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Forbes
12 hours ago
- Business
- Forbes
AI Coding Agents: Driving The Next Evolution In Software Development
Vikas Mendhe is a solution architect and digital transformation expert specializing in API-driven solutions in financial technology. As artificial intelligence continues to reshape industries, one of the most significant innovations in the software world is the rise of coding agents. They are reshaping how code is written, tested and maintained, marking a new era in software development. What Are Coding Agents? Coding agents are intelligent systems powered by large language models that write, debug and optimize code. They generate APIs, refactor legacy systems, write tests and even build apps with minimal input. Popular tools include GitHub Copilot, Amazon CodeWhisperer and Tabnine. New-generation assistants such as Cursor, Windsurf (recently acquired by OpenAI) and Cline focus on deeper IDE integration, context retention and developer autonomy. Industry Adoption The adoption of coding agents is gaining momentum across sectors. Tech companies are embedding coding assistants into their workflows, startups are exploring autonomous agents like AutoGPT and Devin for rapid prototyping and governments are integrating them cautiously for tasks like data transformation, compliance automation and internal tool development. While accuracy and oversight concerns remain, the shift toward AI-assisted development is well underway. Language-Specific Strengths Of Popular Coding Agents As coding agents continue to evolve, developers often look for tools that best support the languages they work in. • GitHub Copilot thrives in Python, JavaScript and TypeScript, with robust IDE integration. • Amazon CodeWhisperer specializes in Java, Python and JavaScript, featuring AWS-native tools and cloud focus. • Cursor excels in TypeScript and Python, with built-in memory and pair programming. • Tabnine supports Java, Python, C++ and Go with offline capability and customization. • Claude Code optimizes Shell, Python and Bash for terminal-based tasks. • Devin, a Python-based agent, enables complex, multi-step, end-to-end coding automation. Real-World Case Studies Let's just take a look at GitHub Copilot's applications in the real world. ANZ Bank's 2024 trial of GitHub Copilot showed engineers completing tasks 42% faster with improved code quality. Accenture's enterprise study found Copilot users coding 55% faster, with 90% reporting higher fulfillment. And a 2025 ZoomInfo case study involving over 400 developers reported a 33% code acceptance rate and 72% satisfaction. These findings show coding agents reduce repetitive work and free developers for higher-value tasks. Impact On Software Development Coding agents could transform software development from end to end. For developers, they act as smart copilots, automating repetitive tasks and simplifying complex workflows. Businesses gain faster delivery, lower costs and greater agility, turning ideas into prototypes in days instead of weeks. These tools also democratize development: Non-coders can build apps using natural language, and junior developers can produce better code with minimal oversight. Educational studies confirm this potential. AI code completion tools enhance student productivity and engagement while preserving problem-solving and conceptual learning. Programs such as the Stanford Institute for Human-Centered AI are exploring how such tools support computer science education at scale. Behind The Scenes Of Coding Agents Most coding agents are built on transformer-based LLMs such as OpenAI's Codex and GPT-4. Popular tools like GitHub Copilot and Amazon CodeWhisperer operate through IDE plugins, sending prompts to remote model APIs. GPT-4o mini supports a 128K token context window, enabling broader file-level reasoning. Claude 3.7 Sonnet offers 200K tokens for extended reasoning workflows. Gemini 1.5 Pro surpasses both with a 2M token context, ideal for workflows spanning entire codebases. More autonomous agents, such as AutoGPT and Devin, use frameworks like LangChain to chain prompts, memory and shell commands, completing multi-step engineering tasks with minimal human input. Terminal-Based Coding Agents In parallel, new terminal-based coding agents are emerging to support command-line workflows for professional developers. Tools like Claude Code, Codex CLI and Gemini CLI bring AI-powered development directly into the terminal environment, enabling agents to execute commands, write scripts and interact with live file systems, all while preserving developer autonomy. Coding Agents As A Service Despite advances, coding agents can still produce insecure or low-quality code. Safeguards like validation mechanisms and inline linting help, but human oversight remains essential. Rigorous testing, linting and code reviews should be part of every deployment pipeline. Code Quality, Security And The Role Of Supervision Despite advances, coding agents still generate insecure code and lack deep understanding of intent. Recent advancements have introduced better safeguards, validation mechanisms and inline linting. However, ongoing oversight remains essential. This underscores the need for rigorous testing, linting and human code review pipelines before production deployment. Getting Started With AI Coding Agents Before adopting AI coding agents, focus on clear, high-value use cases and choose tools suited to those needs instead of automating everything. Keep humans in the loop by ensuring AI-generated code undergoes rigorous testing, security scans and peer reviews. Research shows nearly half of developers don't fully trust AI output and often spend extra time debugging it. Be mindful of data privacy, intellectual property and licensing rules to avoid compliance issues, and set governance policies to prevent security blind spots and vendor lock-in. To mitigate common pitfalls—such as inaccurate code, scope creep, security risks and hidden costs—start with structured pilot programs that have measurable outcomes. Enterprise case studies show that successful rollouts often begin with controlled experiments, formal risk assessments and well-defined change management plans. Strong guardrails, clear policies and an ongoing review process help organizations capture productivity gains while maintaining quality and security. Conclusion Coding agents are not meant to replace human developers—they are tools that help make their work faster and easier. As more companies start using them, it's important to find the right mix between automation and human control. When used responsibly, coding agents can help teams work more efficiently, come up with new ideas and change the way software is built in the AI era. Everyone, not just developers, should understand what coding agents can and can't do, especially those shaping the future. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Time of India
24-07-2025
- Business
- Time of India
How automation is streamlining modern game development
The Indian mobile gaming industry has undergone an extreme makeover, powered by automation and advanced development tools. As India's gaming market surges—valued at $3 billion in 2024 and projected to reach $11 billion by 2033—studios are increasingly adopting automation to stay competitive, accelerate production cycles, and deliver richer player experiences. This shift mirrors a global trend, where automation, fuelled by AI and machine learning, is fundamentally reshaping every stage of game India, this growth is driven by affordable smartphones, widespread internet penetration, and a young, tech-savvy population. The demand for esports, casual games, and culturally localized content has created a fiercely competitive environment, making automation essential at every stage of the development process. Today, automation is more than just a tool for efficiency; it forms the backbone of modern game production, enabling studios of all sizes to push creative and technical boundaries at unprecedented speeds. One of the most profound impacts of automation is in content creation. AI-powered tools are helping developers generate intricate textures, 3D models, and even complete procedural environments far faster than traditional methods. Systems can dynamically adjust game difficulty, script non-player character (NPC) behaviors, and support rapid prototyping—crucial for Indian studios weaving local myths and cultural narratives into their games. By automating asset creation and iteration, developers can maintain cultural authenticity while meeting the increasingly tight timelines demanded by the market. Testing, traditionally one of the most time-consuming stages of game development, has been equally transformed. Automated testing protocols can now simulate thousands of gameplay scenarios in minutes, enabling faster and more comprehensive quality assurance. In India's mobile-first market—where smooth performance and seamless gameplay are non-negotiable—developers are embedding automated testing suites into continuous integration and delivery (CI/CD) pipelines, reducing time-to-market while improving stability and player satisfaction. Automation has also redefined the coding process itself. Tools like GitHub Copilot, Tabnine, Cursor, and Windsurf are widely adopted to automate repetitive tasks, suggest optimizations, and even detect bugs during development. This not only speeds up production but empowers smaller indie studios to compete with larger players, levelling the playing field and fueling the growth of India's vibrant indie gaming ecosystem. Unlocking creative potential through automation While automation accelerates development, its true value lies in freeing up creative bandwidth. Industry experts at Bengaluru GAFX 2025 noted that development timelines that once stretched six to nine months have been compressed to just two or three months. This faster iteration allows developers to experiment, pivot with market trends, and launch higher-quality games at speed—an invaluable advantage in India's fast-changing gaming landscape. Globally, automation is ushering in next-gen gaming innovations—real-time ray tracing, AI-driven upscaling, and generative AI for NPCs are now embedded in leading game engines. Indian studios are mirroring these trends by investing heavily in advanced graphics, AI analytics, and innovative monetization models like blockchain and play-to-earn mechanisms. Automation is also proving crucial in rapid localization efforts, enabling developers to efficiently customize content across India's diverse linguistic and cultural landscape, from vernacular language support to regionally themed experiences tied to Bollywood, cricket, and local influencers. Despite automation's sweeping influence, industry leaders agree: it is an enabler, not a replacement. Human creativity remains at the heart of great game design, storytelling, and player experience. Automation handles the heavy lifting, but the imagination, intuition, and craftsmanship of developers continue to define a game's success. As India continues to emerge as a global mobile gaming powerhouse, automation will be central to shaping the next decade of growth. With a booming indie sector, increasing investments, and a growing, demanding audience, the Indian gaming industry is not just keeping pace—it is poised to set new global standards. Automation is not merely streamlining workstreams; it is empowering a new generation of developers to reimagine what is possible in mobile gaming, both within India and across the world.
