Yogesh Chauhan

LiteLLM is an open-source proxy that connects your app to LLMs through one unified interface. Paired with Redis, it gives AI and ML teams a simple yet powerful way to unify access to LLMs, accelerate response times, and make AI apps real-time. Redis handles performance, memory, and data coordination that modern AI apps demand, while LiteLLM handles abstraction and routing. Our AI Product Marketing Manager Rini Vasan dives into: ▶️ What LiteLLM is ▶️ Why it works well with Redis ▶️ How LiteLLM and Redis work together Learn how to scale your LLM gateway with LiteLLM & Redis: https://lnkd.in/gqsTebF7

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Had a great time attending the Product Thinking and the Future of EPD(Engineering, product and Design) as an Engineering Leader event hosted by ELC today! A big thank you to ELC and Commure for organizing this thoughtful and engaging session—and to the amazing panel, including Dhruv Parthasarathy, Nissim Lehyani, James Tyack,Patrick Gallagher, for sharing their candid insights on how the traditional boundaries between Engineering, Product, and Design are rapidly evolving in the age of AI. Here are a few takeaways that really stuck with me: 🔹 Companies are shifting away from static PRDs and increasingly using prototypes as a discovery tool—validating ideas with customers early and often. 🔹 Hiring is changing: it’s less about checking boxes and more about finding problem solvers and clear thinkers who can adapt and lead. 🔹 When it comes to LLMs, everyone has their own “AHA moment.” Until then, keep exploring. You’ve essentially got the smartest person in your pocket—start using it to solve real problems. Excited to bring these insights back to my team and continue experimenting at the intersection of product, engineering, and AI! #EngineeringLeadership #AI #ProductThinking #ELC #LLM #TechLeadership #Prototyping #EPD

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Proud to be part of the Goodlife AI advisory board. The mission resonates deeply — building a shopping assistant that works for the people across every surface of their shopping journey. It's been exciting to guide the engineering team as they bring this AI-first product to life. From finding the right product at the best price, to budgeting your cart across stores, optimizing payment methods and loyalty perks and eventually post purchase support — Goodlife aspires to be the omnipresent assistant every person deserves.

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Shantanu Narayen’s 18 year tenure as CEO at Adobe is a reminder of how rare long-term stewardship has become in Silicon Valley. During his time with the company, the company’s stock increased more than 6x and its business model fundamentally changed. The most important decision of his tenure was moving Adobe from selling boxed software like Creative Suite to a subscription platform through Creative Cloud. At the time it was controversial. Today, it is considered one of the most successful SaaS transitions in the history of enterprise software, turning Photoshop, Illustrator, and Acrobat into one of the most profitable recurring software ecosystems ever built. The respect he commands across the industry says a lot about how difficult that transformation actually was. Microsoft CEO Satya Nadella even posted publicly congratulating Narayen on a “legendary run,” praising both his leadership and the way he expanded what creators and businesses could do with software. In an industry that is often intensely competitive, that kind of recognition from peers is not given lightly. There are only a few CEOs in the world who truly get to define one era of software and then help set the stage for the next. Narayen did it by turning Adobe into a SaaS powerhouse. However, the next leader will have to answer a harder question. What does a creative software company look like when AI becomes part of the creative process itself? #Adobe #Leadership #SaaS #AI #Technology

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Proud to see our work with Nimbus Therapeutics featured in the AWS re:Invent keynote! Our team developed drug-discovery aware LLMs using Nova Forge, combining Supervised Fine-Tuning (SFT) and Reinforcement Fine-Tuning (RFT) to create custom model tailored for Nimbus. Thanks Andy Lapastora Krishnateja Killamsetty Elyse (Jiali) Zhang and Clement PERROT for the exceptional work. Also thanks to the wonderful AGI and Nimbus team for making this collaboration a success. cc: Hannah Marlowe, PhD Sri Elaprolu Taimur Rashid Sharlina Keshava Caleb Wilkinson Alexandra Fedorova

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Snapped this during Nimisha Asthagiri’s talk on Scaling responsible multi-agent architectures at #InfoQDevSummit. “What makes a micro-service different than an AI agent? An agent can make decisions and has self-learning abilities.” This gave me more clarity on how to see AI agents in software developers lens.

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𝗔𝗜 𝗱𝗶𝗱𝗻’𝘁 𝗯𝗿𝗲𝗮𝗸 𝘆𝗼𝘂𝗿 𝗙𝗶𝗻𝗢𝗽𝘀. 𝗜𝘁 𝗼𝘂𝘁𝗴𝗿𝗲𝘄 𝗶𝘁. Model training can run for hours or weeks. Inference costs change with user behavior. Experiments share GPU infrastructure across teams and timelines, making ownership and accountability unclear. GPU costs are 10–20x higher than standard compute, yet most cost tools only show totals - not intent, impact, or outcomes. Why Enterprise FinOps Needs an AI-Oriented Architecture explains why cost governance breaks under AI workloads and how AI-aware visibility, guardrails, and outcome-based tracking help enterprises regain control before budgets spiral. 𝘙𝘦𝘢𝘥 𝘵𝘩𝘦 𝘧𝘶𝘭𝘭 𝘣𝘭𝘰𝘨 𝘣𝘦𝘭𝘰𝘸 𝘪𝘯 𝘵𝘩𝘦 𝘤𝘰𝘮𝘮𝘦𝘯𝘵𝘴 𝘵𝘰 𝘶𝘯𝘥𝘦𝘳𝘴𝘵𝘢𝘯𝘥 𝘸𝘩𝘢𝘵 𝘍𝘪𝘯𝘖𝘱𝘴 𝘧𝘰𝘳 𝘈𝘐 𝘳𝘦𝘢𝘭𝘭𝘺 𝘳𝘦𝘲𝘶𝘪𝘳𝘦𝘴. #FinOps #AICostManagement #AIInfrastructure #CloudCosts #EnterpriseAI #CAIStack

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Not supporting the Meta layoffs but after going through the memo by Alexandr Wang wherein he explains the reason for downsizing is to give more opportunity to individuals to make an impact, it makes sense if I look at from my own experience. Companies where I have made the most impact and also stayed longer usually I led projects end to end and took responsibility of making sure the project and the team succeeds. What most executives don't understand that hiring a talented individual is not another cog in the wheel and if they are not given the necessary ownership and power to lead a project along with all the components there is a high chance those individuals will make lower impact than expected. Whenever I led other engineers I made sure they are given the entire responsibility of one particular area with all possible components instead of assigning fractional tasks to multiple devs.

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Incomplete thoughts about compensation (5) – the cliff The most common vesting schedule for RSUs is a grant that vests over 4 years. On top of the initial grant, you get refreshers every year where the expectation is that if you operate at the right level 4 refreshers are equal to your initial grant. With this vesting schedule, you have an increasing comp for the first 4 years but have a dramatic cliff after 4 years since you vested all your initial grant. To give an example, if your initial grant is 400k over 4 years, and each yearly refresher is 100k over 4 years again, your stock compensation is: - Year 1: 100k - Yea 2: 125k - Year 3: 150k - Year 4: 175k - Year 5: 100k The year 4->5 is the hard pill to swallow – it probably is one of the many difficult topics for managers to deal with. While managers may try to tell you about your growth, the opportunities and what not, I think the best way to think about this cliff is to look at a bigger time window. Rather than looking at your comp year over year, look at the average over 2-4 years – companies could easily prevent the cliff by giving refreshers every 4 years only. If they don’t it’s because they would rather reward good engineers earlier even if it will create a cliff after 4 years. The cliff is also worse if the stock has performed well for the past 4 years – you should discard this additional benefit when looking at the cliff. Look at the value at grant time rather than vesting time. Some companies recently (in the past few years) have started to frontload RSUs (e.g. you get larger vest for the first 2 years) – this kind of vesting tends to soften the cliff, but also present two large drawbacks: - You don’t benefit much from stock growth - The company can reduce your compensation faster if you’re underperforming Thoughts on the 4 year cliff?

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