SDLC 2.0 is not simply about adding AI tools to the software lifecycle—it is about rethinking how people, processes and technology work together. This session explores real-world challenges in adopting AI across the SDLC, including people adoption, technology limitations, client and infrastructure constraints, governance and leadership. Through practical implementation experiences and lessons learned, we will explore how organizations can move from AI experimentation and copilots toward agentic workflows, while maintaining human oversight, security, quality and measurable business outcomes.
Key Takeaways:
1. AI adoption is a people challenge before it becomes a technology challenge. Building trust, addressing resistance and enabling teams to work effectively with AI are critical to successful AI transformation.
2. Moving from an AI proof-of-concept to production is the real challenge. Security, data, infrastructure, integration, governance, cost and observability must be considered from the beginning.
3. Successful AI implementation requires redesigning processes, not simply automating existing tasks. Organizations need to identify the right SDLC activities where AI can deliver measurable value.
4. The shift to Agentic SDLC is a progression from AI-assisted tasks to AI agents collaborating across requirements, development, testing, deployment and monitoring—with appropriate human oversight and guardrails.
5. Leadership should focus on business outcomes rather than AI adoption for its own sake. Start with a real problem, measure the impact, build trust and scale what works.
- Date:22/08/2026
- Time:10:50
- Event:SDLC 2.0: The Agentic Shift @Chennai
