Raghavan from IBM asserts that AI will create more software and change developer roles

Although artificial intelligence is capable of generating code at unprecedented speeds, the process of testing, verifying, and deploying it into a working environment remains a separate complex task. Engineering teams are increasingly using AI agents to write code, fix bugs, and create new features, but faster coding does not guarantee faster software delivery.

As code generation gains momentum, the volume of checks increases, testing slows down, and teams find it difficult to coordinate the growing amount of changes.

At the TechSparks 2026 conference, Tushar Matur, CEO of Forge Code, highlighted this issue in his session 'Anatomy of a Software Factory.' He explained how AI-focused engineering organizations can move beyond automating individual coding tasks and start creating systems that manage the entire Software Development Life Cycle (SDLC).

Matur noted that just because code generation has become easier and faster does not mean the overall SDLC will accelerate. He reminded that the traditional development approach focused on writing code efficiently, requiring teams to define requirements, prepare specifications, and design architecture to reduce the load on the implementation phase.

However, since AI takes on much of the coding work, bottlenecks shift to other areas. Matur described a situation where organizations face a huge number of pull requests awaiting review, longer testing cycles, and more errors than existing regression suites can detect.

He emphasized that solving the problem does not necessarily involve hiring more engineers or launching more AI agents. Additional staff can increase coordination costs, and adding agents without effective feedback mechanisms can lead to code that overwhelms the verification and testing systems.

'The reason for this is the lack of signal,' Matur explained, clarifying why simply connecting automated steps does not create an effective software factory.

Matur presented Forge Code as a software factory that coordinates AI agents throughout the development cycle. The process begins with sorting requests, creating specifications, and implementing features. Then, agents check the changes before they are deployed, with human engineers intervening when decisions or feedback are required.

The system also monitors in the working environment, using the gathered data to inform future tasks. This forms a feedback loop, allowing the factory to identify issues, improve its workflows, and generate new work based on the experience gained. During the presentation, Matur reported that Forge Code used about 100 agents in the background to work on features, compatibility, and bug detection.

He outlined six principles for building an effective software factory: autonomy, scalability, cost-effectiveness, measurability, self-improvement, and alignment with business goals. The last principle is particularly important.

The factory should not operate as a task of writing code for every request, but rather be aimed at achieving specific outcomes, such as increasing customer retention or meeting regulatory compliance. Teams can then prioritize features based on the value they bring. In this model, engineers spend less time managing each task and more time observing results, analyzing signals, and improving the system itself. Business leaders can also provide requests and priorities directly, allowing the factory to translate organizational goals into a development backlog.

Code writing speed is good, but creating better software is the real victory. For engineering teams, the key is transforming AI-driven speed into reliable products, measurable progress, and real business results.

Amid the growing use of automation, many large companies are investing in artificial intelligence and conducting staff reductions. Nevertheless, the company Anthropic is ready to offer 32.5 million rupees for text-writing related work. This is surprising because what a person does in an hour, AI can do in mere seconds.

Artificial intelligence can write an email in a few seconds or create a blog draft in minutes, helping companies produce content on a scale that previously required an entire team. Because of this, many authors are questioning the value of their work if machines start writing.

Despite the emergence of AI, Anthropic has opened a special vacancy. For this position, the company offers an annual salary ranging from $295,000 to $345,000 USD, which is equivalent to approximately 2.5 to 3.25 crore rupees. However, this position is not intended for ordinary writers. The candidate must have at least eight years of experience in executive communication, working with senior management.

A natural question arises: why would Anthropic pay such money if AI can perform the job? The answer lies in the fact that the employee in this position will work directly with the company's top management. They will be responsible for preparing messages to convey the company's position to the public at important moments and explaining complex issues in simple terms. This requires not only good writing skills but also the ability to think strategically and provide balanced answers when necessary.

This job goes beyond simply writing articles for websites or product descriptions. It requires a specialist capable of deeply analyzing problems, predicting the impact of a message on the audience, and helping leaders decide what and how to communicate.

Anthropic is not the only AI company offering high salaries to writing and communications specialists. In September 2025, OpenAI also announced a vacancy related to content strategy, with an annual package of around $400,000. The employee in this role was tasked with improving the brand awareness of ChatGPT, creating content, and collaborating with engineers and designers.

However, this does not mean that salaries in the writing field are rising everywhere. It only indicates that some AI companies value experienced specialists who possess strategic planning skills, an understanding of people's needs, and the ability to simplify complex topics, in addition to good writing.

There is another side to the coin. In June 2023, one content writer reported that after the appearance of ChatGPT, some of his clients stopped commissioning him work. He specialized in writing content for websites and product descriptions, which can now be quickly created using AI tools, intensifying pressure on such tasks.

Thus, on one hand, experienced communications specialists are offered high-paying positions, while on the other hand, some freelancers involved in general content find it harder to find work. However, this does not mean that all entry-level writing positions are disappearing or that any senior author's job is guaranteed protection. The influence of AI depends on the type of work performed and the client's willingness to pay for it.

The author's task is not only to create content but also to verify the accuracy of information, identify missing details, and assess the material's suitability for readers. A report for September 2025 mentioned work related to correcting errors and improving AI-generated content.

This shows that humans may still be needed to check and refine AI-generated drafts. However, it cannot be assumed that the professions of editor and fact-checker are completely safe, as AI tools can assist in these tasks as well. Consequently, it becomes critically important for authors not only to write drafts but also to find errors, confirm information, and add necessary context.

The Anthropic vacancy is not suitable for all authors, as it is a high-level position requiring many years of experience. Therefore, it cannot be concluded that everyone can earn such a salary in the writing field. For those aiming to build a career in journalism, copywriting, or corporate communications, not only good writing skills but also research abilities, fact-checking, subject matter understanding, and critical thinking are important. Mastering the proper use of AI tools may also prove useful.

Authors who can use AI to speed up their work while simultaneously verifying information, performing quality editing, and applying their own original thinking will be able to adapt to the changing work environment.