Code with AI Archives - Creospan https://creospan.com/tag/code-with-ai/ Digital Transformation Consultancy Fri, 24 Apr 2026 15:39:33 +0000 en-US hourly 1 https://wordpress.org/?v=6.9.4 AI: Building the Engine, Not Just Greasing the Machine  https://creospan.com/ai-building-the-engine-not-just-greasing-the-machine/ Fri, 24 Apr 2026 15:39:31 +0000 https://creospan.com/?p=1485 It’s a common scene in the modern enterprise: developers are using AI to crush unit tests, designers are using it to generate assets, and QA is using it to write scripts. On paper, everyone is "using AI." But in reality, we are often just applying high-tech grease to an old-fashioned machine. We’ve optimized the silos, but we haven't touched the walls between them. 

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]]> It’s a common scene in the modern enterprise: developers are using AI to crush unit tests, designers are using it to generate assets, and QA is using it to write scripts. On paper, everyone is “using AI.” But in reality, we are often just applying high-tech grease to an old-fashioned machine. We’ve optimized the silos, but we haven’t touched the walls between them. 

I realized this after a side project forced me to change my own workflow. I was building an app for an organization and needed a way to bridge the gap between a vague idea and working software without the typical overhead. 

The “Back of the Napkin” Breakthrough 

Instead of writing a massive requirements document, I had Gemini generate mockups in HTML and CSS. I gave it a specific constraint: make it look like a “back of the napkin” sketch. 

The goal was psychological; I wanted the client to focus on the flow and the logic, not the hex codes or the padding. It worked brilliantly for the client, but the real magic happened when I moved to the build phase. I realized that these informal, “messy” screens weren’t just mockups—they were the ultimate requirements document. 

Because the AI had helped me build the visual logic, it already “understood” the intent of the application. I fed those screens back into the model, and it gleaned the functional requirements, data structures, and edge cases with startling accuracy. I had a working application in record time, moving straight from logic to final styling with almost zero back-and-forth. 

The Corporate Paradox: Efficiency vs. Disruption 

This experience highlighted a glaring issue in how many organizations approach AI. At work, we tend to respect the traditional boundaries of the SDLC. We hand off a document from one silo to the next, with each role using AI to speed up their specific slice of the pie. 

The premise is simple: Businesses are failing to capture the full value of AI because they are using it to perform tasks as currently defined, rather than using it to collapse the process itself. 

If you are just using AI to write code faster, you’re missing the point. The real value is unlocked when the lines between “Requirement,” “Design,” and “Code” blur into a single, continuous stream. 

Why Siloed AI is a Half-Measure 

When we keep AI trapped within existing roles: 

Context is lost in handoffs: The “intent” of a feature gets diluted as it moves from a PRD to a Figma file to a Jira ticket. 

The process remains linear: We are still waiting for “Step A” to finish before “Step B” starts, even though AI can often see the end result from the beginning. 

Innovation is incremental: We get 20% faster at doing things the old way, rather than 500% faster by doing things a new way. 

To realize the true potential of this technology, we have to be willing to be disruptive to the entire process. We shouldn’t be asking “How can AI help this developer?” but rather “How can AI change how we get from an idea to a product?” 

The “back of the napkin” approach taught me that the most valuable thing AI can do is remove the friction between thinking and building. If your organization is still treating AI as a personal assistant for individual roles, you aren’t leading an AI transformation—you’re just upgrading your word processors. 

Article Written By Norm Murrin

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]]> What is Vibe Coding? https://creospan.com/what-is-vibe-coding/ Fri, 14 Mar 2025 14:06:11 +0000 https://creospan.com/?p=1209 Vibe coding isn’t an official term. It’s more of a coding mindset. Vibe coding is a programming approach that leverages AI tools to create code based on natural language descriptions of desired functionality. In this method of developing code, we rely heavily on autocomplete, AI coding assistants like GitHub Copilot or ChatGPT or various AI Coding Editing tools, and use existing code examples, all while making decisions based on intuition rather than structured instruction.

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What is Vibe Coding?

Vibe coding isn’t an official term. It’s more of a coding mindset. Vibe coding is a programming approach that leverages AI tools to create code based on natural language descriptions of desired functionality. In this method of developing code, we rely heavily on autocomplete, AI coding assistants like GitHub Copilot or ChatGPT or various AI Coding Editing tools, and use existing code examples, all while making decisions based on intuition rather than structured instruction.

How it Works:

Instead of manually coding line by line, developers provide instructions to AI-powered coding platforms, which generate code blocks based on prompt inputs.

Examples of Vibe AI Coding Tools:

Platforms like Cursor, Bolt, and Claude exemplify vibe coding technology, assisting developers in the code-generation process.

I know some of you might already be using Copilot with VS Code which in itself is vibe coding, But you want to elevate your ability “You want a fully-featured IDE with AI capabilities built-in” or “You need flexibility in choosing AI models (GPT-4, Claude, etc.)” or “You prefer using your own API keys to control costs” you can try using any of the Vibe AI Coding tools, and you can start with one : https://www.cursor.com/

Role Transformation for Programmers:

Vibe coding alters the programmer’s role, emphasizing tasks like guiding, testing, and refining AI-generated source code rather than writing it manually.

A Creative Shift in the Programming Mindset

Vibe coding represents a larger cultural shift in how people approach software creation. It lowers the psychological barrier for beginners, prioritizes creativity over precision, and embraces of experimentation.

Vibe coding accelerates the AI transformation. When anyone can generate functional code through conversation/Prompt Engineering, the specialization that once protected technical roles evaporates. The implications ripple through organizations and everyone has an elevated role to play:

  1. For Product managers would not hide behind documents/wireframes — they would be generating working prototypes.
  2. For Designers can’t just hand off mockups — they’ll will have a role to implement their designs.
  3. For Marketers can’t request custom tools — they’ll be building their own analytics dashboards
  4. For Executives can’t survive technical ignorance — they’ll need to understand the systems they oversee.

The Build Vs Run/Maintenance Model

Vibe coding excels at build but struggles with Maintenance/Run. This creates a fundamental split:

  • Creation/Building New: Easy, accessible, new functionality.
  • Maintenance/Run: Complex, requiring deep business expertise, increasingly valuable.

Smart Innovative organizations will develop dual skillsets — rapid vibe coding for prototyping and proof-of-concepts, alongside rigorous engineering practices for enterprise grade systems.

Programming Evolution:
Vibe coding reflects programming’s evolution, with developers potentially transitioning into roles as “AI architects.”

Benefits:

This approach can speed up software development, give Iron man suite to existing developers, empower non-developers to create applications, and foster creativity without requiring deep coding expertise.

Concerns:

Developers must still understand underlying syntax and code, ensure quality, and address security issues, as these remain critical in AI-assisted coding.

Finding the Right Balance: Augmentation, Not Replacement

I would not suggest abandoning AI-assisted coding ship — that would be like rejecting power tools in favor of manual screwdriver. But we need to approach this revolution thoughtfully, preserving the craftsmanship while embracing innovation.

Article Written by Krishnam Raju Bhupathiraju.

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