LLMs in Production with Microsoft
- Date
- 2024-08-28
- Location
- Bengaluru, Karnataka, India
- Host
- Microsoft
About this event
Shipping an LLM demo is easy. Shipping an LLM system that works reliably in the real world is where things get interesting. LLMs in Production with Microsoft is an in-person gathering in Bengaluru for people who want to move beyond experiments and talk seriously about what it takes to build, deploy, and operate AI applications that can stand up to real usage. This event brings together practitioners, builders, and curious professionals around a topic that matters right now: how large language models behave once they leave the notebook and meet product requirements, users, costs, latency, and operational constraints. If you care about making AI useful, dependable, and practical, this is the room you want to be in. About the Event At its core, this is a community event focused on LLMs in production through the lens of real-world implementation and discussion. The Microsoft connection signals a practical, platform-aware conversation rather than abstract AI hype, with attention on how modern teams think about deploying and maintaining LLM-powered systems. Expect a format that balances learning with conversation. This is not just about sitting through slides; it is also about hearing how others are approaching similar problems, comparing notes with peers, and getting sharper on the decisions that matter once an AI feature moves from prototype to product. Because the event is in person in Bengaluru, it also creates space for the kind of exchange that is hard to reproduce online: quick follow-up questions, candid implementation stories, architecture debates, and side conversations that often lead to better ideas than a formal session alone. Whether you are deep in AI work already or still figuring out how production-grade LLM systems should be designed, this event is meant to give you a clearer view of the landscape and a stronger sense of what good looks like in practice. What to Expect You should expect a grounded evening centered on the challenges and patterns that show up when teams put LLMs into real environments. The focus is likely to be on production concerns rather than introductory theory: how systems are structured, where they break, what tradeoffs teams make, and how to think more rigorously about operating AI applications over time. A strong event in this space usually creates room for several kinds of value, and this one is well positioned for that mix: Practical discussions around deploying and running LLM-backed applications Community exchange with other engineers, founders, product thinkers, and AI practitioners Networking time with people actively working in LLMs, AI infrastructure, and applied ML Implementation perspectives that help connect technical ideas to real product decisions You can also expect conversations around the production lifecycle itself, including questions such as: How do you move from prototype quality to user-facing reliability? What changes when cost, latency, and monitoring become first-order concerns? How should teams think about evaluation, failure modes, and iteration loops? Where do platform choices and ecosystem tools actually help, and where do they add complexity? Even if the session content spans multiple levels of depth, the biggest advantage of attending in person is that you can calibrate quickly. You will hear what others are building, what problems keep resurfacing, and which approaches seem to be holding up under actual usage. Why Attend If you are working with LLMs today, you already know that the hard part is rarely getting a model to produce an interesting output. The hard part is building something that is repeatable, maintainable, useful, and trustworthy. This event is valuable because it is anchored in that reality. You will leave with a better sense of how practitioners think about production readiness. That can mean architectural perspective, clearer terminology, sharper questions to ask your team, or a more realistic understanding of what shipping AI features actually involves once user expectations and operational constraints enter the picture. There is also real value in the room itself. Bengaluru has one of the strongest technology communities anywhere, and being in a space with people who care about applied AI can shorten your learning curve. A single conversation can help you avoid a weak implementation path, discover a better way to structure your stack, or simply validate that the problems you are facing are shared by others. This event is especially worth your time if you want to: Build a more practical mental model for LLM deployment and operations Learn from peers who are thinking beyond demos and proofs of concept Meet people across engineering, product, AI, and startup ecosystems Stay current on how production AI is being discussed in a serious, implementation-focused setting Practical Details Location: This is an in-person event in Bengaluru, India. If face-to-face learning and networking matter to you, that is a major reason to attend. The in-person format makes it easier to ask nuanced questions, meet collaborators, and continue conversations after the formal programming ends. Date and time: Wednesday, August 28 at 6:00 PM GMT+5:30. An evening schedule makes this accessible for working professionals who want to attend after the core workday and still get meaningful learning and connection out of the session. A few good ways to prepare: Come with a clear picture of your current LLM use case, if you have one Bring questions about reliability, evaluation, tooling, deployment, or scaling Be ready to introduce yourself and what you are building or exploring Leave a little buffer in your schedule for networking before or after the main session If you are deciding whether this deserves a spot on your calendar, the simplest answer is this: if you care about how AI systems actually get built and run in the real world, this event is directly aligned with that interest. It is local, timely, and focused on one of the most important shifts happening in software right now.
Who should attend
If you want more than surface-level AI talk and care about how LLMs actually work in live products, you will likely feel at home here. - You are a **software engineer, ML engineer, or AI developer** working on LLM-enabled features and want stronger intuition for production architecture, reliability, and deployment tradeoffs. - You are a **product manager, technical founder, or startup operator** figuring out how to turn AI capabilities into something useful, scalable, and maintainable for real users. - You are already experimenting with **RAG, copilots, assistants, internal AI tools, or workflow automation** and want to compare your approach with others building in the same space. - You are part of a team evaluating **Microsoft-based AI workflows, infrastructure, or ecosystem choices** and want a more grounded view of production considerations. - You learn best by being in the room with other practitioners, asking direct questions, and hearing what is working, what is failing, and what teams are changing. - You are based in or around **Bengaluru’s tech community** and want to meet people actively building with LLMs, not just talking about them.