MLDS speaker · 2026

Sachin Tripathi

Senior Manager, AI ResearchAIM

About Sachin Tripathi

Sachin Tripathi, is an eminent professional with over 8+ years of experience in the ever-evolving realms of AI and Machine Learning. As a revered mentor, Sachin has consistently raised the bar in education, empowering students and professionals through engaging and effective training programs. His expertise spans diverse domains, including programming languages, machine learning, artificial intelligence, big data analytics, and cybersecurity. Sachin’s exceptional ability to communicate complex concepts in an accessible and engaging manner sets him apart. Committed to staying at the forefront of industry trends, he remains dedicated to nurturing talent and advancing human knowledge. Sachin is a luminary in AI and machine learning, with a profound impact on education and professional development.

1 edition on the MLDS stage · 2 sessions on record

Sachin Tripathi, Senior Manager, AI Research, AIM

Talks at MLDS

Sessions from the MLDS agendas, newest first.

MLDS 2026
Bengaluru
26–27 Mar 2026
- Mar 27, 2026 · 10:30–12:30 · Hall 2 · Bengaluru
  Exclusive Workshops
  Protocol Wars: The battle for agent-to-agent interoperability
  Interoperability will define the future of agent ecosystems. This workshop unpacks the emerging standards—Model Context Protocol (MCP), Agent-to-Agent (A2A), and Agent Communication Protocol (ACP)—that allow agents to “speak” to each other. Through hands-on exercises, you’ll compare strengths, trade-offs, and real implementations. You’ll learn to build adaptable systems that can evolve with changing standards—future-proofing your AI stack for a multi-agent, protocol-driven world.
- Mar 26, 2026 · 10:30–12:30 · Hall 2 · Bengaluru
  Exclusive Workshops
  From Prototype to Production: Ship battle-tested agentic AI into the real world
  Learn how to take agentic applications from lab experiments to production-grade deployments using AWS Copilot. This workshop shows how to automate infrastructure provisioning, CI/CD pipelines, and integrate standards like the Model Context Protocol (MCP) to extend agents beyond chat into real-world tasks. By the end, you’ll know how to create resilient, scalable, and context-aware AI agents that can truly operate in enterprise environments, while freeing developers to focus on logic instead of infrastructure firefighting.
MLDS 2026 agenda MLDS 2026 talk recordings on YouTube (opens in a new tab)