of writing code line by line, I describe what I want in plain language, receive working code in return, paste it into an environment like Google Colab, run it, and test the result.

    Collins Dictionary named “vibe coding” word of the year in 2025, defining it as “the use of artificial intelligence prompted by natural language to write computer code.”

    In this guide, I’ll explain how I approach vibe coding, where I think it works well, where it breaks down, and which SEO examples can inspire practical projects of your own.

    Vibe coding variations

    I use “vibe coding” as a broad term, but it helps to separate it from nearby approaches:

    TypeDescriptionTools
    AI-assisted codingAI helps write, refactor, explain, or debug code. I usually associate this with developers or engineers who already understand the systems they are building.GitHub Copilot, Cursor, Claude, Google AI Studio
    Vibe codingAI handles most of the work after I provide the idea or prompt.ChatGPT, Replit, Gemini, Google AI Studio
    No-code platformsPlatforms handle what I ask for through visual interfaces, drag-and-drop workflows, or background automation. Many now use AI, but they existed before AI became mainstream.Notion, Zapier, Wix

    For this guide, I’m focusing only on vibe coding.

    The barrier to entry is low. In most cases, I only need a ChatGPT account, free or paid, and access to a Google account. Depending on the project, I may also need API access or subscriptions to SEO tools such as Semrush or Screaming Frog.

    ```json { "alt": "The CapmatchOne logo with a gradient circle and bold text.", "caption": "Discover innovation with the CapmatchOne logo, featuring sleek typography and a modern gradient circle.", "description": "The CapmatchOne logo features bold, modern typography coupled with a gradient circle, symbolizing connection and innovation. The sleek design conveys a sense of progress and creativity. This image can be used for branding or promotional purposes, appealing to audiences interested in innovative solutions and forward-thinking designs." } ```

    I also like to set expectations early: by the end of this kind of workflow, I’m usually aiming to run a small program in the cloud. If I want to build a SaaS product or software I plan to sell, I treat AI-assisted coding as the more realistic path because it usually requires more technical knowledge, more testing, and more budget.

    Vibe coding use cases

    I find vibe coding most useful when I’m working with clear buckets of data and need a helpful outcome, not a perfect one. That might mean finding related internal links, adding pre-selected tags to articles, comparing groups of URLs, or building something playful where the output does not need to be exact.

    For example, I built an app that creates a daily drawing for my daughter. I type a short phrase about something she told me, such as “I had carrot cake at daycare.” The app uses examples of drawing styles I like and a few pictures of her, then generates a drawing as the final output.

    When I ask for precise changes, the tool often gets worse. I once asked it to remove a mustache, and instead it recolored the image. That is exactly the kind of limitation I expect with this approach.

    If my daughter were a client reviewing every detail, I would need someone with Photoshop or similar skills to make exact edits. For this use case, though, the result is good enough, and that is where vibe coding shines.

    ```json { "alt": "Two cartoon characters eating spaghetti at a table with forks.", "caption": "Two cheerful cartoon characters enjoy a classic spaghetti meal, each showcasing a different artistic style.", "description": "This split image features two cartoon characters sitting at a table, each enjoying a plate of spaghetti with a fork. The character on the left is depicted in a clean, outlined style with minimal shading, while the character on the right is drawn with more detail and shading, giving a sense of depth and realism. Their expressions are joyful, as they savor the spaghetti. The image highlights two contrasting artistic techniques in cartoon illustration, making it a visually intriguing piece ideal for discussions about art styles and graphic design." } ```
    Daily drawing example created with AI

    I would be cautious about building commercial applications solely through vibe coding. Some companies may even need vibe coding cleaners to clean up AI-generated work. But for demos, MVPs, internal tools, and quick experiments, I see vibe coding as a useful shortcut.

    How I create SEO tools with vibe coding

    When I create an SEO tool with vibe coding, I usually follow three steps:

    1. I write a prompt describing the code I need.
    2. I paste the code into a tool such as Google Colab.
    3. I run the code and check whether the results match what I expected.

    Here’s a real prompt example from a tool I built to map related links at scale. After crawling a website with Screaming Frog and extracting vector embeddings through the crawler’s OpenAI integration, I vibe coded a tool to compare topical distance between the vectors for each URL.

    This is exactly what I wrote in ChatGPT:

    I need a Google Colab code that will use OpenAI to:

    ```json { "alt": "Google Colab code snippet for HREFLANG matcher using Python and CSV.", "caption": "Dive into HREFLANG matching with this Google Colab Python script, designed to automate CSV uploads and find similar pairs. A tool for seamless data processing.", "description": "This image displays a Google Colab code snippet for a HREFLANG matcher written in Python. It starts by uploading a CSV file, identifies columns for locale and embeddings, and calculates the top two most similar pairs for each locale. Import statements include essential libraries such as ast, json, math, numpy, pandas, and itertools. The script concludes with an Auto-download feature for outputting results in a CSV format. Keywords: Google Colab, Python, CSV, HREFLANG, data processing." } ```

    Check the vector embeddings existing in column C. Use cosine similarity to match with two suggestions from each locale (locale identified in Column A).

    The goal is to find which pages from each locale are the most similar to each other, so we can add hreflang between these pages.

    I’ll upload a CSV with these columns and expect a CSV in return with the answers.

    After ChatGPT generated the code, I pasted it into Google Colab, which is a free Jupyter Notebook environment for running Python in a browser. I then used “Run all” to test whether the program produced the output I wanted.

    Google Colab code example

    That is the clean version of the process. In practice, AI can make the workflow look perfect while still producing code that does not behave the way I need.

    ```json { "alt": "Screenshot of a code review discussion and code snippet for converting embeddings in Python.", "caption": "Engaging in a code troubleshooting session, this screenshot captures a conversation about refining a Python script to handle dataframe column names efficiently.", "description": "This image shows a screenshot from a discussion about debugging a Python code involving DataFrame column names. A code snippet suggests checking actual column names using 'print(df.columns)' and converting embeddings from strings to numpy arrays. This is a useful reference for data scientists looking to troubleshoot and optimize their data processing scripts, particularly when dealing with CSV file imports and DataFrame manipulations." } ```

    I expect issues along the way, and most of them are simple to troubleshoot if I keep the prompt and testing process clear.

    First, I always state the platform I’m using. If I want code for Google Colab, I say that directly in the prompt.

    Sometimes I still get code that depends on packages that are not installed. When that happens, I paste the error back into ChatGPT and ask it to fix the code or suggest an alternative. I do not need to fully understand the missing package to move forward. I can also ask Gemini inside Google Colab to identify the problem and update the code directly.

    Gemini fixing code in Google Colab

    I also check outputs carefully because AI can sound confident while inventing data. One time, I forgot to specify that the source data would come from a CSV file, so the tool created fake URLs, traffic, and graphs. “It looks good” is not the same as “it is correct.”

    If I connect to an API, especially a paid API from a provider such as Semrush, OpenAI, Google Cloud, or another platform, I need to request my own API key and keep usage costs in mind.

    Semrush subscription dashboard showing API units, masked API key, expiration date, and copy button for SEO API access.
    A Semrush subscription screen highlights 2 million Standard API units and a masked API key, underscoring the setup step needed for SEO automation and vibe-coded tools.
    Semrush API example

    If I want an even lower execution barrier than Google Colab, I can use Replit.

    Replit coding interface

    With Replit, I can prompt what I want, and the platform can generate the code, design the interface, and let me test everything in one place. That reduces copy-and-paste work and gives me a shareable URL quickly. I still need to review poor outputs and keep iterating until the app behaves properly.

    The tradeoff is cost. Google Colab is free unless I use paid API keys, while Replit charges a monthly subscription and usage-based API fees. The more the app runs, the more expensive it can become.

    SEO vibe-coded tools that inspire me

    Google Colab is the easiest place for me to start, but SEOs are taking vibe coding much further. I’ve seen people create Chrome extensions, Google Sheets automations, and even browser games.

    I’m sharing these examples because they show what is possible when useful SEO ideas meet practical AI tooling. If I see a tool and wish it had a different feature, that is often a sign that I could try building a version for myself.

    Replit workspace screenshot showing a KidLaughs AI prompt for a child-friendly daily joke app beside the publishing dashboard.
    A Replit vibe-coding session turns a simple prompt for toddler-friendly daily jokes into a published web app, illustrating how AI tools can quickly prototype playful ideas.

    GBP Reviews Sentiment Analyzer by Celeste Gonzalez

    After vibe coding SEO tools in Google Colab, Celeste Gonzalez, Director of SEO Testing at RicketyRoo Inc, pushed the idea further by creating a Chrome extension. “I realized that I don’t need to build something big, just something useful,” she explained.

    Her extension, the GBP Reviews Sentiment Analyzer, summarizes sentiment analysis from reviews over the last 30 days and shows review velocity. It also exports the information to CSV and works on Google Maps and Google Business Profile pages.

    GBP Reviews Sentiment Analyzer Chrome extension

    Instead of relying only on ChatGPT, Celeste used Claude to create stronger prompts and Cursor to turn those prompts into code.

    AI tools used: Claude (Sunner 4.5 model) and Cursor

    APIs used: Google Business Profile API (free)

    GBP Sentiment Analyzer interface showing analysis complete, review sentiment summary, and export option for Google Business Profile reviews.
    A vibe-coded GBP Sentiment Analyzer turns review data into a quick snapshot, showing negative sentiment trends, key topics, and an export option for SEO workflows.

    Platform hosting: Chrome Extension

    Knowledge Panel Tracker by Gus Pelogia

    I became obsessed with the Knowledge Graph in 2022, when I learned how to create and manage my own knowledge panel. Later, I discovered that Google’s Knowledge Graph Search API lets me check the confidence score for any entity.

    That led me to build a vibe-coded tracker that checks entity scores daily, or at any frequency I choose, and returns the results in a Google Sheet. I can track multiple entities at once and add new ones whenever I need to.

    Knowledge Panel Tracker spreadsheet example

    The Knowledge Panel Tracker runs entirely in Google Sheets, and the Knowledge Graph Search API is free to use. This guide explains how to create and run it in your own Google account, or you can see the spreadsheet here and update the API key under Extensions > App Scripts.

    AI models used: ChatGPT 5.1

    Google Sheets-style Knowledge Panel Tracker listing entity queries, URLs, names, types, descriptions, and confidence scores for SEO research.
    A spreadsheet-based Knowledge Panel Tracker turns entity searches into structured SEO data, comparing names, entity types, descriptions, and confidence scores at a glance.

    APIs used: Google Knowledge Graph API (free)

    Platform hosting: Google Sheets

    Inbox Hero Game by Vince Nero

    I also like the idea of vibe coding a link building asset. That is what Vince Nero from BuzzStream did with the Inbox Hero Game. The game asks players to use the keyboard to accept or reject a pitch within seconds, and it ends if they accept too many bad pitches.

    Inbox Hero Game interface

    Inbox Hero Game is more complex than running a small script in Google Colab, and it took Vince about 20 hours to build from scratch. “I learned you have to build things in pieces. Design the guy first, then the backgrounds, then one aspect of the game mechanics, etc.,” he said.

    The game was built with HTML, CSS, and JavaScript. “I uploaded the files to GitHub to make it work. ChatGPT walked me through everything,” Vince explained.

    Pixel-art Inbox Hero game screen showing a journalist sorting email pitches with hearts, timer, score, and accept or reject controls.
    A retro arcade-style Inbox Hero screen turns PR pitch triage into a fast keyboard game, challenging players to accept or reject emails before time runs out.

    He also found that longer prompt threads became less useful over time, “to the point where [he’d] have to restart in a new chat.”

    That became one of the hardest parts of the project. Vince would add a feature, such as a score, and ChatGPT would “guarantee” it had found the error, update the file, and still return the same problem.

    In the end, Inbox Hero Game shows that it is possible to create a simple game without coding knowledge. It also shows where a developer becomes valuable when the goal shifts from “working prototype” to polished product.

    AI models used: ChatGPT

    APIs used: None

    Platform hosting: Webpage

    How I think about vibe coding with intent

    I do not expect vibe coding to replace developers, and I do not think it should. What I do see is a practical way for SEOs to prototype ideas, automate repetitive tasks, and explore creative experiments without a heavy technical lift.

    The key is realism. I use vibe coding where precision is not mission-critical, I validate outputs carefully, and I stay alert for the moment when a project grows beyond “good enough” and needs stronger technical support.

    When I approach vibe coding thoughtfully, it becomes less about shipping perfect software and more about expanding what I can test. For internal tools, proofs of concept, and SEO side projects, the best results come from pairing curiosity with restraint.

    Inspired by this post on Search Engine Land.

    crushpress.ai community screenshot
  • Unlocking SEO Success with Vibe Coding: Transform Your Strategy

    Unlocking SEO Success with Vibe Coding: Transform Your Strategy

    I’ve discovered that the biggest SEO gains now come from interactive experiences that immediately address user intent and remove friction.

    SEO was once heavily reliant on external factors, especially developer support and waiting on roadmaps that promised features “maybe next quarter.”

    If I needed a new page template, a calculator, or even an interactive component, I had to wait. But that’s no longer the case.

    Nowadays, if you’re involved in SEO or GEO and haven’t explored vibe coding, you might be hindering your potential impact.

    Vibe Coding: Shifting SEO Power Dynamics

    Not long ago, creating tools like calculators or widgets involved lengthy processes, but now I’ve used AI to build dozens of apps without needing a developer.

    Some tools are basic and others not visually appealing, but they’re effective and drive thousands of organic visits monthly.

    Pages centered around these tools are outperforming traditional content competitors.

    ```json { "alt": "The CapmatchOne logo with a gradient circle and bold text.", "caption": "Discover innovation with the CapmatchOne logo, featuring sleek typography and a modern gradient circle.", "description": "The CapmatchOne logo features bold, modern typography coupled with a gradient circle, symbolizing connection and innovation. The sleek design conveys a sense of progress and creativity. This image can be used for branding or promotional purposes, appealing to audiences interested in innovative solutions and forward-thinking designs." } ```
    Parents Hub "Back To School Countdown" Vibe-Coded Tool

    What’s truly transformative is that my SEO team is now adept at building tools independently, which empowers us to achieve our goals faster.

    We can test ideas instantly and utilize developer skills for more complex tasks like scaling and infrastructure.

    There’s a significant sense of accomplishment when creating and releasing a tool that consistently attracts traffic.

    It’s not about sophistication; it’s about building effective tools.

    Engage Directly: From User Personas to Conversations

    The traditional approach says to identify and cater to user personas. But few explain how to present that effectively.

    • Recognize user personas.
    • Pinpoint their challenges.
    • Create content to address those challenges.

    Previously, SEO relied heavily on text targeting personas, which is now outdated.

    ```json { "alt": "Transfer options for families featuring Alcúdia and Santa Ponsa destinations with spacious MPVs.", "caption": "Explore stress-free family transfers to Alcúdia and Santa Ponsa, offering spacious MPVs with optional child seats—your perfect travel solution!", "description": "This image showcases family travel transfer options to popular destinations such as Alcúdia and Santa Ponsa. It highlights services featuring MPVs or minivans that accommodate luggage, strollers, and child seats, ensuring ample space for all travelers. Safety is prioritized with the option to add infant or booster seats to bookings. A pricing guide indicates costs, with MPVs priced at £111 and shuttles at £20 per person. A quick tip mentions services to private villas and fincas in Alcúdia and Pollensa." } ```

    Instead, we should let users self-identify to show the most relevant content.

    • A vibe-coded component with tabs for different personas.
    • Each tab reveals content tailored to that persona.

    For instance, Majorca airport transfers differ greatly between family travelers and solo adventurers.

    Example case of the "User Persona" component

    Families care about safety and child-friendly options, visible only when their tab is selected.

    SEO strategies now harness data from sources like Google Search Console to directly address these needs.

    The component was strategically coded to enhance immediate intent satisfaction.

    This mirrors AI platforms’ approach: segmented, persona-aware, and intent-driven.

    ```json { "alt": "NSRF Childcare Centers calculator interface for estimating voucher eligibility based on family income, number of children, and employment status.", "caption": "Discover your potential NSRF childcare voucher eligibility with this handy calculator. Adjust income, number of children, and employment status for an indicative estimate.", "description": "The NSRF Childcare Centers calculator is designed to provide an unofficial estimate of points and potential voucher amounts for childcare assistance. Users input their family income, number of children, and employment status to receive an indicative result. Additional options include specifying special categories such as single-parent family or disabled family member. This tool aids families in estimating eligibility for NSRF programs." } ```

    Harnessing Traffic through Tool-Only Categories

    In a personal project, I launched a Tools category with ten pages of simple, effective tools like calculators and count-down timers.

    • Calculators.
    • Checklists.
    • Calendars.
    • Countdown timers.
    • AI generators.

    Each page’s centerpiece is its tool, supported by components addressing additional queries.

    The impact? Over 5,000 clicks in two months, even with seasonal variations.

    UI: A Powerful Ranking Factor

    SEO capabilities have expanded, but creativity remains essential.

    Visual presentation is a highly underrated SEO asset today.

    Merely producing text is insufficient. Instantly fulfilling intent through UI is key.

    ```json { "alt": "Interface of Parents Hub Baby Name Generator with input options for sex, name type, and letter count.", "caption": "Discover the perfect baby name with the Parents Hub Baby Name Generator. Customize options based on sex, mythology, and letter count for personalized suggestions.", "description": "This image shows the interface of the Parents Hub Baby Name Generator. It features dropdown menus to select the sex of the baby and type of names, such as 'Mythology'. An input field allows users to specify the maximum number of letters for the name. The prominent 'Suggest names' button indicates the action to generate baby names. Ideal for those seeking unique and meaningful baby name ideas, particularly with a mythological theme." } ```
    • Two calculator pages have added significant monthly sessions.
    • A tool ranked in the top three within days for a government query.
    • Pages rank off-season thanks to superior UI.

    Where others list information, I offer interactive user engagement.

    • Eligibility calculators.
    • Countdown timers.
    • Dynamic tables.
    • Visual comparisons.

    Text backs up the tool rather than being the main attraction.

    SEO Done Right, Quickly

    I published a page targeting a Greek government program, outshining heavy-text competitors.

    We introduced:

    • An eligibility tool.
    • A transparent algorithm explanation.
    • Tips to avoid application errors.
    • Historical program updates.
    • An application walkthrough.
    Parents Hub Kindergarten Financial Support Eligibility Calculator

    The page was promptly tagged and marked up, achieving a first-page ranking within three days and generating substantial clicks.

    Solving problems better than anyone else shortens the typical SEO timeline.

    ```json { "alt": "ChatGPT app settings window showing Ahrefs MCP Server as an enabled app.", "caption": "Explore the possibilities with the Ahrefs MCP Server now enabled in the ChatGPT app settings!", "description": "This image displays the app settings window from ChatGPT 5.2. The interface highlights 'Ahrefs MCP Server' as an enabled app under the 'Enabled apps' section. The dark mode interface shows options like 'Advanced Settings' and 'Drafts,' offering users control over their app configurations. This setup allows integration with Ahrefs MCP for enhanced functionality." } ```

    Maximize SEO and PR with Tools

    Tools can drive traffic or act as valuable digital PR assets.

    A due date calculator or baby name generator could turn into a major PR opportunity.

    A modern tool addressing real needs, outshining SERP features, can become the interface where SEO and PR beacons meet.

    Uncovering Tool Page Opportunities with Ease

    SEO tools’ MCP servers now make discovering tool ideas from search demand a breeze, letting me validate and launch swiftly.

    This method has significantly sped up my tool page creation process compared to traditional methods.

    We’re moving into an era where ideation, validation, and action can occur in days, reducing project duration considerably.

    The Paradigm Shift in SEO

    SEO has evolved beyond long-form content, demanding fast intent fulfillment and seamless user experiences.

    Embracing vibe coding can accelerate development and provide a competitive edge. Building interactive elements, not just content, is crucial for modern SEO success.

    Inspired by this post on Search Engine Land.

    crushpress.ai community screenshot
  • Create an Affordable AI Search Tracker for SEO Success

    Create an Affordable AI Search Tracker for SEO Success

    Tracking my brand’s visibility in AI-powered searches has become an essential part of SEO. However, the available tools often come with hefty price tags, starting around $300 to $500 monthly. For those of us who need custom solutions, these costs can be prohibitive.

    I encountered this challenge firsthand. I required a specific tool that wasn’t available within my budget. So, I took matters into my own hands and built one myself, despite not being a developer. With a weekend of effort and dialogue with an AI agent, I crafted an AI search visibility tracker tailored to my needs.

    Sharing my experiences, I’ve compiled a guide that I wish I had at the start—a step-by-step playbook for creating a custom tool. This guide navigates through technology, processes, the hiccups I faced, and how to streamline your build.

    My main goal was to automate an AI engine optimization (AEO) testing protocol. To achieve comprehensive AI-driven brand visibility, tracking across five critical AI surfaces was necessary:

    ChatGPT (via API): Renowned for its conversational AI prowess.

    ```json { "alt": "Dashboard interface of AEO Testing platform with recent test runs listed.", "caption": "Explore the AEO Testing platform's dashboard, showcasing recent test runs with detailed analytics.", "description": "The image displays the AEO Testing platform dashboard. The interface includes navigation options on the left, while the main section shows test statistics, such as total runs, prompts, average accuracy, and error percentage. A list of recent test runs also is visible, detailing their status, date, and batch information. This image offers insights into the platform's functionality and user interface, ideal for understanding its test management capabilities." } ```

    Claude (via API): A significant competitor with a unique response style.

    Gemini (via API): Google’s direct model aimed at developers.

    Google AI Mode: Enhances Google’s AI search experience with advanced reasoning.

    Google AI Overviews: Summaries at the top of search results, prevalent by late 2025.

    ```json { "alt": "AEO Testing platform interface showing a list of prompts in the Prompt Library with options to upload CSV files and create new prompts.", "caption": "Explore and manage your testing prompts effortlessly with the AEO Testing platform. Customize your test runs by uploading CSV files or creating new prompts on the go.", "description": "This image showcases the AEO Testing platform interface, specifically focusing on the 'Prompts' section. The interface displays a list of prompts categorized under different classes such as 'Acquisition' and 'Current Customer.' It includes options to manage prompts by uploading CSV files or creating new ones. The navigation menu on the left offers access to various features like Dashboard, Test Runs, Analytics, and Settings. This setup aids users in efficiently managing their evaluation testing processes. Keywords: AEO Testing, Prompt Library, CSV upload, New Prompt." } ```

    On top of these, I implemented a custom 5-point rubric for scoring results based on criteria like brand name inclusion and citation quality. With no existing SaaS tools offering this particular mix, the solution was to build one.

    This project leveraged vibe coding, translating natural language into functional applications with AI assistance. Amid developers increasingly adopting AI coding and the growing trend of AI-generated code, this approach offered a viable path for a non-developer like me to create an impactful internal tool.

    Your tech stack: The three tools you’ll need

    To replicate this project while keeping costs manageable, here are the necessary components:

    Replit Agent: An online development environment costing around $20/month, enabling application building via description alone.

    ```json { "alt": "Dashboard of AEO Testing Platform showing test run history with various test details.", "caption": "Explore the AEO Testing Platform interface showcasing comprehensive test run history and execution statuses for efficient analytics.", "description": "This image displays the AEO Testing Platform dashboard, highlighting the 'Test Runs' section. It includes details of various test runs, such as Q1 Test Jan 19th and 50 Prompt Test Run 5, with statuses ranging from running to completed. Tags like chatgpt and gemini are used, and features include view results and details options. This interface aids in managing and analyzing test execution history efficiently." } ```

    DataForSEO APIs: The core of this project, allowing data retrieval from various AI platforms, priced on a pay-as-you-go model.

    Direct LLM APIs (optional): Establishing direct connections with OpenAI, Anthropic, and Google APIs to verify and correct any discrepancies.

    The playbook: A step-by-step guide to building your tool

    Building this tool involved clear communication and step-by-step progress. Here’s a structured approach to guide your process:

    Step 1: Write a requirements document first

    Start by outlining your needs clearly. This document acts as a blueprint covering problems, features, and necessary data. Initial conversations with your AI should revolve around this document to set a solid foundation.

    ```json { "alt": "The CapmatchOne logo with a gradient circle and bold text.", "caption": "Discover innovation with the CapmatchOne logo, featuring sleek typography and a modern gradient circle.", "description": "The CapmatchOne logo features bold, modern typography coupled with a gradient circle, symbolizing connection and innovation. The sleek design conveys a sense of progress and creativity. This image can be used for branding or promotional purposes, appealing to audiences interested in innovative solutions and forward-thinking designs." } ```

    Step 2: Ask the AI, ‘What am I missing?’

    Once your needs are outlined, seek the AI’s help in uncovering overlooked areas. Questions like “What am I not accounting for?” can avert common pitfalls and ensure comprehensive planning.

    Step 3: Build one feature at a time and test it

    Avoid building everything simultaneously. Tackle one small task and test it thoroughly before moving to the next. This methodical approach aids in pinpointing and addressing issues efficiently.

    Step 4: Point the agent to the documentation

    When integrating APIs, guide the AI using specific documentation. Providing exact URLs ensures accurate implementation and saves time otherwise spent fixing errors.

    Step 5: Save working versions

    Before introducing significant changes, save copies of your project. In Replit, this is done through “forking.” It’s a precaution against potential new feature-induced disruptions.

    ```json { "alt": "DataForSEO task lookup dashboard with task details, dates, costs, and results.", "caption": "Explore the detailed task lookup interface on DataForSEO, showcasing task status, results, and costs - a comprehensive tool for data optimization.", "description": "This image shows the DataForSEO task lookup dashboard interface. The dashboard displays a list of tasks with details including task ID, search engine, task set, completion time, turnover duration, cost, and task result. Users can export data or choose columns to display. The navigation menu on the left provides access to various features including settings and documentation. A user profile and balance are displayed at the top right. Useful for businesses seeking data optimization insights." } ```

    Common problems and how to fix them

    You’ll likely face technical hurdles. Here are frequent issues with solutions to help you navigate the process smoothly:

    ProblemSolution
    1. API authentication failsProvide the exact authentication documentation URL to the agent.
    2. Results disappearEnsure persistent storage by requesting a database from the start.
    3. API responses don’t showShare raw JSON data with the agent to diagnose and fix parsing logic.
    4. Model response cut shortConduct parameter checks post-updates to maintain consistent results.

    Evaluating the real costs

    Building this tool has clear advantages over purchasing a SaaS solution, notably cost savings. Here’s a breakdown:

    ExpenseCustom ToolSaaS
    Subscription$20/month$500/month
    API Usage$60/monthIncluded
    Total$80/month$500/month

    Despite the initial time investment, the ability to adapt and tailor the tool outweighs the ongoing costs.

    Is building your own tool right for you?

    This decision largely depends on your specific needs:

    Consider building if:

    • You require unique testing methods not supported by current tools.
    • Your agency needs a white-labeled solution.
    • You prefer cost-effective strategies and are willing to invest time.

    Stick with SaaS if:

    • Your time is more valuable than subscription costs.
    • You need robust security and customer support.
    • You find standard features sufficient.

    Ultimately, crafting a tool that aligns perfectly with your workflow can provide a distinct edge in the competitive SEO landscape. Welcome to the era of practitioner-developers; it’s time to innovate.

    Inspired by this post on Search Engine Land.

    crushpress.ai community screenshot
  • Build Powerful PPC Tools Instantly with Vibe Coding Magic

    Build Powerful PPC Tools Instantly with Vibe Coding Magic

    Discover how vibe coding empowers me to create custom PPC tools quickly using intuitive AI prompts instead of traditional coding techniques.

    I now find myself able to generate custom PPC tools using plain English, thanks to GPT-5. It’s a game-changer, giving a competitive edge to those who embrace AI-assisted automation.

    Frederick Vallaeys, who has built tools in mere minutes instead of months, is leading the way with AI. He has ten years of experience at Google creating invaluable tools like the Google Ads Editor and another decade at Optmyzr as CEO.

    Vallaeys has witnessed the evolution of automation firsthand, and vibe coding is the next giant leap. At SMX Next 2025, he shared his personal journey with vibe coding.

    If you’re involved in PPC, automation is crucially important. Initially, I relied heavily on Google Ads scripts because there was always more work than could be done in a day.

    ```json { "alt": "Presentation on converting a flowchart to Google Ads script with a handwritten flowchart and displayed script.", "caption": "Transform your marketing strategy! Learn how to convert a flowchart into an actionable Google Ads script for better campaign control and efficiency.", "description": "This image displays a slide from a presentation on converting a flowchart into a Google Ads script, featuring a handwritten flowchart and accompanying script on-screen. The flowchart outlines decision-making based on target ROAS (Return on Ad Spend) and conversions, while the script provides a structured approach to automate this process. Ideal for marketing professionals seeking to enhance campaign effectiveness. Keywords: Google Ads, flowchart, script, marketing automation." } ```

    The problem arises when Vallaeys questions who truly writes their scripts. Only a few people raise their hands, as most often copy and paste due to lack of coding skills.

    This results in limitations, confining you to what others have crafted instead of adding your personal flair.

    GPT revolutionized scriptwriting for those without coding skills.

    The best part lies in large language models being multimodal. Now, a simple photo of my campaign decision flowchart can be deciphered by AI to generate a complete Google Ads script.

    Instead of viewing client meetings as additional work, I’ve embraced them as opportunities for prompt-engineering sessions.

    ```json { "alt": "Presentation slide titled 'Let's Vibe Code Something' with a task to build a persona scorer for an ad. Speaker is visible on the left.", "caption": "Exploring the fusion of coding and creativity, the presentation delves into building a persona scorer for ads, sparking inspiration for innovation.", "description": "This image showcases a presentation slide titled 'Let's Vibe Code Something,' focusing on a task to build a persona scorer for ads. The speaker is featured to the left, suggesting a live engagement. The slide mentions creating apps with AI, hinting at the intersection of technology and creativity. This context is suitable for those interested in coding, AI, and innovative marketing strategies. Ideal for search queries related to AI-driven app development and persona scoring." } ```

    Changing my mindset allowed me to treat these meetings as prompt instructions for AI, simplifying task execution.

    Instead of delving into code, I merely describe my desired outcome, and AI takes care of the technical side. That’s vibe coding for you!

    Imagine needing software to perform functions X, Y, and Z. Detail your needs to a coding tool, and watch as it constructs the software. Vallaeys describes this process as mind-blowing.

    Scripts have become outdated; vibe coding is the way forward.

    Vallaeys demonstrated the effectiveness of this method by requesting a persona scorer for an ad tailored to various audiences from Lovable. The result was rapid and precise.

    ```json { "alt": "Presentation slide discussing tasks for automation, with a focus on marketing tasks, alongside a speaker.", "caption": "Exploring the evolution of automation in marketing: Identifying small and large tasks ripe for automation in a pre-AI era.", "description": "This image displays a presentation slide titled 'Tasks to Consider for Automation' from a marketing event. It outlines 'LOTS' of tasks, such as frequent analysis and review, and 'LONG' tasks like report generation and updating account structures for efficient automation. A speaker is visible in the corner, indicative of a live presentation. The slide emphasizes the transition to more affordable automation processes and is relevant for digital marketers looking to optimize routine and strategic activities. Keywords: automation, marketing, tasks, analysis, RSA headlines, account structure." } ```

    Working collaboratively with it, akin to a human developer, you describe needed changes without ever touching code.

    The automation framework traditionally targeted tasks ranging from frequent, quick activities to extensive, periodic ones. Vallaeys recommends not limiting automation to what’s already being done, but rather considering what you wish to do more often, making time-consuming tasks manageable.

    The old method was slow, taking at least a month to launch anything.

    I used to spend days compiling specifications, waiting for engineers to build, finding bugs, organizing meetings, and repeating the cycle.

    Traditional code was deterministic, relying purely on if/then logic. While reliable, it struggles with nuanced actions, like identifying competitor terms. Encompassing every variation of competitor keywords was virtually impossible.

    ```json { "alt": "Flowchart showing the process of building automations involving marketers and engineers, with time estimates for each step.", "caption": "Discover the intricate dance between marketers and engineers in building automations—where coordination and timing make all the difference.", "description": "This flowchart illustrates the process of building automations with input from both marketers and engineers. It begins with a marketer writing a specification, followed by engineers building based on the spec. The cycle then involves discovering bugs, changing specs, and updating code, iterating over several days before reaching a launch phase after a month. The image is part of an SMX presentation on search marketing automation." } ```

    Sam Altman’s launch of GPT-5 heralded a new era of on-demand software generation, transitioning beyond software-as-a-service.

    Tapping into this new approach takes just minutes, from writing a spec to letting AI build and refine it. Within an hour, you have a functional automation tool.

    This code isn’t just deterministic; it’s also flexible. Large language models handle nuanced queries with impressive accuracy.

    Vibe coding allows machines to create anything I can articulate clearly, from landing pages adhering to brand guidelines to unique audience tools.

    This paradigm shift means even tasks taking 90 minutes by hand are candidates for automation, creating disposable software to save time today, unaffected by future failures.

    ```json { "alt": "A person gives a presentation with a slide showing a robot at a computer. Text lists items like landing page and mobile app.", "caption": "Exploring creative possibilities with Vibe Code: A futuristic look at coding applications with an AI-driven robot at the helm.", "description": "The image shows a presentation slide featuring a robot seated at a computer, symbolizing advanced technology in coding. The slide titled 'Things You Can Vibe Code' lists several coding projects: Landing page, Microsite, Interactive web app, Mobile app, Browser extension, and WordPress plugin. A person is presenting, emphasizing innovation in technology. The SMX logo, representing search marketing, is also visible. Keywords: Vibe Code, robot, coding, innovation, technology." } ```

    Vibe coding enables building a range of online solutions — from landing pages to browser extensions — all through simple directives.

    Begin with tools you may already use, such as Claude or ChatGPT, for data analysis or visualization tasks.

    For more complex applications with databases or user logins, tools like Lovable, V0.dev, Replit, or Bolt simplify the process.

    If you have technical skills, Codex, Bolt.new, or Cursor offer robust capabilities, but simpler tools are often sufficient.

    I challenged someone in my team with no coding background to create a seasonality analysis tool using Claude.

    ```json { "alt": "Presentation slide showing tools for vibe coding, with options for coders and non-coders.", "caption": "Explore the best tools for vibe coding, whether you're a seasoned coder or just starting out! Discover options tailored for both coders and non-coders.", "description": "This image features a presentation slide titled 'Tools for Vibe Coding,' highlighting tools for both coders and non-coders. For non-coders, it lists Claude (Anthropic), ChatGPT, and platforms like Lovable.dev, V0.dev, and Replit, known for AI-powered applications and data analysis. Options for coders include GitHub Copilot, Bolt.new, and Codex. The background is a geometric blue pattern, with a small speaker image in the left corner, likely presenting the slide. Keywords include coding, AI tools, and presentation." } ```

    The process involved gathering materials, crafting a prompt, and testing via a browser without requiring installation.

    The team quickly iterated, enhancing features. The AI efficiently added helpful guidance and streamlined interfaces, leveraging its extensive training.

    I envisioned a tool sequence for expert review of blog posts, synthesizing feedback through a consolidated summary. This was easily vibe-coded in V0.dev.

    A Chrome extension for demos needing to blur sensitive numbers was swiftly constructed via simple prompts, addressing specific visibility needs.

    Effective prompting involves specifying the exact use case, allowing AI to generate relevant options and suggest innovative methods.

    ```json { "alt": "Screenshot of PPC Ad Audience Analyzer with a blue background. A man is visible in the bottom left corner.", "caption": "Exploring the PPC Ad Audience Analyzer: Discover AI-driven insights that elevate your ad strategies with just one prompt. Ideal for marketers aiming to optimize audience targeting.", "description": "This image shows a comprehensive screenshot of the PPC Ad Audience Analyzer interface, designed to provide AI-powered insights on ad audiences. The screen highlights target audience analyses for fitness enthusiasts and brand-loyal customers with identified strengths and potential issues. A man is pictured on the left, and a QR code and call-to-action prompt users to explore customization options. With a blue geometric background, this tool is aimed at marketers seeking to enhance their advertising strategies." } ```

    Engage with questions to uncover insights such as process approaches or data storage solutions, furthering learning opportunities.

    Utilizing chat mode for alternative exploration is advantageous, allowing detailed direction without altering code initially.

    You can experiment with my team’s audience analyzer, adapting it with ease to suit specific needs like logo integration or functional adjustments.

    It’s clear from Vallaeys: the competition isn’t against AI but against individuals harnessing its capabilities more effectively.

    Dive into vibe coding today. Select a tool, issue a simple prompt, and witness the remarkable outcomes firsthand. My first attempt left me in awe.

    By integrating this newfound knowledge, improving AI skills becomes attainable, ensuring a competitive edge.

    Inspired by this post on Search Engine Land.

    crushpress.ai community screenshot
  • Mastering Vibe-Coding: SEO Tools Without Losing LLM Control

    Mastering Vibe-Coding: SEO Tools Without Losing LLM Control

    I interact with LLMs daily, both at work and in my personal projects. For many of us in tech, leveraging these language models has become second nature.

    It’s well-known that folks in the tech sector, like me, engage with LLMs at twice the rate of the general population. In my case, LLM usage often exceeds a full day each week.

    ```json { "alt": "Bar chart showing LLM usage for work with categories ranging from 'More than 10 hours' to 'Do not use LLMs', highlighting percentages and sample sizes.", "caption": "How much do you rely on language models for work? This bar chart reveals that most people use LLMs for 1-2 hours, while a significant portion doesn't use them at all.", "description": "This bar chart illustrates the usage amount of language models (LLMs) for work among 1963 individuals. Categories range from 'More than 10 hours' to 'Do not use LLMs for work'. The chart shows that 26% use LLMs for 1-2 hours, while 24% use them for less than an hour. Meanwhile, 12% don't use LLMs for work at all. Data highlights are expressed in both percentage and sample size, providing insights into LLM reliance." } ```

    Even as regular users, we sometimes find ourselves frustrated when an LLM doesn’t quite deliver the responses we expect. Here’s how I effectively communicate with LLMs during vibe coding sessions. These insights are just as valuable when navigating extended interactions with an LLM UI like ChatGPT.

    ```json { "alt": "The CapmatchOne logo with a gradient circle and bold text.", "caption": "Discover innovation with the CapmatchOne logo, featuring sleek typography and a modern gradient circle.", "description": "The CapmatchOne logo features bold, modern typography coupled with a gradient circle, symbolizing connection and innovation. The sleek design conveys a sense of progress and creativity. This image can be used for branding or promotional purposes, appealing to audiences interested in innovative solutions and forward-thinking designs." } ```

    Choosing My Vibe-Coding Environment

    ```json { "alt": "Screenshot of a conversation about building a system in Cursor with a focus on SEO and AI Overviews.", "caption": "Discussing innovative ways to leverage AI Overviews in Cursor for improved SEO processes while brainstorming effective content strategies.", "description": "This image showcases a discussion about developing a system in Cursor intended for SEO enhancement using AI Overviews provided by Google. The conversation mentions the dynamic nature of AI Overviews in 2026 and the potential for leveraging the 'Composer' feature for simultaneous iteration of scraper and LLM logic. Keywords include SEO, AI Overviews, and Cursor system development." } ```

    Vibe coding is the art of co-creating software with AI. I lay out my vision, the AI generates code, and together we refine it to match my intent. However, the process isn’t always smooth sailing.

    ```json { "alt": "Table showing SERP API providers with highlighted SerpApi using page token for AI overviews.", "caption": "Explore the future of AI overviews with dedicated SERP APIs like SerpApi, designed for efficiency and reliability.", "description": "This image illustrates the concept of reverse-engineering Google AI overviews using SERP APIs. It features a table of SERP providers, highlighting the 'SerpApi' which employs a 'page_token' for fetching AI overviews. This professional method offers a reliable solution for managing proxy rotation and JavaScript execution. Keywords: SERP API, Google AI, page token, SerpApi." } ```

    The first step in my workflow involves choosing a coding environment. This space serves as a hub for interacting with the LLM, drafting, and executing code. I’m partial to Cursor, having started on their free Hobby plan, but I’ve since upgraded to the Pro+ account due to my extensive usage.

    ```json { "alt": "Comparison table of high-precision AI models for document extraction, highlighting Gemini 3 Pro, GPT-5.2, and Claude 4.1 Opus with their accuracy scores.", "caption": "Explore the leading AI models in precision document extraction, with Gemini 3 Pro, GPT-5.2, and Claude 4.1 Opus setting benchmarks in accuracy and contextual intelligence.", "description": "This image showcases a comparison table of advanced AI models that excel in high-precision extraction tasks from complex documents. Featured are Gemini 3 Pro, renowned for its multimodal capabilities with a top benchmark score of 92.6%, GPT-5.2, recognized for its structured output proficiency with a similar score of 92.4%, and Claude 4.1 Opus, noted for contextual intelligence with a benchmark of 43.6%. Ideal for legal or medical queries, this overview provides essential information for selecting the right AI model." } ```

    For those interested, here are some environment options:

    ```json { "alt": "Text discussing a recommendation for using a cross-verification ensemble of AI models Claude 4.6 and GPT-5.2.", "caption": "Discover a strategic approach using Claude 4.6 and GPT-5.2 for thorough AI model analysis through cross-verification, enhancing output accuracy.", "description": "This image contains a text-based recommendation on employing a cross-verification ensemble of AI models, specifically Claude 4.6 and GPT-5.2. It suggests avoiding reliance on a single model, as current benchmark leaders are closely matched. By using Claude 4.6 for nuanced question extraction and GPT-5.2 for systematic interpretation, a third 'Judge' instance can be used to evaluate the results, ensuring more accurate outcomes. This method emphasizes precision and comprehensive analysis in AI-generated tasks." } ```
    • Cursor: Widely used by vibe coders for its customizable interface.
    • Windsurf: An alternative that executes terminal commands independently.
    • Google Antigravity: A unique option favoring agent-driven development.
    ```json { "alt": "Screenshot of a software interface displaying a panel with layout options and customizable settings.", "caption": "Exploring the customizable settings in this software tool, featuring layout toggles and agent configuration options for a personalized interface experience.", "description": "This image showcases a user interface of a software application, highlighting a panel with layout options such as Agents, Editors, and Sidebar. The interface allows customization through toggle switches and displays a right-aligned panel for additional settings. This environment is likely designed for users seeking a tailored workspace setup. Keywords: software interface, customization, layout options, user interface." } ```

    In my examples, I’ll be using Cursor, but the principles are applicable across platforms. Even if you’re simply delving deep into LLM conversations, the same guidelines apply.

    ```json { "alt": "Screenshot of model selection menu, highlighting Claude Opus 4.6 with options like auto and MAX mode.", "caption": "Choosing the right AI model is crucial - here, Claude Opus 4.6 is highlighted for its power and capability in tackling difficult tasks.", "description": "The image displays a user interface for selecting AI models, with 'Claude Opus 4.6' highlighted. It indicates this model as Anthropic's most powerful option, suitable for complex tasks, with a 200,000 context window and high effort version. Other model options listed include Composer 1.5, Opus 4.6 Max, and GPT-5.2. The interface also features toggles for 'Auto' and 'MAX Mode'. Keywords: AI model, selection menu, interface, Anthropic, Claude Opus 4.6." } ```

    Why Prompting Alone Isn’t Enough

    ```json { "alt": "Screenshot of a software interface showing a dropdown menu with options: Agent, Plan, Debug, Ask.", "caption": "Navigating through the software interface: a dropdown menu reveals various action options for creating detailed plans and debugging.", "description": "This image showcases a screenshot of a software interface featuring a dropdown menu in the Plan section. Options visible in the menu include Agent, Plan, Debug, and Ask, highlighting tools for task management and problem solving. The selected option is 'Plan' with a tooltip that says 'Create detailed plans for accomplishing tasks,' illustrating a user-friendly interface designed for easy navigation and efficient workflow." } ```

    You might ask why we’d even need a tutorial for vibe coding. It’s true—the basic idea is simple: specify an outcome, and the LLM delivers. However, once the complexity increases, especially when dealing with multifile systems or tools, context management becomes crucial.

    ```json { "alt": "Screenshot of a digital note outlining a plan for using AI in SEO content strategy.", "caption": "Exploring innovative SEO strategies with AI: A detailed plan to harness AI-generated insights for content creation.", "description": "This image features a screenshot of a digital workspace detailing a plan for leveraging AI in SEO content strategy. The note outlines steps including selecting queries, conducting searches, and using AI to extract questions and insights. The interface shows various tool options and written content, reflecting a modern approach to integrating AI technologies in SEO planning. Keywords include AI, SEO, content strategy, and digital planning." } ```

    The context window is a pivotal concept. It’s the memory scope LLMs use to handle input/output data, a window defined by token limits. For example, GPT-5.2 allows a 400,000-token window, while Gemini 3 Pro goes up to 1 million. Understanding this helps in avoiding token overflow, which can diminish retrieval accuracy.

    ```json { "alt": "Screenshot showing search confirmation options with checkboxes and buttons.", "caption": "Manage searches efficiently with convenient confirmation options, ensuring precise data retrieval and control over automated web searches.", "description": "This image is a screenshot of a user interface displaying search confirmation options. Each option includes a checkbox for auto-search web activation and buttons labeled 'Cancel' and 'Continue.' The interface is designed to streamline search management, allowing users to confirm or cancel searches efficiently. Keywords: search confirmation, auto-search, user interface, screenshot, button, checkbox." } ```

    Expert commentator Matt Pocock explains the nuances of context windows well—view his YouTube video for more insight. For now, keep in mind that effective planning minimizes verbosity and assumes clear window management.

    ```json { "alt": "User interface showing a question about detail level for extracted questions with options A to D.", "caption": "Choosing the Right Detail Level: A snapshot of a user interface question asking for preferred detail levels, presenting options from simple lists to full analyses.", "description": "This screenshot displays a user interface element questioning the desired level of detail for extracted questions. It offers multiple choice options, labeled A through D, where users can select from just listing questions, adding context, or providing a full analysis. The image also shows the user's previous choices for other questions, emphasizing the interface's decision-making process and user engagement. The design showcases typical elements of interactive software, useful for usability studies and interface design discussions." } ```
    • One team, one dream. Divide projects into manageable phases, clearing LLM memory regularly between tasks.
    • Do your own research. While you don’t need exhaustive detail, grasp general methods and potential build paths.
    • Trust but verify during troubleshooting. Get clarifications from the LLM and cross-check details externally.
    ```json { "alt": "Screen showing code and notes for AI model selection and logging.", "caption": "Diving into AI model selection, this screen showcases notes on using GPT models and detailed instructions on creating a logging system with W&B Weave for data analysis.", "description": "This image captures a computer screen displaying code and notes related to AI model selection and logging. Key points include instructions on choosing GPT models such as gpt-4-turbo, recommendations for reasoning models, and guidance on setting up W&B Weave logging with the 'src/weave_logger.py' file. The image is useful for those interested in AI, programming, and data analysis, offering insights into structured query analysis and project initialization." } ```

    Explore Further: How Vibe Coding Transform Search Marketing Workflows

    ```json { "alt": "Console output showing AI analysis for best running shoes 2026, displaying questions about shoe features and sizing.", "caption": "Exploring the Future of Running: AI Analysis Reveals Top Questions on 2026's Best Running Shoes.", "description": "The image displays a console output analyzing 'best running shoes 2026' using AI tools. Key findings include questions about shoe features like cushioning and support, and tips on choosing the right shoe size. The analysis points to an AI Overview and SerpAPI integration, and emphasizes logging to W&B Weave for SEO content planning. The setup involves tasks listed on the right, within a user interface showing the project plan and dependencies." } ```

    Tutorial: Creating an AI Overview Question Extraction System

    ```json { "alt": "Screenshot of a text editor with notes and AI prompts on the screen.", "caption": "Capturing a strategic workflow in a text editor, this screenshot reveals insights into AI integration and error handling, sparking curiosity about implementation.", "description": "This image is a screenshot displaying a text editor interface filled with notes. On the left, there are identifiable headers and bullet points discussing tasks related to AI overview and handling. The right side features a task list addressing error messages and system responses in AI systems. The screenshot includes UI elements like menus and prompts, indicative of digital planning and coding strategy. Keywords include AI integration, task management, and error recovery." } ```

    To produce high-ranking content in AI Overviews, address the questions they respond to. This tutorial guides you in developing a tool to extract such questions, not just to provide a use case but also to demonstrate effective system development via vibe coding. It’s not a guaranteed path to AI prominence but offers strategic insights.

    ```json { "alt": "Screenshot of a command input interface featuring file navigation and options.", "caption": "Explore the interface designed for efficient navigation and command input, optimizing workflow with ease.", "description": "This image displays a user interface with a focus on file management and command input. The design includes options such as '9 Files' and a section for planning or executing commands with an input field labeled 'Agent' and a dropdown titled 'Gemini 3 Pro'. This interface is designed for seamless navigation and efficient operation, offering practical tools for users to manage their tasks effectively. Keywords: interface, command input, file management, navigation." } ```

    Step 1: Planning

    ```json { "alt": "Screenshot of a coding environment showing Python code for a question extraction tool using AI overview.", "caption": "Exploring a detailed coding environment where a question extraction module is being developed using AI technology.", "description": "This image showcases a coding environment, likely Visual Studio Code, where a Python implementation for a question extraction tool is visible. The code involves using GPT-5.2-based AI to extract questions from overview text retrieved via SerpAPI. The interface highlights a class definition named 'QuestionExtractor' with methods to initialize and extract questions. The environment displays open files related to the project, such as 'plan.md' and 'requirements.txt', with a visible git diff indicating recent changes." } ```

    Before diving into Cursor or any other tool, identify your goals and necessary resources. Although it’s early days, using generative AI for initial brainstorming can be beneficial. I often start by articulating my end goal in a sentence or two, alongside requisite steps, in AI tools like Gemini or ChatGPT. Missteps here are okay—this stage is about outlining thoughts, not finalizing builds.

    ```json { "alt": "Visual Studio Code workspace with an open .env.example file showing API key configurations.", "caption": "A glimpse into a developer's setup on Visual Studio Code, showcasing an open .env.example file rich with API key configuration details.", "description": "This image displays a Visual Studio Code environment with the .env.example file open. The file contains template configurations for various API keys such as SerpAPI and OpenAI, as well as WandB Weave. Text in the right pane provides an overview of tasks completed and next steps in a project setup. The workspace is tidy and organized, suggesting a structured approach to software development." } ```

    For instance, I could outline:

    ```json { "alt": "Screenshot of a code editor open with a terminal menu expanded.", "caption": "The terminal menu in a code editor is opened, offering a variety of task and terminal options for development.", "description": "The image displays a code editor with the 'Terminal' menu expanded, showcasing options such as New Terminal, Run Task, and more. The background shows code highlighted in green. This setup is commonly used for software development, with tools to manage and execute various programming tasks efficiently." } ```
    I’m an SEO, aiming to leverage Google's AI Overviews to inspire our authors' content. We need to extract implicit questions addressed by AI Overviews. Proposed steps include:

1 – Choose a keyword target.
2 – Run a search and collect the AI Overview.
3 – Deploy an LLM to derive underlying questions from the AI Overview.
4 – Preserve questions in an accessible format.
    ```json { "alt": "Terminal window showing Python virtual environment setup commands.", "caption": "Setting up a Python virtual environment in the terminal is essential for managing project dependencies efficiently.", "description": "This image displays a terminal window with commands for setting up and activating a Python virtual environment. The commands shown involve initializing the environment with 'python3 -m venv .venv' and activating it using 'source .venv/bin/activate'. This process helps in isolating project dependencies, ensuring that each project has its own libraries and versions. Keywords: Python, virtual environment, terminal, command line, project setup." } ```

    With a clear direction, select your preferred LLM. While I’m partial to Gemini for chats, modern models with robust reasoning will suffice. Initiate a session, state your intent to build an AI Overview extractor, and share your planning prompt.

    ```json { "alt": "Terminal window showing installation of Python packages via pip.", "caption": "Capturing a moment in the life of a developer: installing crucial Python packages with pip in a terminal window.", "description": "This image displays a terminal window on a computer, where a user is installing Python packages using pip, via a requirements.txt file. The process includes packages like google-search-results, openai, weave, python-dotenv, click, and requests. Installation progress messages and metadata details are visible, reflecting a typical setup process in a Python environment. This scene is common during software development, particularly when setting up virtual environments." } ```

    Step 2: Laying the Foundation

    ```json { "alt": "Environment file with API key configurations in code editor.", "caption": "Securely configuring API keys in a .env file for seamless integration and management.", "description": "This image shows a .env file opened in a code editor, featuring configurations for various APIs including SerpAPI, OpenAI, and W&B Weave. Important API keys are masked for security. The file also includes a section for optional model selection, showcasing a structured approach to manage environment variables crucial for development. Keywords: API configuration, .env file, code editor, environment variables." } ```

    Cursor offers diverse models which I find advantageous. For this task, start in Plan mode, allowing for structured discussions and informed decision-making.

    ```json { "alt": "Terminal screen displaying error messages for SEO query in Python script.", "caption": "An unexpected journey in debugging: tracing the elusive 'what is SEO' query in a Python session.", "description": "This image shows a terminal window with a Python script execution for an SEO-related query 'what is SEO.' The terminal logs display error messages indicating no AI overview was found and suggest broader search strategies. The environment seems to involve integration with Weights & Biases and Weave projects. Useful for developers working on SEO automation and debugging script issues, highlighting common real-time troubleshooting steps." } ```

    Kick off discussions with our defined project prompt.

    ```json { "alt": "Search result page for 'what is seo' explaining search engine optimization.", "caption": "Exploring SEO: A glimpse into how search engine optimization enhances website visibility in organic search results.", "description": "The image shows a search result page for 'what is SEO' in a browser. It highlights a section explaining SEO as the practice of improving a website to increase its visibility in organic search results. Key aspects include optimizing technical infrastructure and content relevance. The goal is to attract targeted traffic by ranking higher for user queries. SEO is essential for effective online presence and digital marketing." } ```

    Making modifications is crucial, so carefully review the LLM’s plan to ensure alignment with your vision. Address any disparities through collaborative discussions with the model.

    ```json { "alt": "Terminal window showing a Python script execution with search queries related to SEO.", "caption": "Exploring SEO Queries: A glimpse into how a Python script handles search term analysis in the terminal.", "description": "The image displays a terminal window where a Python script is being executed to analyze SEO-related search queries. The script searches for variations of 'what is SEO,' and notes the absence of an AI overview. Commands and responses highlight interactions with Weights & Biases integration, offering insight into query handling processes. Keywords include Python script, terminal window, SEO, and search query analysis." } ```

    Consider seeking insights into possible project failure points and implement preventive measures accordingly. For efficiency, I tend to request models to generate outline files for improved context window management, validating internal consistency before proceeding.

    ```json { "alt": "Coding interface with text suggesting a search query issue on AI overview.", "caption": "Debugging an AI Overview query issue in a coding interface, with instructions to review the approach.", "description": "The image shows a coding interface with text highlighting a problem with an AI Overview search query. Users are prompted to broaden the search or troubleshoot. There's also a side panel with a Python file related to SerpAPI documentation, providing context on the issue. This setup is used for testing or refining API interaction mechanisms." } ```

    Step 3: The Build

    ```json { "alt": "Screenshot of a terminal running a Python script related to SEO question extraction.", "caption": "Diving into SEO: This screenshot captures the execution of a Python script designed to extract questions about SEO, showcasing command line output and search results.", "description": "This image is a screenshot of a terminal window showing the execution of a Python script aimed at extracting SEO-related questions. The script is run within a virtual environment, and the output displays successful extraction of questions about Search Engine Optimization (SEO), including context and importance ratings. Keywords such as 'Python script', 'SEO', 'terminal', and 'question extraction' are relevant for search purposes. The screenshot also features tool references like Weights & Biases and some minor deprecation warnings." } ```

    With the foundation laid, shift to Agent mode using your selected model—in my case, Gemini 3 Pro—to execute the building phase. Keep an eye out for required approvals during script execution to ensure a smooth process.

    ```json { "alt": "Terminal window showcasing SEO question extraction with highlighted text.", "caption": "Delve into the nuances of SEO question extraction with this detailed terminal output highlighting context and importance.", "description": "This image shows a terminal window displaying a process related to SEO question extraction. Text about important SEO aspects like search engines and Google understanding pages is highlighted. The window includes links to further analyses and paths, indicating a running environment for code execution. Keywords include terminal, SEO, question extraction, and Google." } ```

    Once script development is complete, proceed with library installations via the provided requirements.txt file. For organized dependency management, setting up a virtual environment is recommended.

    ```json { "alt": "Dashboard view showing query analysis related to SEO using a GPT model.", "caption": "Discover how AI interacts with SEO queries using a detailed dashboard analysis. Dive into how machine learning models, like GPT-5.2, interpret and respond to search optimization questions.", "description": "This image depicts a dashboard screen from a project on online inference, showcasing the use of AI to analyze SEO-related queries. The left pane displays a list of traces, while the right pane details selected inputs and outputs. Highlighted sections show inputs like the query 'what is seo' using model 'gpt-5.2', and outputs with comprehensive AI overview and questions. Significant text annotations emphasize the user interaction elements and analysis details, providing a clear visual representation of AI in SEO application. Keywords include SEO, AI analysis, GPT model, dashboard, and query processing." } ```

    Running your first script execution often surfaces unforeseen challenges. Tackle these by leveraging comprehensive diagnostic feedback, ensuring issues are resolved before moving forward.

    ```json { "alt": "Screenshot of an online SEO analysis tool showing query traces and AI completion texts.", "caption": "Exploring SEO insights with this robust online tool: Analyze your queries effortlessly to optimize content strategy.", "description": "This image displays a screenshot of an SEO content analysis tool interface. It includes a list of query traces and AI-generated completion texts related to SEO content. The highlighted query involves analyzing a Google AI overview to extract implied questions from a search query about SEO. Essential for digital marketers, the tool aids in understanding and optimizing content structure for better search engine visibility. Keywords: SEO analysis, query traces, AI tool, content strategy." } ```

    Troubleshooting and Improvements

    My initial run revealed a lack of expected AI Overview detection—a misstep rectified through close inspection of terminal outputs, model adjustments, and informed re-execution.

    Embrace troubleshooting as a key growth component in the vibe coding journey, enhancing reliability and performance as you fine-tune system components.

    Dive Deeper: Inspiring Examples of Responsible Vibe Coding for SEO

    Logging and Output Management

    Employ Weave for maintaining organized records of query inputs and LLM outputs. This robust tool aids in both immediate log assessment and long-term query-trace reference.

    Use the analyze_query trace to monitor pivotal data points, fostering awareness of the direct connection between query intentions and AI Overview content insights.

    Structure Over Vibes: A Strategic Approach

    Across my years of vibe coding, I’ve learned structure creates reliability—increasing complexity demands methodical workflows, ensuring sustainable success. Remember to keep the vibes in your collaborations strong, united by a shared purpose and approach.

    Inspired by this post on Search Engine Land.

    crushpress.ai community screenshot
  • Agentic AI: Transforming PPC with Smart Automation

    Agentic AI: Transforming PPC with Smart Automation

    I’ve watched automation quietly transform PPC management over the years with rules, scripts, and API-driven workflows in Google Ads.

    Like many other marketers, I’m already very comfortable with automated bidding, data-driven optimization, and a suite of other AI-powered enhancements. But there’s a new shift on the horizon that’s set to redefine how we manage and optimize PPC campaigns.

    This time, I’m talking about AI agents and vibe coding. These innovations are ushering in a more autonomous mode of working where AI takes the lead in execution, allowing marketers like me to focus on strategy and creativity.

    This evolution promises unprecedented efficiency and flexibility, redefining effective PPC management.

    Agentic AI: Google Ads’ Game-Changing Feature

    In November 2025, Google rolled out its Agentic Ads Advisor, powered by advanced Gemini models. This tool helps advertisers like me uncover insights and boost campaign performance effortlessly.

    Google positions Ads Advisor as an AI partner that enhances campaign management by understanding business contexts, simplifying tasks, and learning from interactions to deliver better outcomes.

    However, the pressing question remains: What functionalities should an agentic AI tool embody?

    It should function as an autonomous agent, surfacing information as needed but also operating independently. It should identify opportunities for enhancing campaign setups, assets, ad copy, and more.

    An ideal agentic AI wouldn’t just make recommendations but also implement essential changes on its own.

    Integrating Agentic AI in PPC Workflows

    Agentic AI should ideally make decisions autonomously without needing constant human input, thereby managing, adjusting, and optimizing campaigns as they run.

    Beyond just advice or reporting, its real value lies in managing bidding, ad placements, and creative testing in real-time, based on live data, seasonality, and user behavior trends.

    With agentic AI handling more operational tasks, I can direct my efforts toward strategic decision-making.

    The competitive edge will increasingly rely on strategy rather than tools, focusing on marketing fundamentals like positioning, value propositions, and brand awareness.

    Read more: Agentic PPC: What Performance Marketing Could Look Like in 2030

    Why Agentic AI is Key for Advanced PPC Marketers

    Agentic AI appeals to experienced PPC marketers like myself because it scales campaigns without compromising strategic control, proving to be a true game-changer.

    With real-time optimization, data-driven creativity, and reduced human error, it redefines my role by allowing more time for strategy rather than execution.

    Despite its capabilities, informed oversight is essential to ensure alignment with broader marketing objectives, highlighting the need for ongoing professional engagement.

    Agentic AI isn’t replacing PPC professionals. Instead, it extends our capabilities, reduces manual effort, and facilitates better outcomes with minimal friction.

    Vibe Coding: Creating Your Marketing Toolbox

    In tandem with agentic AI, vibe coding is redefining how I work with AI-powered platforms, allowing me to create personalized, intuitive marketing tools and campaigns.

    Tools like Cursor and AI Studio have enabled me to articulate and realize specific needs seamlessly, even without being a developer.

    Incorporating vibe coding led me to build an SEO schema markup generator, an SEO audit tool, and a marketing idea generator, proving its practical value in my professional life.

    The possibilities expand when combining vibe coding with agentic AI, empowering marketers to engineer their AI agents tailored for PPC work.

    With this combination, I integrated these tools effectively within my marketing workflows, enhancing performance and strategy development at scale.

    Explore further: How Vibe Coding is Changing Search Marketing Workflows

    The Future: Navigating PPC with Agentic AI and Vibe Coding

    Agentic AI and vibe coding present immense opportunities to streamline PPC operations, enhance performance, and maintain competitiveness in a fast-evolving landscape.

    The future is about leveraging these technologies for more autonomous, data-driven, and personalized marketing strategies that benefit both internal teams and customers alike.

    As a PPC professional, it is crucial to embrace these advancements, ensuring adaptability and continued relevance in an AI-powered future.

    Follow experts like Alfred Simon, Mike Rhodes, and Ales Sturala to see practical applications of these innovative technologies in real-world scenarios.

    Inspired by this post on Search Engine Land.

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  • Revamp Your Search Tactics: Discover Vibe Coding

    Revamp Your Search Tactics: Discover Vibe Coding

    In a world where Google’s AI Overviews address more queries instantly, I’ve found that vibe coding allows us to craft interactive experiences that AI simply can’t replace.

    I’ve noticed that search marketers are now shifting their roles from merely optimizing to actually building. Tools like vibe coding, coupled with AI-powered development technologies, have significantly reduced the time from idea conception to execution—from weeks to just a few hours.

    These tools don’t make developers obsolete, but they empower search teams to test and create interactive content on their own timelines. This is crucial, as Google’s AI Overviews increasingly pull answers directly into the SERP, reducing clicks to our brand websites.

    For marketers, building unique, conversion-focused tools is becoming an indispensable tactic in this zero-click environment.

    ```json { "alt": "Tweet by Andrej Karpathy discussing a coding style called 'vibe coding' using AI tools.", "caption": "Andrej Karpathy humorously describes 'vibe coding' with AI, embracing automation for coding tasks while building projects with ease.", "description": "This image shows a tweet by Andrej Karpathy discussing a new coding style he calls 'vibe coding,' where he utilizes advanced AI tools like LLMs and SuperWhisper to automate coding processes. He explains the casual approach to coding by accepting AI-generated suggestions without detailed review, finding it amusing for casual projects. The tweet has garnered significant engagement with over 5 million views, highlighting interest in AI-driven coding solutions." } ```

    What is vibe coding?

    Vibe coding is about creating software by guiding AI with natural language instead of traditional coding methods. This means focusing on the tool’s purpose, appearance, and response, while AI takes care of implementation.

    This term gained popularity in early 2025, thanks to OpenAI co-founder Andrej Karpathy, who described it as a loose, exploratory building style. The appeal? Speed. The risk? Potential shortcuts that could lead to fragile systems.

    ```json { "alt": "Infographic on search marketing and vibe coding, highlighting problems, solutions, cost impact, and critical factors.", "caption": "Discover how vibe coding revolutionizes search marketing by transforming niche tools into necessities while slashing development time and costs.", "description": "This infographic provides a guide to vibe coding in search marketing, addressing the 'zero-click' issue posed by AI overviews on Google. It illustrates how natural language can be used to prompt AI platforms for interactive content creation, reducing development time from weeks to hours. Cost and security implications are also discussed, with examples of drastic cost reduction from $55,000 to $20/month. The infographic emphasizes the importance of selecting the right coding platform for different experience levels and aims to empower users to become indispensable partners." } ```

    Today, AI-powered development platforms extend this approach to non-engineering teams, with tools like Replit and Lovable, allowing everyone to build and iterate quickly.

    Vibe coding vs. vibe marketing

    It’s important to distinguish vibe coding from vibe marketing. Vibe coding involves AI tools designed to create applications and interactive experiences, whereas vibe marketing uses automation platforms to connect existing tools and systems.

    ```json { "alt": "Flowchart from a patent publication showing a system for generating synthetic search queries using various engines and classifiers.", "caption": "Explore the intricate flowchart from a patent, outlining a sophisticated system for generating synthetic search queries, incorporating multiple engines and classifiers.", "description": "This detailed flowchart is from a patent application publication dated August 29, 2024. It illustrates an advanced system for generating synthetic search queries. Key components include Context Engine 113, Search System(s) 160, LLM Selection Engine 132, and a variety of LLMs (Large Language Models) such as Creative Text and Ambient Generative LLMs. Classifiers and user state signals are integral, facilitating complex query processing and output generation for enhanced user engagement. This diagram is crucial for understanding the functionality and interconnections of system components in synthetic query generation." } ```

    Together, these approaches empower search teams to build and operationalize their creations efficiently.

    Why vibe coding matters for search marketing

    I believe that soon, AI-powered coding will be an essential part of any marketer’s toolkit. It allows us to create sophisticated interactive tools that Google’s AI can hardly mimic, enhancing our SEO and PPC strategies.

    ```json { "alt": "Growth forecasting dashboard displaying forecast inputs, expenses, and executive summary with revenue and ROI details.", "caption": "Explore your business's future with this growth forecasting dashboard. Discover revenue trends, profit margins, and client growth insights powered by AI.", "description": "This image shows a growth forecasting dashboard designed for SEO and AI optimization. On the left, it features forecast inputs including timeframe, client churn, and salary increase. The right side displays an executive summary with total revenue of $18.83M, a total profit of $9.73M, and an average ROI of 96%. It provides AI-powered insights for questions like break-even points and profit margins. Additional options for scenario management and data export are available, enhancing decision-making processes." } ```

    With vibe coding, my team can rapidly develop tools that boost conversion, like interactive content aimed to improve user engagement—a factor crucial for both SEO and PPC efforts.

    Through vibe coding, I’ve created custom systems that help manage our operational needs efficiently, saving time and costs. For instance, a project quoted at $55,000 was completed in under a week using Replit for just $20 a month.

    The opportunity to teach these skills to clients also adds significant value, emphasizing the transition from “we’ll do it for you” to “we’ll build it with you.”

    ```json { "alt": "Comparison chart of five AI development tools, listing experience level, pros, and cons.", "caption": "Explore the strengths and weaknesses of top AI development tools like Google AI Studio and Replit, tailored for various experience levels.", "description": "This image is a detailed comparison chart of AI development tools, including Google AI Studio, Lovable, Figma Make, Replit, and Cursor. Each tool is paired with a recommended experience level, such as beginner, intermediate, or advanced. Pros include seamless integration and ease of use, while cons highlight limitations like ecosystem lock-in and steep learning curves. Ideal for developers seeking the right fit for their AI projects." } ```

    Vibe coding offers a competitive edge, allowing us to navigate zero-click search environments while fortifying long-term relationships with our clients.

    Top vibe coding platforms for search marketers

    Several leading vibe coding platforms are making waves. My personal preference is Replit for its flexibility, though Figma Make is a great choice too, particularly as it integrates well with our existing workflows.

    ```json { "alt": "AI Adoption ROI Calculator interface for accounting firms.", "caption": "Discover the potential ROI from AI in your accounting firm with our intuitive calculator. Input your firm's data and explore the benefits.", "description": "The AI Adoption ROI Calculator interface allows accounting firms to estimate return on investment from implementing AI solutions. Users enter firm details such as number of employees, hourly rate, repetitive tasks hours, automation percentage, billable hours, and annual tool costs. The tool provides a user-friendly experience to calculate potential savings and efficiencies. Keywords: ROI calculator, AI adoption, accounting, automation, investment." } ```

    Testing different platforms will help find the best fit. Whether it’s Lovable for beginners or Cursor for advanced users, there’s a solution tailored to your needs.

    Practical SEO and PPC applications: What you can build today

    Vibe coding can create a variety of tools, from lead generation calculators to interactive content that increases website engagement. The key is to build tools that fill existing gaps, providing unique and useful solutions.

    ```json { "alt": "AI ROI Calculator for Accounting Firms highlighting AI use cases for data processing, compliance, client management, and financial analysis.", "caption": "Explore the AI ROI Calculator for accounting firms, which demonstrates how automation can save time and enhance efficiency across various accounting functions.", "description": "This image showcases an AI ROI Calculator for Accounting Firms, designed to assess the financial benefits of AI integration in accounting. It lists high-impact AI use cases divided into categories such as Data Processing, Compliance & Tax Work, Client Communication, and Financial Analysis. Key features include bank reconciliation, tax return validation, automated client query responses, and trend analysis. This tool aims to help firms quantify potential savings and efficiency improvements through AI automation." } ```

    For instance, I developed an AI-powered accounting ROI calculator, a tool that couldn’t be easily replaced by Google’s direct answers. This not only helps the target audience but also boosts SEO efforts by encouraging repeat visits.

    A 7-step vibe coding process for search marketers

    I’ve found that following a structured workflow is crucial when using vibe coding. This includes thorough research, creating a content spec document, and iterating designs before functionality.

    ```json { "alt": "Financial charts showing ROI timeline, time allocation, and benefits breakdown after AI implementation.", "caption": "Discover the impact of AI on ROI with detailed charts showcasing time savings, cost reductions, and revenue growth over the first year.", "description": "The image features a series of financial charts analyzing ROI and benefits after AI implementation over the first year. The top chart displays an ROI timeline, indicating cumulative benefit, investment cost, and net position, with a break-even point at month one. Below, a pie chart illustrates weekly time allocation, showing 85% time saved and 15% remaining. A bar chart details annual benefits with a comparison of cost savings and revenue growth. Keywords: ROI, AI implementation, financial analysis, cost savings, revenue growth." } ```

    These steps ensure a comprehensive approach, allowing for prompt testing and deployment. Updating documentation at each milestone helps in managing future updates or revisions.

    The dark side of vibe coding and important watchouts

    While powerful, vibe coding tools come with risks. Security and compliance issues, price creep, and technical debt are concerns that require careful attention.

    ```json { "alt": "Screenshot of a chat exchange explaining a setup issue with list submission.", "caption": "In this chat exchange, a user queries a setup error, prompting a detailed explanation and fix to ensure proper list submission functionality.", "description": "This screenshot captures a chat where a user questions why a setup was done differently than expected. The respondent explains the situation, detailing that while list submission triggered the flow correctly, pairing data was sent as event properties, not accessible in list-triggered flows. To fix this, pairing data will be sent as profile properties instead. This exchange highlights a technical issue and the proposed solution, keywords: setup, list submission, event properties, profile properties." } ```

    Always ensure security reviews and keep track of costs as projects evolve. Monitoring these risks can make vibe coding a reliable tool rather than a complicated headache.

    Vibe coding is your competitive edge

    In this evolving landscape, vibe coding gives us the ability to build unique digital experiences. It’s a skill set that empowers us to thrive, helping create meaningful, interactive content that stands out in the crowded search environment.

    Embracing vibe coding not only promotes strong client partnerships but also equips us to adapt to new search realities, making it a pivotal skill for future success.

    Inspired by this post on Search Engine Land.

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