Allowing Product Developers to Develop Products with Tommy Dang, Co-Founder and CEO at Mage
Hashmap on Tap Ep. 116
“It doesn’t matter how powerful your tool is or even if it can predict the future, if I’m going to have to sit around for a month and read a manual, we’re going to have to move on.” -Tommy Dang, Co-Founder and CEO at Mage
Tommy Dang is Co-Founder and CEO at Mage where they are helping product developers use AI and data to make predictions for use cases such as churn prevention, product recommendations, customer lifetime value, and sales forecasting.
Tommy is a Bay Area native and attended Berkley. Right out of college, Tommy and a friend created their first website, Flash Deals, which sparked his interest and passion for creating and entrepreneurship. Prior to starting Mage, Tommy joined the Airbnb team as a Software Engineer on a small team that would launch the new Airbnb Experiences Business. A couple of years later, Tommy put together a team that created an internal Saas tool that helped other developers build landing pages, emails, promotions, search promotions, send push notifications, and more. This tool really helped empower others at Airbnb to build and create.
While working with a lot of developers on this project, Tommy realized that there were a lot of product developers that know what machine learning is, what it’s being used for, and how it can be used. However, when it came down to implementing their own ideas, they always had to rely on other data scientists to see their vision fulfilled. Tommy saw that this problem was hindering a lot of innovation and potential revenue. While searching for a data tool that would solve this issue, Tommy realized there were no such tools for machine learning for product developers built by other product developers. That’s when Tommy set out to create his own solution, Mage.
The goal at Mage is to make a product that is super easy and accessible to product developers. Although product developers are technical, they’re still burdened with learning a lot and coding a lot. The last thing they want to do is learn a whole new language or a whole new system. There are a lot of tools that are super powerful, but they have such a steep learning curve. Mage’s value comes from empowering current product developers to access and use AI technology by allowing them to build and deploy models rapidly and try out ideas without committing significant time and resources upfront.
Mage is an incredible tool that transforms your data into predictions, just like magic. It allows you to build, train, and deploy predictive models quickly even if you have no AI experience. They bring all the advantages of AI/ML to product developers so they can augment human decision-making and avoid repetitive tasks.
Mage holds themselves to three simple tenets. They strive for simplicity so that their tool is easy to use and quick to start. They place a high value on education by demonstrating what they do and how they work in order to build trust and boost confidence in their users. Lastly, they want to make sure every project is adaptable. Tommy’s opinion is that it is very important that however you build your model, you should be able to quickly get it back to your app. The goal is to make Mage super easy and accessible to its users.
Listen in to the episode to hear how Mage does it, perspectives on AI/ML, Mage’s GTM strategy, and their plans for the future.
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