Two Keys To AI’s Future: What We Heard From Developers At AWS re:Invent 2023

Casey Stegman and Olivia Cohen
December 19, 2023
#genAI

At AWS re:Invent 2023, we chatted with numerous developers about the thing everyone was talking about. Which was…

drum roll

AI.

Specifically, Generative AI.

So much has happened over the last year in this space. LLMs have gone from being primarily a field of academic research to something every developer, product engineer, IT decision maker, C-level executive (and everyone in between) is thinking about.

Questions that have emerged in that time—in the news, at tech conferences, in conversations with developers, among colleagues, in blog articles, etc.—include: Are we in a hype cycle? Is this just another fad? Is AI, after a series of promising starts and then long winters, here to stay for real this time? And if so, how can an organization use Generative AI to disrupt the market instead of being disrupted?

We chatted with several developers at AWS re:Invent to get a sense of what they were thinking about when it comes to Generative AI.

Here’s some of what they had to say:

"[Generative AI] will help people build faster and safer, but [it’s] definitely not going to replace everything." - Developer

"I'm excited about all the tools that can help developers to develop faster, like CodeWhisperer." - Head of Cloud Operations

"Generative AI is here to stay." - Chief Technology Officer

The theme throughout these quotes is how Generative AI will benefit developers in the work they do. Specifically, how Generative AI will help them develop faster and easier.

A prime example of this is, as one of those quotes above notes, Amazon CodeWhisperer, which boosts developer productivity through AI-driven code assistance.

The data used to train Generative AI code assistants, like Amazon CodeWhisperer, is key, though.

This is why MongoDB collaborated with the Amazon CodeWhisperer Data Science team to train CodeWhisperer’s foundational model on MongoDB use cases to give developers the best possible code suggestions.

In addition to helping developers do their work faster and easier, advancements in Generative AI are also empowering developers—specifically developers with more limited backgrounds in AI/ML—to use LLMs more effectively in their applications.

In fact, it’s now easier than ever for developers to build AI-powered apps.

As one data engineer at AWS re:Invent 2023 said: “Generative AI enables people that have no experience in AI to start entering this industry to use their domain knowledge to explore the applications.”

A good example of this is Retrieval-Augmentation Generation or RAG.

MongoDB’s Mat Keep writes in a recent blog article: “As recently as 12 months ago, any mention of retrieval-augmented generation (RAG) would have left most of us confused. However, with the explosion of generative AI, the RAG architectural pattern has now firmly established itself in the enterprise landscape.”

RAG presents developers with a potent combination. They can take the incredible knowledge and reasoning capabilities of pre-trained, general purpose Generative AI models and feed them with accurate and up-to-date company-specific data. This means developers can build AI-powered apps that generate outputs grounded in enterprise data and knowledge without having to turn to specialized data science teams to train or fine-tune models — which is a complex, time-consuming, and expensive process.

RAG is one of many examples of how development tools and technologies are changing to allow developers to build AI confidently and securely.

When you look at all of the above, it’s very clear that this new revolutionary era of Generative AI is driven by empowered developers.

Still, because there are so many incredible advances in both commercial and open-source Generative AI models, and because everyone has access to these, the real differentiation comes down to something unique to every organization: data.

One question we’re left to ask is: What will developers be talking about with respect to Generative AI at AWS re:Invent in the coming year?

As we’ve seen over the last twelve months, a lot can happen and change. So there’s no exact telling what the future will hold.

But what is clear is that the two key things that will determine Generative AI’s future will continue to be data and developers.

To learn more, check out our resources page for building AI-powered apps.

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Introducing Auto-Index Creation for Atlas Serverless Instances

Atlas serverless instances now offer auto-index creation, a new capability that automatically generates indexes to help optimize performance and reduce the cost of your queries. Auto-index creation is now available in public preview and enabled by default for all serverless instance deployments - allowing developers to worry less about needing to manually optimize their serverless database. Simplify development with Atlas serverless instances Developers love serverless technology primarily because of its unparalleled ease of use. By abstracting away infrastructure management, serverless allows developers to focus on what they do best: writing code and building amazing applications. It’s expected that any great serverless offering just works out of the box, without a large learning curve or emphasis on implementation and setup. Atlas serverless instances, first announced as generally available in June 2022, deliver on this promise by allowing you to deploy a database that seamlessly scales with demand in seconds with minimal configuration and a consumption-based pricing model that only charges for what you use. The addition of auto-index creation now further reduces management overhead by automating index creation for common queries to ensure fast response time. How auto-indexing works Indexes are special data structures that store a small portion of the collection's data set in an easy-to-traverse form. Without indexes, MongoDB must perform a collection scan—i.e., scan every document in a collection—to select those documents that match the query statement. By adding an index to appropriate queries, you can dramatically reduce the number of documents the query engine must inspect in order to return a result and in turn benefit from improved query performance and a reduction in the read operations you are charged for. With auto-index creation enabled, Atlas will analyze your recent query workload and automatically create high-impact indexes based on index suggestions in the Performance Advisor . This helps promote good index hygiene for your data by creating high-impact indexes without requiring you to regularly check for suggestions or create indexes manually. You can view newly created indexes in the Atlas UI in the Collections tab of the Data Explorer. You can also continue to manually add additional indexes in the Collections tab or via the Performance Advisor at any time. To learn more about auto-index creation, visit our documentation . Create a serverless instance in Atlas today.

December 18, 2023
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The Developers' Developers: Two Australian Developers Share Their Connections to Customers

The world’s 28 million software developers are writing the foundations of our future, propelling innovation for their organizations through lines of code by creating game-changing new apps. Indeed, the US Bureau of Labor Statistics predicts that between 2022 and 2032, the number of software developers, quality assurance analysts, and testers will grow 24%, “much faster than the average for all occupations.” Fueling this innovative workforce is another group of developers, the people working behind the scenes to build the tools, technologies and platforms that other developers need to be successful: the developers’ developers. Many developers at MongoDB—which after all was built by developers for developers, and is beloved by enterprises and startups alike—fall into this camp. To learn more about what makes these developers tick, we talked with two Australia-based senior software engineers at MongoDB who love to code for their peers. For Lavender Chan and Angus Lee, there’s nothing like seeing the ripple effect of the code they have been working on and the impact it has on their customers. What’s more, the opportunity to be a “developer’s developer” has allowed Chan and Lee to find a space for deep technical work while thriving in an autonomous environment. At MongoDB we believe developers will build the future. First, can you share more about your roles and what you’re working on? Lavender Chan (LC): I work on the Relational Migrator tool, which allows developers to migrate SQL data onto MongoDB. I joined the company two and a half years ago, and have been part of the Sydney technology scene for the last 10 years. The appeal of joining MongoDB was that it’s a large global company, but in the engineering team you are able to have a big impact and a lot of autonomy. Relational Migrator was a greenfield project, and our team has been able to take the original product idea built out of the US and run with it. I’m a full stack developer and have touched on every feature of the tool. A lot of the engineers were able to contribute and work on new ideas. There’s also a strong emphasis on culture here which practically means a lot of the people I work with are excited to be here and passionate about their roles. Angus Lee (AL): I work in the MongoDB Charts team in Australia and think our team is a sweet spot for developers. I’ve interned for other tech companies and started my career at MongoDB. Since then I’ve been given responsibilities where I can create a lot of impact. My role at MongoDB in Sydney has also given me great opportunities to connect directly to the developers we are creating products for in a way that pushes my work to a higher level. Your roles are focused on products targeted to other developers. How does developing for developers affect your approach to your work? LC: In our roles we are creating directly for other developers, so the work that I am doing is deeply technical and specific. As Migrator is a newer product, we are able to interact directly with our customers—other developers—and often a lot of their questions are quite complex and specific, which means I go on a learning journey in debunking and fixing their problems. AL: We have a strong team culture in that as developers we want to be our own users. That means we want to use other MongoDB team products, and they use ours, so we can better identify pain points and issues for our customers. There’s a term that developers use called “dogfooding” that really sums up how we think on this, which basically means to use your own product. It means for me that I think about writing clean code to help any other developers extend on this, and how effective what I do will be for the user. What I’ve also learnt is how our product helps other products thrive. We should have done all the hard work to transform data and show it through data visualizsation tools so it’s easy for the customer. Can you tell us more about this connection to customers and how MongoDB empowers developers? LC: When Relational Migrator was released as a general product, I went to MongoDB World to work at the booth, and I talked to the developers and customers using the platform. As an engineer, it was an amazing experience and opportunity to see how it was being used and what else we could be doing. This connection of engineers with customers, as well as the ability to speak to them regularly in my role, is unique. In other companies I would need to go through support teams, to go through someone else just to push out a bug fix. Our team is very customer focused, so we can prioritizse features that our customers want. AL: One of the best moments for me at MongoDB was when I went to MongoDB World and I sat down with a customer to talk through a feature of Charts. It was a pivotal moment to see the improvements it makes for the businesses that use it, and the impact it generates for their customers beyond that. I could sit back and see the ripple effect of the code I’m writing. There is also a great feedback engine where our users can submit ideas and other users can vote for that feature. The product managers pick from these and push out features that are directly relevant to the developers using it. Where we really connect is in our aim to create an open forum for developers and customers to provide feedback and suggest ideas. Developers are problem solvers. As part of the MongoDB Love Your Developers campaign, we believe in championing the voice of developers and giving them the freedom to experiment and innovate. How do you see this in action? LC: In other places I was a small cog in a massive system. At MongoDB, I really have an impact, and can see directly how my work translates to our final product. In Sydney, we’re a satellite office, but it’s indicative of our company culture that there is huge trust placed in these teams. We’re given high impact projects and can run with them, which means I’ve been able to watch the Relational Migrator product go from a tiny product used by only a few customers, to one that is now generally available. Not many engineers get to work for a well-established,large company and still have the opportunity to work on and release products like a startup. There is a strong global interest in AI-driven innovations. How have your connections to customers led to innovations in this area? AL: We’ve been able to take an idea for a new AI feature, Natural Language Charts , and take it from concept to being released as a feature at MongoDB.local in London. We could see from our conversations with customers, as well as broader industry trends, that there was strong interest in new AI features so we were able to prioritizse it for Charts. We started with nothing and were given the freedom to research how this feature could work using AI, create a new proof of concept, and from there we were able to push it out into a feature which was a really proud moment. Having this agility and flexibility to prioritize something new is exactly what we want to provide to our customers. I never feel like I'm just churning out code. We are connected to the work and to our customers. MongoDB is built by developers, for developers. Become part of the team changing the way the world works with data!

May 9, 2024