1) Let’s start with you! Tell us a bit about yourself – your background, current role, and what excites you most in the world of tech.
I’m Lakshmi Sravya, a software engineer currently working at JPMorgan Chase. I’m deeply fascinated by the intersection of AI and databases, and I spend my time exploring how generative AI can optimize PostgreSQL queries and performance. I enjoy diving into PostgreSQL’s internals, experimenting with features like logical replication and foreign data wrappers (FDW), and solving complex problems that push the boundaries of database performance and reliability. What excites me most is building smarter, more efficient systems that combine AI’s intelligence with PostgreSQL’s powerful data processing capabilities.
2) Why PostgreSQL? What inspired you to explore or switch to PostgreSQL?
My PostgreSQL journey began at Amazon, where I first encountered it. The depth and flexibility of PostgreSQL fascinated me, and I was fortunate to have mentors and subject matter experts who patiently guided me through both the basics and advanced concepts. This solid foundation sparked my passion for PostgreSQL and its ecosystem.
3) What are you working on with PostgreSQL right now? Share the cool stuff you’re building, learning, or solving using PostgreSQL.
Currently, I am working on an open-source project focused on optimizing database queries using generative AI techniques. This is one of the most interesting problems in database engineering today-finding ways to embed the power of AI with PostgreSQL’s robust query processing to enhance performance and efficiency. Alongside this, I continue to explore and implement PostgreSQL features to solve complex data challenges.
4) What’s been your biggest learning or challenge on this journey?
A lesson, mistake, or an aha moment, we’d love to hear about it!
One of my proudest moments was when I helped my husband with his GeoDjango project, which had millions of records but suffered from high query latency. I introduced pg_partman to partition his huge database, drastically improving performance. That moment, along with many others where I helped clients solve critical, almost doomsday-level problems, reinforced my confidence in PostgreSQL’s power and my skills.
5) Your wisdom to rookies like yourself?
What’s one tip or piece of advice you’d give to someone just starting out with PostgreSQL?
Focus on mastering the fundamentals of SQL and relational databases first. Don’t hesitate to ask questions and learn from the community and mentors, they were invaluable to me. Explore PostgreSQL’s unique features like logical replication and foreign data wrappers (FDW), and use tools like EXPLAIN to understand query performance. Be patient with complex concepts like MVCC; once you understand it deeply, everything becomes much easier.
6) Finally, describe your PostgreSQL journey in one word.
Yep, just one!
Empowering- has given me the confidence, tools, and community support to tackle complex challenges and build impactful solutions.
7) Who or what has influenced your PostgreSQL learning the most?
A mentor, a community, a course, a project, tell us what or who helped you grow.
Recently, I participated in the Postgres Women India Upskill Program, where I had the opportunity to learn from many PostgreSQL experts. One person who has become my go-to mentor is Hari Sir, whose guidance and support have been instrumental in my growth. Along with the mentors I met at Amazon and the vibrant PostgreSQL community, these influences have greatly shaped my journey.
8) What’s one PostgreSQL concept or feature you finally understood and felt proud of?
That lightbulb moment when something clicked, we all have one!
The logical replication feature stands out for me. Understanding how PostgreSQL’s publish-subscribe model works to replicate data incrementally and in real-time was a game changer. I also admire FDW for its ability to connect and query across different data sources seamlessly. On the challenging side, MVCC was tough to grasp initially, but once I understood its inner workings, it unlocked a much deeper appreciation for PostgreSQL’s concurrency and transaction management.
Talk Title: PostgresML: Revolutionizing Machine Learning with SQL
In today’s data-driven world, organizations often struggle with complex machine learning infrastructures and data movement challenges. This talk introduces PostgresML, a game-changing PostgreSQL extension that brings machine learning capabilities directly into your database. We’ll explore how PostgresML enables developers and data teams to perform sophisticated ML operations using familiar SQL commands, eliminating the need for separate ML systems. Through live demonstrations, we’ll showcase practical implementations of model training, real-time predictions, and GPU acceleration features. Whether you’re a database engineer, ML practitioner, or technical lead, you’ll learn how to leverage PostgresML to simplify your ML pipeline, enhance security, and accelerate deployment. Join us to discover how this innovative tool is bridging the gap between traditional database operations and modern machine learning workflows.
Talk Title: Developers are decision-makers now. DevRel gets you there faster
DevRel as a role has existed since the 1990s, yet it remains one of the least understood roles in tech. Whether due to changing definitions, role titles, or evolving industries, DevRel has transformed significantly over the past few years—yet it continues to shape the devtool landscape. Since 2023, we’ve seen explosive AI growth alongside a surge in tech companies and technical talent. But who reaches these developers? Developers distrust traditional marketing. Who builds the samples, docs, tutorials, and SDKs they rely on? DevRel has become more critical than ever, especially as developers increasingly become decision-makers. In this talk, we’ll explore what DevRel is, how it drives impact, and how you can build an effective DevRel program.
Talk Title: DPDPA(Digital Personal Data Protection Act) Unleashed – Why It Matters for Women in Data
India’s Digital Personal Data Protection Act (DPDPA) is reshaping how organisations collect, store and use personal data, with a phased, 18‑month rollout. This presentation explores what’s in policy and law, then dives into what it unlocks for careers in data, security and consulting—especially for women. As data architect ,designing database architectures, will try connect legal constructs (Data Principals, Fiduciaries, Consent Managers, the Board) to real-world data and database practices, and show how DPDPA can be a powerful career accelerator, not just a compliance requirement.
Talk Title: Where Technology Meets Customer Needs: Lessons from a Newbie Solutions Engineer
When I stepped into the world of open-source databases as a Solutions Engineer, I expected to feel overwhelmed, but I found a role that made surprising sense. In this talk, I’ll share my journey navigating PostgreSQL with the help of modern cloud platforms like Aiven and DigitalOcean, tuning tools like DBtune, and migration partners like Hexacluster. This isn’t a deep-dive into internals, it’s a practical, beginner-friendly session to reducing the friction of managing PostgreSQL in real-world environments. Along the way, I’ll highlight the often-overlooked role of a Solutions Engineer: the human bridge between customer needs and engineering solutions. If you’re a student, a DBA, a DevOps engineer or just Postgres-curious, you’ll walk away with not only tools to explore, but also a career path to consider.

Talk Title: Architecting Ethical and Responsible AI with PostgreSQL 18
Have you ever developed an Agentic AI application using an agentic framework such as langGraph and pgai extension and noticed you don’t get good results during testing or the results are biased towards a demographic. You don’t know what to do. Organizations developing Agentic AI applications using an agentic framework such as LangGraph and pgai extension often encounter issues during implementation and testing, including suboptimal performance or bias in results such as demographic bias. Identifying the root causes of these issues can be difficult without proper tools and methodologies. This session addresses these challenges by introducing Responsible AI interpretability and explainability techniques. Participants will learn how to understand and trace the model’s decision-making process, enabling them to identify why specific results are generated. These capabilities are essential for meeting compliance requirements in regulated sectors, including banking and insurance. Attendees will gain practical knowledge on building Agentic AI applications that incorporate Responsible AI principles, ensuring transparent, accountable, and fair outcomes.
Rumi ![]()
Talk Title: New features of PostgreSQL 18
PostgreSQL 18 continues the PostgreSQL project’s long-standing focus on performance, scalability, reliability, and developer productivity, building incrementally on the improvements delivered in PostgreSQL 15–17.
Rather than introducing disruptive changes, PostgreSQL 18 is expected to emphasize refinement and maturity across core subsystems such as query execution, indexing, concurrency, replication, and observability, making PostgreSQL even more suitable for enterprise-scale and cloud-native workloads.
Talk Title: Platform Engineering Unpacked: Architecture, Evolution, and Hard-Won Lessons
The way engineering teams build and deliver software has changed dramatically. We’ve moved from manual server setups to automated pipelines, from ticket-based operations to self-service workflows, and from siloed teams to platform-driven organisations. This shift gave rise to Platform Engineering, a discipline focused on creating the internal systems, golden paths, and tooling that empower developers to move faster with less friction.
In this session, I’ll walk through the evolution that brought us here and why Platform Engineering has become a strategic priority across industries. I’ll share the architecture patterns that define successful platforms, how self-service emerges as a core capability, and the practical dos and don’ts learned from building real-world internal platforms.
Attendees will gain a clear understanding of:
Why DevOps wasn’t enough, and what Platform Engineering solves
The natural evolution from scripts → automation → abstractions → platforms
What makes a good platform (and what absolutely doesn’t)
How to design developer-centered systems and golden paths
My firsthand lessons from enabling engineering teams at scale
This talk gives a foundational, experience-driven view of what Platform Engineering really means today and how teams can start their journey the right way.
Our idea explores the implementation of AI-driven query optimization in PostgreSQL, addressing the limitations of traditional optimization methods in handling modern database complexities. We present an innovative approach using reinforcement learning for automated index selection and query plan optimization. Our system leverages PostgreSQL’s pg_stat_statements for collecting query metrics and employs HypoPG for index simulation, while a neural network model learns optimal indexing strategies from historical query patterns. Through comprehensive testing on various workload scenarios, we will validate the model’s ability to adapt to dynamic query patterns and complex analytical workloads. The research also examines the scalability challenges and practical considerations of implementing AI optimization in production environments.
Our findings establish a foundation for future developments in self-tuning databases while offering immediate practical benefits for PostgreSQL deployments. This work contributes to the broader evolution of database management systems, highlighting the potential of AI in creating more efficient and adaptive query optimization solutions.
This talk provides an introductory overview of Artificial Intelligence (AI) and Machine Learning (ML), exploring key concepts and their application in building intelligent systems. It will highlight the essential AI/ML techniques, such as supervised and unsupervised learning, and discuss practical use cases in modern industries. The session also focuses on how PostgreSQL, with its powerful extensions like PostgresML, TimescaleDB, and PostGIS, supports the development of AI-powered applications. By leveraging PostgreSQL’s ability to handle complex datasets and integrate machine learning models, participants will learn how to build scalable, intelligent solutions directly within the database environment.
Success is a multiplier of Action, External Factors and Destiny.
Out of these three, the only controllable aspect is our action. Again, action is the result of our EQ, IQ, SQ, and WQ (Willingness Quotient) together.
We all want to be successful and keep trying to motivate ourselves with external factors. We read inspirational books, listen to great personalities, and whenever possible upgrade ourselves with more knowledge and the list goes on.
Indeed these are excellent motivators, but in this process, we forget the most important source of energy, YOU!
We read other stories to feel inspired, thinking “I am not enough!”
But, the day we start accepting ourselves, introspect, understand, and align our life purpose with our routine, we find the internal POWER. This is a continuous source of motivation and energy which we need at down moments. When we feel, lonely, stuck and seek help, our inner voice is the greatest companion.
But, how many times do we consciously think about our “Subconscious”?
“Journey to Self” is our structured coaching program where we take back focus from the outside and delve deep inside to find our inner strength. Focusing on self-acceptance and personal growth
I believe everyone has POWER within them!
Let’s be the POWERHOUSE!
Human, AI, and Personalized User Experience for DB Observability: A Composable Approach
Database users across various technical levels are frequently frustrated by the time-consuming and inefficient process of identifying the root causes of issues. This process often involves navigating multiple systems or dashboards, leading to delays in finding solutions and potential downstream impacts on operations.
The challenge is compounded by the varying levels of expertise among users. It is essential to strike the right balance between specialized and generalized experiences. Oversimplification can result in the loss of critical information, while an overwhelming amount of data can alienate certain users.
Developers and designers are constantly navigating these trade-offs to deliver optimal user experiences. The integration of AI introduces an additional layer of complexity. While AI can provide personalized experiences within databases, it is crucial to maintain user trust and transparency in the process.
The concept of personalized composable observability offers a potential solution. By combining the strengths of human expertise, information balance, and AI-driven personalization, we can create intuitive and user-friendly experiences. This approach allows users to tailor their observability tools and workflows to their specific needs and preferences.