The Enterprise GTM Podcast How Are World-Class Engineering Teams Setting Up For Success with AI?
Now that AI has been fully integrated into our lives, the question among developers, engineers, and even end-users is no longer “What is AI?” but rather “How can I use AI in the best possible way?” We are joined today by Sushant Hiray, the Senior Director of Machine Learning at the business communications platform, RingCentral, and Guhan Venguswamy, the Head of Platform at Jasper – a marketing-focused AI copilot. The pair are here to discuss how their companies have adapted to the explosion of LLMs, beginning with what their businesses are all about, the products they offer, and the customers they aim to serve. In our conversation, we learn about the common challenges that are found at the platform and engineering layers, how the adoption of LLMs has changed the way data, engineering, ML, and data science teams are structured, and why the title “Full-Stack Engineer” will need to be revisited moving forward.
Key Points From This Episode:
* Jasper:
* Developer experience is paramount for the platform team at Jasper AI. Rapid onboarding, and providing a scalable and flexible platform are their key tenets.
* The landscape in AI is changing so rapidly that it's hard to be too opinionated on platform level choices.
* Enabling their larger enterprise customers to bring their own model or giving them the choice to pick and choose models off-the-shelf has been key for customer acquisition.
* A constant theme for his team is to be thoughtful about what they make part of their platform versus use something that is off-the-shelf. You don’t want to build something into your platform when a pure-play infra player is better positioned to do it 100x better.
* Ringcentral:
* Ringcentral is infusing product after product with AI and Sushant’s team is a key enabler for that.
* Some of the engineering challenges that Ringcentral faces include tapping into troves of multi-modal data, building on a platform that is at least a decade old, and driving a streamlined customer experience while doing so.
* Privacy and regulatory challenges are an entirely different kind of challenge that Ringcentral faces in infusing their products with AI.
* Team composition and skill sets:
* Embedding someone with deep AI expertise into an engineering team working on a feature has worked out for Jasper AI. For Ringcentral, a more central AI team is the way to go but collaboration is very strong cross-functionally.
* Our guests predict which job title will be the most glamorous by 2026.
Quotes:
“Our goal from a developer experience is to onboard new engineers and get them ready to commit code within the first day or two of being in the company” — Guhan Venguswamy [0:07:39]
“Historically, communications [was] as simple as pick up the phone and call somebody. Now, you have made it a lot smarter but at the cost of a lot of data privacy along the way.” — @SushantHiray [0:18:58]
“The pace is changing so rapidly that you cannot be really opinionated about what tech stack you’re using because very soon, within six months maybe, something is going to change.” — @SushantHiray [0:23:35]
“Focusing on rapid iteration in the short-term, with a long-term vision to hang our hat on, is what helps us adapt to challenges.” — Guhan Venguswamy [0:34:02]
“A core skill set for any engineer, regardless of where you are in the organization, is to have the ability to work with large language models. And when I say work with, I mean, utilize and apply the large language models to whatever use case you have..” – Guhan Venguswamy [0:35:21]
Links Mentioned in Today’s Episode:
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