Vibe Coding: What It Is and Why You Need It

As you probably already know, sitting around Googling solutions the old-fashioned way and then copying and pasting each line of code is becoming a thing of the past. The world of programming is in the midst of a major transformation. Instead of spending countless hours writing lines of code, you now have the ability to communicate your requirements in plain language, and the AI will generate your entire solution in a matter of seconds. The Stack Overflow Developer Survey shows that 44% of developers have already used AI to generate code at least once a week in 2024. That's nearly half!

Over a year and a half, I built a team of 47 people, launched four crypto products, and automated 73% of our processes — without hiring any full-time programmers. None. This was made possible by vibe coding. While it may sound like a buzzword, vibe coding is a legitimate method for building IT projects and launching businesses without traditional programming. You define what needs to be built; the AI handles the technical side. In this article I'll explain what vibe coding is, who vibecoders are, and why developing these skills will change the way you bring products to market — quickly, and without millions in funding.

Let's get started!

When you say, "I'd like an email-validated registration form," or "Set up an automatic Telegram broadcast whenever a new entry appears in the database," a solution arrives within minutes. That's the core idea: shifting focus from syntax to outcome.

With traditional programming, you detail every aspect of the solution — variables, conditions, error handling, debugging. Vibe coding works differently: you describe the desired outcome, the AI generates the code, and you oversee the result — refining your request as needed and running tests. The repetitive work of environment setup, library selection, and boilerplate is handled by the machine.

The Origins of the Terms "Vibe" and "Vibe Coding"

Vibe refers to the general mood, atmosphere, or impression — while coding is the process of writing instructions for a computer to execute. Together, they capture the essence of the method: the person sets the direction — the vibe — and the technology fills in the coding details.

In 2023–2024, vibe coding began appearing in real production workflows as large language models (LLMs) like GPT-4, Claude, and Gemini became capable enough to reliably generate code from plain text. The hashtag #vibecoding hit 140,000 views on Twitter within its first week, and over 300 repositories tagged "vibe-coding" appeared on GitHub within six months.

Who Uses Vibe Coding? Who Is a Vibecoder?

Vibe coding is useful for a wide range of people who want to move ideas into reality quickly and cheaply: startup founders who need to test a business hypothesis in a week rather than six months; marketers and analysts who want to automate data entry, CRM workflows, or reporting; small businesses without the budget for a programmer; and experienced developers who want to prototype faster or tackle non-standard challenges.

A vibecoder is someone skilled at communicating with AI clearly enough to get exactly what they need. They don't have to be expert programmers, but they do understand logic flows, APIs, HTTP requests, and how to chain services together into a workflow. A vibecoder focuses on the functional side of a project rather than the syntax. For example, when integrating Telegram with Google Sheets, a vibecoder simply needs to understand that a trigger is needed when a new message arrives, which sheet should receive the data, and what condition prevents duplicate entries.

Skills and Duties of a Vibecoder

Prompt engineering: The ability to describe a request accurately enough that AI fulfills it correctly on the first or second attempt — for example, specifying an HTML registration form with built-in validation.

Understanding automation structure: Knowing the four building blocks — triggers (what happened), logic (what should happen), tools (what's being used), and AI agents (what's analyzing or generating) — and how they fit together like a model kit.

Basic API and data format knowledge: Reading API documentation, configuring HTTP requests, processing JSON or XML.

Testing and debugging: Identifying and fixing errors, refining AI requests, and reviewing logs to confirm everything is running correctly.

In practice, a vibecoder handles task decomposition, tool selection, prompt writing, integration setup, testing, and documentation. At ASCN.AI, for example, vibecoders built crypto analytics automation: a token price move triggers an AI agent that processes on-chain data and sends a Telegram message with a summary and recommendations.

Where Is Vibe Coding Used?

• Marketing & Sales: Automated lead generation, competitor monitoring, A/B testing with dynamic creative rotation, AI-driven conversion analysis.
• Finance: AI-generated reports, budget tracking, cash flow forecasting.
• HR & Operations: Automated communication monitoring, reminders, AI-generated project reports.
• Crypto + Web3: Trading bots with on-chain analytics, whale monitoring, cross-exchange arbitrage.

ASCN.AI example, October 2024: During a crypto market flash crash, a vibecoding team built an automated response workflow in two hours. The trigger was a major price drop; an AI agent analyzed activity on both Ethereum and Solana and sent users alerts with arbitrage opportunities and projected returns of 5–40%. This would have been impossible to execute manually in that timeframe.

Vibe Coding Concepts

Vibe and Communicating Intent

Vibe coding is about transmitting the concept to AI and letting it figure out the specifics. You state the desired end result and the constraints, and the AI takes it from there. It's like asking an experienced employee to produce a report without explaining which buttons to press in Excel.

Classic Coding vs. Creative Problem-Solving

Classic programming requires knowledge of algorithms and syntax. Vibe coding shifts the focus toward creativity: instead of a developer writing every line of code, a marketer or analyst can design an automation, and the platform handles the technical implementation. This frees up time for strategy and new ideas.

Vibe Coding in Marketing and Communications

For marketing practitioners, vibe coding automates the collection, analysis, and application of marketing data through AI agents. Tasks like scraping websites, monitoring social media, and sending personalized email campaigns based on user behavior — previously requiring a developer — can now be built by marketers directly, in hours rather than weeks.

Vibe Coding Mechanics and Principles

Three core components: prompt engineering (how you describe the task), no-code platforms (visual automation builders), and language models (for code generation and data analysis). The process is straightforward: describe the desired result clearly → the AI generates the automation → test it → adjust → deploy.

The major advantage over traditional coding is speed. A traditional build-test-fix cycle can take days. With vibe coding, you can run 10–15 iterations in a single hour. A developer might debug one function in that same time.

Modularity is central to vibe coding. Instead of writing code line by line, you assemble pre-built blocks — nodes for HTTP requests, AI agents, messaging, data processing — like a construction kit. Complex tasks, such as sentiment analysis, are delegated to AI agents with carefully written prompts, and their structured output feeds into downstream processing.

Main Tools and Components

No-code platforms: ASCN.AI, Zapier, Make.com, n8n.

Language models: GPT-4, Claude, Gemini — for code generation and data analysis.

Integrations: Telegram API, Google Sheets, exchanges, CRMs — triggered automatically by new messages, webhooks, scheduled runs, or new entries.

Data storage: Databases and vector stores that give AI agents the context they need to provide relevant responses.

Logic and triggers: Conditions, filters, loops, and routing that define when and how automation runs.

Data tools: Actions for creating, reading, updating, and deleting data via API calls and formatting operations.

AI agents: Language models that perform complex analysis or generate structured output.

Prototypes

Prototype template sets are ready-made workflow starting points for fast deployment. ASCN.AI offers templates for Finance, Sales, Marketing, and Operations. Pick a template, plug in your data, and you're running within minutes — no workflow setup required.

snap2txt

snap2txt is a tool that compiles your project files into a single text context for AI. It immediately exposes structure, documentation, and relationships, which leads to more accurate and relevant AI recommendations. This saves significant time when working with large codebases.

The Technology Behind Vibe Coding

Vibe coding is powered by large language models (LLMs) — GPT-4, Claude 3, Gemini Pro — trained on trillions of tokens of text and code. These models can generate complete, working code based on the context of a given task.

ASCN.AI is developing specialised models for blockchain data — Ethereum and Solana — that outperform general-purpose AI for these domains due to the unique nature of on-chain systems. Vector databases (Pinecone, Weaviate, Supabase Vector) enable fast contextual search, making AI agent queries more relevant. Integrations are handled through APIs via HTTP requests or purpose-built nodes — Telegram Bot API, Google Sheets API, Binance, Bybit, and others.

How to Apply Vibe Coding in Practice

1. Define the automation task and break it into steps: trigger, data processing, result.
2. Choose a platform. Beginners should start with ASCN.AI or Zapier. Experienced users will find n8n more flexible and powerful.
3. Use existing templates (prototypes) and adapt them to your data and goals.
4. Test iteratively: check results, review logs, make adjustments.
5. Scale by adding automations to adjacent processes.

Successful Examples of Vibe Coding

Example 1: Profiting from a Crypto Flash Crash

On October 11, 2024, Bitcoin dropped 8% in one hour and most altcoins fell 15–30% in the same period. Users with vibe coding automations had price monitors and arbitrage models already running. When the spread exceeded 5%, trades opened automatically. Over two hours, users saw 240+ trades completed with returns of 12–40%. Manual trading could not replicate these results — human reaction time is simply too slow.

Example 2: Falcon Finance — $1,000 from 2 Prompts

Falcon Finance was a DeFi protocol with $47 million TVL. In March 2024, its token dropped 94% in 12 hours following a smart contract exploit. Our clients received an alert 20 minutes before any official news was published. An AI model was continuously tracking large holder transactions and monitoring Telegram and Twitter for anomalies — and flagged the risk in time to act.

Example 3: Finance Department Reporting Automation

One finance team was spending 8 hours a week compiling reports manually from 1C and Excel. A vibecoder built a workflow in 2 hours that exports data from 1C daily, calculates metrics, summarises them into text, and posts the report to Slack. The result: 32 hours saved per month — nearly $1,000 in labour at $30/hour. The platform costs $29/month. That's a return on investment of over 33x.

Skills That Remain Essential in Vibe Coding

1. Logical thinking: Breaking tasks into steps, structuring problems, thinking through edge cases.
2. Business process understanding: Identifying bottlenecks and knowing what's worth automating first.
3. Basic API knowledge: Reading documentation, configuring requests.
4. Testing and debugging: Analysing logs, identifying errors, adjusting requests.
5. Prompt engineering: Framing requests clearly enough to get high-quality AI output.

Advantages of Vibe Coding

• Automations can be assembled in hours, not weeks.
• No programming experience required — the learning curve is far gentler than traditional languages.
• Platforms cost a fraction of what a programmer does.
• You can modify logic yourself without waiting for a development team.
• Templates adapt easily to new tasks and contexts.

Possible Disadvantages and Risks

• Platform dependency: Risk of service outages or price increases.
• Customisation limits: Complex logic may still require actual code.
• AI errors: Models can make mistakes or produce hallucinations.
• Security: API keys and sensitive data need proper protection.
• Cloud performance: You don't have full control over uptime or latency in cloud-hosted services.

Is AI-generated code just "new spaghetti code"? It can be, if used without oversight. Treat AI-generated code as a draft: review it, refactor it, and add to it. With no-code solutions, you don't see the underlying code at all — the platform is responsible for its quality. And perfect code isn't always the goal, especially for internal automations.

Vibe Coding Will Change the Future of Programming

Vibe coding won't replace traditional programming — it will restructure it. Routine coding tasks will be automated, while programmers shift focus toward architecture, security, and complex algorithms. A new role will emerge: the vibe coding architect, who manages AI tools and designs hybrid systems.

The entry barrier to building in tech will drop significantly. After a month of learning vibe coding, you can ship your first working product. This democratises product development. Companies will hire fewer junior developers for routine tasks and more experienced architects with strong AI skills.

The pace of innovation will accelerate. Hypotheses will be tested in days instead of months. MVPs will be cheaper and faster to build. Products that were once too expensive or slow to develop are now within reach.

FAQ

What does vibe coding mean?

Vibe coding lets you build automations by describing what you want in plain language. AI translates that input into working code. "Vibe" refers to the concept or intent; "coding" refers to the method of creating the program.

What is the role of a vibecoder?

A vibecoder designs workflows using no-code platforms and AI agents. They decompose tasks, select tools, write prompts, configure integrations, and test automations — without writing a single line of code themselves.

How do you learn vibe coding?

Start by getting comfortable with a no-code platform like ASCN.AI. Learn the core concepts: trigger, node, variable, API, AI agents. Apply them to real tasks. Read API documentation for the services you want to use. Experiment with prompt phrasing. Participate in communities to share and learn from others' experience.

How do you start when you're not sure where to begin?

Pick something small and concrete — for example, sending a Telegram notification when a new row is added to a Google Sheet. Use available templates and tutorials. Mistakes are part of the process and easy to roll back in no-code environments. Ask questions in the community.

How do you avoid common vibe coding mistakes?

• Don't try to automate everything at once — build incrementally.
• Test each node independently before connecting them.
• Store secret keys securely and never expose them in prompts or logs.
• Implement error handling and logging from the start.
• Document your workflow logic for yourself and your team.

How do you improve as a vibecoder?

• Learn the APIs of popular services you use regularly.
• Practice prompt engineering on real-world tasks.
• Study and adapt workflows shared by others in the community.
• Follow updates to the no-code platforms you rely on.
• Keep solving problems from your own professional context.

Conclusion

Vibe coding represents a shift away from traditional programming toward natural language input combined with AI agents to create automated workflows. The craft of programming hasn't disappeared — but its shape has changed. Builders can now reach market in weeks, at a fraction of the cost. For a vibecoder, the essential skills are prompt engineering, understanding automation structure, basic API knowledge, and methodical testing. None of these require deep technical expertise to develop, but they do demand logical thinking and a solid grasp of the process you're automating.

Yes, there are risks — platform dependency, customisation limits, AI output quality, security concerns. These are manageable through careful platform selection, backup strategies, and where appropriate, self-hosted solutions.

Thousands of businesses are already using vibe coding for lead generation, market analysis, trading, and financial reporting. At ASCN.AI, we build at the intersection of crypto and AI — helping clients capitalise on arbitrage opportunities and flash crash scenarios.

Vibe coding gives you a real shot at building your own Google-scale solution in a specific niche. Start with something simple today and see how many repetitive tasks disappear from your life within a month. The moment to act is now.