01
AI-Assisted SDLC: The Changing Practice of Software Engineering
The question: When AI can generate code, what remains the engineer's responsibility?
Takeaway: An AI-assisted development review checklist.
For colleges, placement cells & coding clubs
Seminars that teach something, even if nobody enrols.
Each 60-minute talk stands alone, is built around one real question, includes audience participation and leaves attendees with a practical takeaway. Any programme mention is optional and agreed with the host in advance.
02
Evolving Software Roles: Understanding Job Descriptions and Hiring Signals
The question: How should a candidate interpret a role asking for backend, cloud, AI and product understanding?
Takeaway: A requirement → capability → evidence map for your résumé.
03
AI Engineering as a Career: Roles, Prerequisites and Entry Pathways
The question: What does an AI engineer do, and how can someone with my background enter the field?
Takeaway: A role-and-skills map and an honest next-step recommendation.
04
From Academic Projects to Production Software: Defining Job Readiness
The question: What separates a completed project from evidence that someone can contribute to an engineering team?
Takeaway: A project-review scorecard.
05
Technical Interviews in the AI Era: Demonstrating Engineering Competence
The question: How can candidates show their own ability when AI can help produce polished code?
Takeaway: A project-defence framework.
06
Agentic AI in Practice: Autonomy, Reliability and Responsible Engineering
The question: What must be established before an AI system is allowed to act?
Takeaway: A framework for deciding when an agent is justified and how to constrain it.