Deepti Mittal
Blogger, tech speaker and in love with distributed systems. Also happen to work as Principal software engineer for one of the leading cyber security company Mimecast.
Bengaluru, India
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Deepti Mittal is a Principal Software Engineer at Mimecast with deep expertise in AI development, distributed systems, observability, scalability, and system architecture. Drawing on experience across healthcare, retail, and finance, she excels at building resilient, scalable solutions tailored to diverse business needs. Currently, they are exploring innovative ways to leverage Generative AI for enhancing everyday engineering and system resilience. A passionate technologist and blogger, Deepti Mittal is known for demystifying complex system internals and sharing practical insights. Their sessions blend technical depth with real-world lessons, empowering teams to build smarter, more scalable systems
From Brain in a Jar to API Factory: How AI Agents + MCP Are Changing application Development
What if AI could do more than just answer questions or generate code snippets? What if it could become an autonomous collaborator—one that understands your intent, orchestrates complex workflows, and manages the entire API lifecycle with minimal human intervention? Thanks to advances in new AI era where AI can act as a true partner in software engineering, transforming the way we build, deploy, and operate APIs in cloud-native environments.
Session Overview:
We’ll begin by easing into core concepts of AI Models, MCPs and Agents
By building this foundational knowledge, you’ll shift your perspective on AI—from a passive tool to an active, autonomous collaborator.
Live Demo: End-to-End Automation in Action
This session will introduce a new mental model for working with AI. Imagine moving from the DRY (Don’t Repeat Yourself) principle in code to DRY as a software engineer, where you automate not just code, but entire workflows and decision-making processes.
API Observability by Design, why I will not do in silos
In today's complex distributed systems landscape, observability isn't something you bolt on after deployment—it must be woven into your API design from the beginning. This practical, code-focused session will demonstrate how thoughtful API design decisions directly impact your ability to gain actionable insights when systems are in production. Drawing from real-world implementation experience, I'll walk through specific design patterns, instrumentation approaches, and architectural considerations that make APIs inherently more observable, enabling teams to troubleshoot faster, understand usage patterns better, and continuously optimize their services. You'll leave with concrete implementation strategies that transform observability from an operational afterthought to a fundamental design principle.
Agentic Automation with MCP: From User Story to Monitored API
As the Model Context Protocol (MCP) rapidly becomes a foundational standard for connecting large language models (LLMs) with real-world applications, developers are discovering new ways to harness agentic AI for end-to-end automation. This session will demonstrate how MCP empowers AI agents to securely orchestrate the entire API lifecycle—from requirements gathering and code generation to deployment, observability, and monitoring—using open standards and open-source tools.
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