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How AI Is Redefining The Way Software Is Built In 2025

Igor Fedulov is CEO of Intersog.

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There is no denying that the software development landscape is evolving as AI-driven automation, intelligent coding tools, and machine learning algorithms redefine how developers approach designing, building, and deploying software solutions.

As we settle into 2025, it's clear that the future of software development is being shaped by trends that prioritize efficiency, intelligence and adaptability. And while adjusting to change isn't always easy, these shifts can be exciting as long as we remain adaptable and learn to overcome potential challenges.

A New Era For Software Development Practices

Over the past few years, software development practices have seen drastic changes. Tasks that were once considered mundane and time-consuming, such as coding and debugging, are now becoming more efficient thanks to advancements in tools and methodologies. Programming languages have evolved to deliver both higher quality and greater speed, streamlining workflows and enabling developers to tackle complex problems more effectively.

Speed and movement have become bigger priorities, especially as businesses start to expect more rapid turnaround times for product development. Not only is this shift driving innovation, but it's also reducing costs.

The AI Revolution

Artificial intelligence (AI) has emerged as a game-changer in the software development process. In the past, AI was often viewed as more of a novelty or research tool, especially as ChatGPT went mainstream. However, more advanced breakthroughs have redefined what's possible, demonstrating AI's capacity to understand and communicate with humans in meaningful ways.

AI now plays an important role in almost every step of development, from coding and testing to deployment and maintenance. For example, AI-powered tools can proofread contracts, analyze complex datasets, and even generate code snippets, allowing developers to focus on higher-value tasks.

Of course, AI adoption in software development hasn't been without challenges. Industries such as fintech, which rely on strict regulatory compliance, have been hesitant to embrace AI due to concerns over accuracy and reliability.

But trust in AI is growing, and these barriers are starting to break down. This is opening the door for widespread adoption as AI continues to advance and become less of an enigma and more of a vital tool.

Overcoming Challenges

One of the greatest challenges with AI in software development is adoption. New technologies often face resistance as teams weigh the risks of change and the learning curves associated with unknown tools.

However, it's clear that the opportunities far outweigh the challenges. AI offers the ability to process and analyze vast amounts of data, automate repetitive tasks and improve decision-making, all of which enhance productivity and innovation.

For businesses, the key to overcoming these potential challenges is simply fostering a culture of continuous learning and adaptability. By embracing AI and other emerging technologies, development teams can future-proof themselves and stay competitive in such a quickly evolving industry.

Skills Developers Need To Stay Relevant

To thrive in this new era, software developers should cultivate a diverse skill set. Understanding how large language models (LLMs) work is no longer optional—it's essential, and not just from a consumer standpoint. Remember to stay focused on data analysis and statistics, as these skills are becoming increasingly important with the rise of AI and quantum computing.

Developers also need to stay up-to-date on trends in cloud-native development, scalable applications and emerging technologies such as voice and handwriting recognition. These innovations are poised to redefine how software products are built and consumed, and it's happening quickly.

Trends To Watch In 2025

By the end of 2025, several trends will likely define the way software products are developed:

1. Transformational technologies: Innovations like voice recognition, image processing and optical character recognition (OCR) are streamlining processes and improving accuracy.

2. Agent-based architectures: Companies are exploring more immersive and dynamic software solutions, allowing for greater customization and adaptability.

3. Cloud-native development: Businesses are moving away from traditional desktop applications in favor of cloud-first architectures that offer scalability and accessibility.

4. Security Innovations: As AI capabilities grow, so do concerns about misuse. Developers will need to implement robust security measures to address looming threats like voice cloning and data breaches.

The future of software development is being shaped by unprecedented technological advancements and evolving business needs. AI, cloud-native architectures and transformational technologies are not just trends—they are the foundation of how products will be built in the coming years.

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ChatGPT Operator: The 'iPhone' Of Agentic AI, If Done Right

The OpenAI ChatGPT logo is seen on a mobile phone in this photo illustration on 30 May, 2023 in ... [+] Warsaw, Poland. (Photo by Jaap Arriens/NurPhoto via Getty Images)

NurPhoto via Getty Images

ChatGPT Operator is here, and it's a significant development in making AI-driven task automation accessible to the general public. This tool offers consumers and businesses new ways to enhance efficiency and productivity. Operator is an AI agent capable of autonomously handling various web-based tasks, such as booking trips, purchasing supplies, and managing data entry. For consumers, Operator's value proposition is to help individuals focus on more enjoyable or productive tasks, leaving automatable ones to the tool. For enterprises, its value lies in enabling businesses to streamline operations and reallocate human resources toward more strategic activities.

ChatGPT Operator: Features, Potential, and Context

In the race for agentic AI dominance, ChatGPT core (without Operator) leads in the conversational, general-purpose category. ChatGPT can generate content, answer questions, search the web, organize data, provide tutoring, and so much more. However, the field of executive, task-specific agentic AI is an entirely different arena. The market is saturated with powerful open-source, task-specific AI agents that developers continually improve and deploy through platforms like Hugging Face and GitHub. Proprietary task-specific AI agents also leverage open-source models to accelerate development, further multiplying the options available.

In this competitive context, ChatGPT Operator seems to aim to position itself as a task-specific AI agent with household and small business utility, creating the potential for a major revolution in how AI integrates into daily life. Operator could very well become the AI agent of choice for society at large—a groundbreaking, "iPhone moment" for agentic AI.

Operator employs a model called the Computer-Using Agent (CUA), based on GPT-4o, to analyze screenshots and navigate websites using standard browser functions, such as a cursor and mouse. Users simply provide a task description (e.G., "Order groceries," "Book a flight"), and Operator executes the required steps. If it encounters obstacles, such as CAPTCHAs or password fields, it pauses to request user input, ensuring control remains in the user's hands.

According to OpenAI, Operator "will streamline tasks for users and bring the benefits of agents to companies that want innovative customer experiences and desire higher rates of conversion." Notably, because Operator does not run on the user's device, it holds strong appeal for general consumers who lack high-performance hardware or technical expertise.

Currently, Operator is available to ChatGPT Pro users in the United States as part of a research preview. This phased rollout allows OpenAI to gather feedback and refine the agent's capabilities before expanding access to a broader audience. The company plans to make Operator available to other paid users and integrate it directly into ChatGPT in the future.

Concerns and Criticisms

Despite its displayed capabilities, ChatGPT Operator presents challenges commonly associated with AI. OpenAI has released a "system card" outlining potential concerns. WIRE reports that among these concerns are the possibilities of Operator misinterpreting user instructions, straying from intended tasks, or being exploited by malicious actors. Yash Kumar, product and engineering lead for OpenAI's Computer Using Agent, notes, "It also poses an incredible amount of safety challenges […] Because your attack vector area and your risk vector area increase quite significantly."

Reliability is another concern. Reports suggest that Operator may occasionally "hallucinate," generating plausible but incorrect or nonsensical outputs. This raises questions about its dependability for tasks requiring high accuracy. Experts recommend that users approach the tool judiciously, carefully verifying its outputs.

Efficiency vs. Effort: The Promise and the Reality

For certain tasks, crafting specific instructions for Operator and monitoring its progress can feel more like creating a new task than actually saving time. For instance, asking Operator to look up a recipe online, order the necessary ingredients on Instacart, monitor the progress, log in, and check out might seem like an entirely new process that requires learning and constant supervision. I wonder what the final version of this tool will look like and whether it will truly save significant time. Perhaps it will simply come down to becoming familiar with the tool and finding more customized ways to use it. I also wonder if Operator could analyze order history—including items, frequency, and slight variations—and compile, for example, a weekly grocery order for the user to review and approve.

The Road Ahead

OpenAI's introduction of ChatGPT Operator marks a pivotal moment in the development of autonomous AI systems for the general public. By enabling AI to handle routine personal and professional tasks, Operator has the potential to transform various aspects of daily life.

However, as an executive AI agent, ChatGPT Operator may not only have access to sensitive data but also perform real-world actions, such as making purchases, spending money, or signing up for services. This raises concerns that go beyond privacy, as there is an additional risk of the tool acting on one's behalf without consent. If OpenAI's vision for Operator is to become an effective, efficient, and trusted "AI agent in your pocket," it still has a long way to go.

Still, the journey has begun—and the early signs are promising.

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