By: Mahesh Bondre, Director – Consulting | Digital Engineering LTIMindtree

In the ever-changing landscape of software development, Agile methodology remains a cornerstone for efficient project delivery. Integrating Gen AI into Agile practices can significantly enhance productivity, streamline processes, and unlock new levels of innovation, making it an indispensable asset for modern Agile teams.

Gen AI in Agile Delivery

Agile methodology has become the standard for software delivery. Gen AI plays a crucial role by automating repetitive tasks, freeing up Agile teams to focus on creative problem-solving and innovation. Here are some valuable tools of Gen AI for Agile projects:

• ChatGPT: It translates languages, generates creative content, and provides informative answers. It’s also useful for creating User Stories.
• aiXcoder: This tool generates code directly from natural language input at the method level and offers intelligent code completion.
• GitHub Copilot: Rapidly produces recurring code structures, streamlining efficiency and maintaining uniformity in your codebase.
• Midjourney: Visualizes realistic product prototypes by generating 3D models from text descriptions.
• TabNine: Enhances code clarity through code refactoring, making it more understandable and maintainable.

Additionally, some artificial intelligence/machine learning (AI/ML) tools support DevSecOps practices and boost Agile delivery in the following ways:

Important considerations

As you explore the integration of Gen AI in Agile framework, keep these points in mind:

• Nature of Gen AI: Gen AI is not a real-time search engine; it operates based on pre-existing data.
• Tool capabilities: Understand the purpose, strengths, and limitations of each gen AI tool.
• Prompt engineering: Effective prompt engineering is essential.
• Validation of AI-generated user stories: While gen AI can create user stories, it is crucial to validate and refine the content. Product Owners (POs) should also exercise caution to avoid including sensitive business-critical information or organizational intellectual property.
• Estimation with Gen AI tools: When using tools like Copilot, estimating story points or tasks becomes a challenge. Teams must evolve their estimation practices to accommodate AI-generated content.
• Impact on metrics: AI assistance affects key Agile metrics such as velocity and throughput. Teams need to monitor these changes and adjust their processes accordingly.
• Ownership of AI-introduced defects: When AI assists in code generation, determining responsibility for defects can be interesting. Who will own the bugs introduced by AI-generated code?
• Evolving roles and skills: As Gen AI becomes more integrated, even Scrum roles will evolve. Mastery in crafting prompts tailored to each tool’s purpose will become a valuable skill.
• Team collaboration: While Gen AI tools enhance productivity, they also impact team collaboration. The Agile principle of valuing “individuals and interactions over process and tools” is at stake.

Gen AI in Agile projects empower Agile teams to achieve faster time-to-market, better deliverables, and cost optimization. Embrace its marvels, but always wield it wisely.

LTIMindtree Gen AI Platform

Considering various aspects and concerns stated above, To solve the above business imperatives, LTIMindtree has developed a Gen AI platform, which is a unique AI-based collection of accelerators to boost agile delivery. This platform enables clients to build, manage, and consume Gen AI solutions responsibly. It is also part of the AWS marketplace, improving developer productivity and delivering Gen AI solutions through a mindful AI approach that prioritizes security, privacy, and sustainability. Here are some its key components:

• LTIMindtree AppScribe: A next-generation framework powered by Gen AI for accelerating phases across the software development lifecycle (SDLC) based on Agile practices. It is an end-to-end integrated platform with capabilities for feature to story points to code generation. It helps teams accelerate their program and project delivery timelines and bring about productivity efficiencies across personas.
• LTIMindtree Genie: A Gen AI-based cloud-native application development tool that reduces cloud-native application development time and cost. This tool uses large language models (LLMs) like AWS Bedrock and OpenAI to provide Gen AI capabilities.
• LTIMindtree Infinity AppLens: A tool for performing code-level analytics and identifying the complexity and cloud readiness of application portfolios. It conducts deep code analysis based on more than 200 built-in patterns for cloud compatibility and produces assessment reports on migration complexity, cloud-readiness, and resiliency. It also provides recommendations for transitioning from monolithic to microservices architectures and code remediations.

Conclusion

Gen AI in Agile projects promise significant benefits offering analytical and strategic advice through data feeds, and improving efficiency in tactical planning. However, there is a trade-off. We will miss the personal touch, emotional support, trust, compassion, and wisdom that human interactions bring to Agile processes. Embrace Gen AI’s capabilities but balance them with the human elements that drive successful Agile teams.

References

Understand the differences between AI, GenAI, and ML, Fusion Development, January 6, 2024: https://blogs.oracle.com/fusioninsider/post/understand-the-differences-between-ai-Gen AI-and-ml#:~:text=Gen AI%20refers%20to%20a%20specific,known%20as%20%E2%80%9Cprompts%E2%80%9D).

Top 30 Artificial Intelligence (AI) Tools List, Akash Pushkar, Intellipaat, May 15, 2024: https://intellipaat.com/blog/top-artificial-intelligence-tools/

Top 11 AI Tools for DevOps Teams in 2024, Agilemania, Mar 29th, 2024: https://agilemania.com/top-ai-tools-for-devops