AI in software development Archives - Creospan https://creospan.com/tag/ai-in-software-development/ Digital Transformation Consultancy Fri, 19 Jun 2026 17:14:27 +0000 en-US hourly 1 https://wordpress.org/?v=7.0 The Era of the “Disposable App” : How AI is Flipping the Economics of Software  https://creospan.com/the-era-of-the-disposable-app-how-ai-is-flipping-the-economics-of-software/ Fri, 19 Jun 2026 17:14:26 +0000 https://creospan.com/?p=1529 The traditional lifecycle of software development—planning, architecting, securing, and scaling—is designed for permanence. We build software to last for years, which justifies the high cost of development and the rigid controls of the modern enterprise.  But what happens when the development cost drops to nearly zero? We enter the era of Throwaway Software.  The Catalyst: Presentation Pulse  The concept is best…

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]]> The traditional lifecycle of software development—planning, architecting, securing, and scaling—is designed for permanence. We build software to last for years, which justifies the high cost of development and the rigid controls of the modern enterprise. 

But what happens when the development cost drops to nearly zero? We enter the era of Throwaway Software. 

The Catalyst: Presentation Pulse 

The concept is best illustrated by a real-world “impossible” deadline. Imagine a high-stakes medical conference where doctors are competing for a trip to Europe. The judging needs to be instant, but the only available tool is paper. Usually, a custom digital solution would be deemed “too expensive” or “not worth the time” for a single-day event. 

I used this as an experiment to see how AI could bridge that gap. By using AI to generate high-fidelity HTML/CSS mocks for immediate feedback, and then using those mocks as the “requirements” for an AI agent, the development cycle vanished. 

This wasn’t a “proof of concept”—it was a production reality. Within 6 hours, I had a mobile-responsive, fully tested application named Presentation Pulse live on its own domain with an SSL certificate. Total cost outside of my time? Roughly $20. The app worked perfectly, handled the live scoring without a hitch, and was deleted the next day. It served its purpose and then it was gone. 

The Shift in Economics 

The success of this experiment solidified a new reality for me: AI has changed the economics of development so deeply that we should now be building software for tasks we previously did manually. 

The Old Paradigm: Traditional Development 

In the traditional world, we build for permanence. This approach makes sense for “forever” software, but it kills the possibility of quick solutions: 

  • Philosophy: Build to last 5+ years. 
  • Approach: If a custom tool is too expensive, we default to manual labor (paper, Excel, or extra man-hours). Software reserved for complex and permanent processes. 
  • Complexity: Built with custom design, microservices, events, complex gateways, and siloed hosting to ensure infinite scalability. 
  • Cost: Tens of thousands of dollars in man-hours and months of lead time. 

The New Paradigm: AI-Enabled Disposable Software 

With AI, we can now focus on “utility” in addition to “longevity”. If the cost of development is negligible, the “throwaway” app becomes the most efficient choice: 

  • Philosophy: Build to solve a problem for 5 hours or 5 days. 
  • Approach: Purpose-build an application for a single data migration, a specific event, or a unique task automation. 
  • Complexity: Embraces “good enough” monolithic architecture—like serving a React app directly from Java—to prioritize speed over theoretical scale. 
  • Cost: The price of a domain name, a few dollars in hosting, and a single afternoon of work. 

The Bottleneck: The “Enterprise Tax” 

The biggest hurdle to this revolution isn’t the AI—it’s the infrastructure. Most companies have taken the “cheap and quick” promise of the cloud and layered it with internal controls designed for $500,000 projects. If you want to deploy a small utility app, you’re often met with: 

  • App registration and setup to enable hosting and source control 
  • Mandatory CI/CD pipeline configurations. 
  • Separate front-end/back-end hosting requirements. 
  • Strict gateway and whitelisting procedures. 

For a permanent enterprise tool, these are vital safeguards. For a 20-user app that will be deleted in 48 hours, these procedures are the “death of the possible.” To make Presentation Pulse feasible, I hosted the static React application directly from the Java backend—a technical “no-no” in many rigid dev shops, but a masterstroke for speed and simplicity. 

Redefining Software Strategy 

If your organization cannot deploy a “throwaway” app in under an afternoon, you are missing out on a massive productivity gain. 

We need to create a space where AI-generated, one-time-use tools can live without triggering the full weight of standard production controls. 

The takeaway: AI has solved the software writing problem. Now, it’s time for leadership to solve the software hosting problem. If we don’t change our procedures, we will continue to use paper for tasks that a $20 app could have solved in a few hours. 

Written by Norm Murrin

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]]> AI Agents – The Future of Workforce https://creospan.com/ai-agents-the-future-of-workforce/ Mon, 19 Aug 2024 22:06:58 +0000 https://creospan.com/?p=1197 The post AI Agents – The Future of Workforce appeared first on Creospan.

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I am sure you can relate to preparing sheets of information about the number of employees in your team, and how the budget is allocated through projects/tasks in your current or previous roles. It is not far you will have to add another dimension to it, how many of them are human and how many are non-human (AI Agents).

AI agents leverage large language models like GPT etc. to understand goals, generate tasks, and go on completing them. We can deploy them to automate work and outsource complex cognitive tasks, creating a team of robotic coworkers.

This field is evolving faster than ever, especially on the software side, with new AI models and agent frameworks increasingly becoming better and more reliable. Even the no-code platforms are more powerful than couple of months back, so this is a right time to get your feet wet and run some experiments.

What are AI agents?

An AI agent can in itself act autonomously in an environment. Can take information from its surroundings, make effective decisions based on that data, and act to transform those circumstances—physical, digital, or mixed. More advanced systems can self-learn and improvise their behavior over time, constantly trying out for new solutions to a problem until the goal is achieved.

Components of an AI agent system

AI agents have different components that make up their software, each with its unique capabilities.

Sensors let the agent sense its surroundings to gather percepts (inputs from the realistic world: images, sounds, radio frequencies, etc.). These sensors can be cameras, microphones, or antennae, among other things. For software agents, it can be a web crawl function or a tool to read files.

Actuators help the agent work in the realistic world. These can be wheels, robotic arms, or a tool to create files in a computer. – Yes, you are thinking of Telsa FSD.

Processors, control systems, and decision-making mechanisms compose the “brain” of the agent. They process information from the sensors, brainstorm the best course of action, and issue commands to the actuators.

Learning and knowledge base systems store data that help the AI agent complete tasks; for example, a database of facts or past percepts, difficulties faced, and solutions captured.

AI Agents for Developers

Code Generation: AI can help generate code snippets based on the developer’s requirements or even create entire skeletons for applications.
Code Review: AI agents can review code to identify potential bugs, optimize performance, and ensure best practices are followed.
Debugging: They can analyze code to find errors and suggest possible fixes, reducing the time spent on troubleshooting.
Documentation: Automatically generate documentation for code, making it easier for developers to maintain and understand over time.
Learning Resources: Provide personalized recommendations for learning new technologies or improving existing skills.
Project Management: Integrate with project management tools to track progress, manage tasks, and ensure timely delivery.
Testing: Assist in writing and running automated tests to ensure code quality and reliability.
Version Control: Help manage version control by automating merges, handling conflicts, and tracking changes.

Examples of AI Agents for Developers

GitHub Copilot: An AI pair programmer that offers code suggestions in real-time.
Tabnine: AI code completion tool that supports various programming languages.
DeepCode: Analyzes code to identify errors and potential improvements.
Kite: Provides predictive code completions to speed up the coding process.

General-Purpose AI Agent Apps

Relevance AI: A no-code platform that allows you to build AI agents for business tasks like data processing and API calls.
Zapier: Connects your favorite apps and automates repetitive tasks with ease, offering over 6,000 app integrations.
Microsoft Power Automate: Enables you to automate workflows by connecting your apps and services.
Otter.ai: An AI-powered transcription service that can capture and share meeting notes with ease1.
Copilot X: Leverages GPT models to autonomously complete tasks by breaking them down into subtasks.

What’s In the News?

For the first time in your life, you would to be working with a CEO AI Agent, a Manager AI Agent, a Peer AI Agent.

Take this example: Think of Siri/Alexa asking you for an update and reminding you of pending tasks.

There is a real possibility that this time you might end up reporting to a non-human manager.

Recent news: “Salesforce CEO Marc Benioff said at the World Economic Forum in Davos that today’s cohort of CEOs will be the last to lead all-human workforces. The AI agents are here—and they’re taking over more work at the office.”

Source: https://fortune.com/2025/01/24/marc-benioff-salesforce-human-workforces-ai-agents/

Will AI Agents Take Our Jobs?

I cannot think of ending this article without this question answered. This technology will absolutely displace jobs and bring substantial change to the market in a very near future. Human workers may be replaced by AI agents in multiple industries. And also, more positions for AI development and maintenance would be created, along with human-in-the-loop positions, to ensure human decisions drive AI actions and not the other way around. That’s going to be game forward.

Article Written by Krishnam Raju Bhupathiraju.

 

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