Startup insights: 5 prompt engineering tips for achieving success in vibe coding.

      Startup wisdom is a fresh series from TNW that provides practical insights from professionals who have contributed to the success of prominent companies. This week, Dainius Kavoliūnas, the leader of the no-code platform Hostinger Horizons, shares his advice on vibe coding.

      Vibe coding has emerged as a vital resource, particularly for entrepreneurial thinkers developing applications and platforms that address everyday challenges, optimize business operations, or improve digital experiences. It signifies a transformative approach in software development. Rather than writing lines of code, users can now articulate their needs and let AI bring those ideas to fruition. Vibe coding is quick, intuitive, and opens up new possibilities where code is not just functional but also expressive, connecting human concepts with machine capabilities.

      However, like any new tool, achieving positive outcomes requires some practice. Drawing on insights from the Hostinger Horizons team and its users, here are five practical methods to interact with AI more effectively.

      1. Keep prompts concise and specific

      While vibe coding may appear spontaneous and flexible, adhering to fundamental guidelines for effective communication with AI is beneficial. My top advice for prompt engineering is brevity. Short, clear, and specific prompts consistently yield superior results compared to ambiguous or broad instructions, and being overly general is one of the most common beginner errors.

      For example, a vague command like “Build a website” may yield generic results, while a more specific prompt such as “Create a one-page website for a freelance designer featuring sections for portfolio, services, and a contact form” produces a more relevant and customized outcome. Including layout details, feature specifications, and stylistic preferences enhances the quality of the output as well. Precision in prompting reduces ambiguity and limits extensive revisions later in the process.

      2. Divide prompts into smaller steps

      Being specific does not mean cramming all instructions into one command. Evidence shows that it’s more effective to break down development tasks into a series of smaller, related prompts rather than providing a single, complex request.

      This method allows the AI to concentrate on specific elements, resulting in cleaner code and minimizing logical mistakes. For instance, one prompt could focus on generating the layout for a landing page, while subsequent prompts might add design or functionality. This modular approach enhances maintainability and makes it easier to identify and address issues early on.

      3. Encourage AI to suggest improvements

      Optimal prompt engineering practices involve using AI not just as a passive output generator but as an active contributor in the development process. AI can take on the role of a creative collaborator beyond merely responding to direct commands.

      Requesting the AI to critique, optimize, or suggest alternative solutions can lead to discovering more efficient techniques or inspire new design approaches. For instance, you might ask the AI for suggestions on features, content, or sections.

      4. Test consistently

      A commonality between traditional coding and vibe coding is that promptly identifying and correcting errors can save significant time later and facilitate the development of functional applications more swiftly. Therefore, I recommend testing AI-generated projects early and often with realistic data or practical scenarios. This enables rapid feedback and ongoing refinement.

      When you ask AI to add a feature—such as sending an email notification to someone who fills out a contact form on your site—you should always verify that it functions as intended. Most often, the functionality will be implemented correctly, though you may still need to refine the user interface. Occasionally, the feature may fail entirely, necessitating clearer instructions or additional context for the AI to succeed.

      5. Retain human oversight

      Although AI speeds up development, human judgment remains crucial, particularly for addressing complex challenges, ensuring long-term maintainability, and assessing the quality of the final product. If the AI-generated output does not meet expectations, revising the prompt or approaching the issue from a different perspective often yields better results.

      It is also wise to keep copies of working versions before making major modifications. This creates a safety net and allows for experimentation without losing previous progress. Sometimes, a degree of technical knowledge may be required—consulting with an experienced developer can assist in resolving deeper architectural or logic-related issues.

      No team, no skills—no problem

      Feedback from Hostinger Horizons users indicates that these techniques—clear prompting, modular thinking, collaborative refinement, consistent testing, and human oversight—constitute the foundation of effective AI-assisted coding. As this field evolves, mastering prompt engineering will become a vital skill for anyone engaging with generative development tools.

      Consider the example of Prashant Maurya, a 20-year-old student. Lacking coding skills and relying solely on intuition supported by AI, he created a suite of tools under his X 247 Project, including an Ads Checker, QR Generator, and Shop Biller. Each tool took merely five to 15 days to develop at a fraction of the cost he would have incurred through traditional methods. Over 1,000 users have already utilized his tools, crafted simply by prompting AI.

      “As a student with no team, no budget, and just a vision to address real problems