How many engineers does it take to launch a great product?
Turns out, it depends on who you ask. Many start-ups claim that five is the right number. Large companies, on the other hand, can have a hundred or more engineers on each project. Jack Dorsey, Noah Glass, Biz Stone and Evan Williams formed the quartet that famously built and ran the first version of Twitter on an IBM Thinkpad with a Verizon wireless card. That early prototype was simply an internal system for employees at a podcasting company called Odeo. Today, Twitter has more than 540 million users.
Unlike Dorsey and his colleagues, most product and software engineers won’t become household names. Instead, they’re likely to deploy their brilliance as part of a larger group while working in relative anonymity.
Engineers think about users and their needs. They’re curious and empathetic. They’re willing to try new things, accept tough feedback and push for innovation. They’re idealistic problem solvers who are content to stay behind the scenes and share both credit and glory with others who have played their own part.
They’re accustomed to being the unsung heroes. Today, however, Built In is celebrating the people and teams that build great things at Ro and Keyaway. Here, their principals show off their teams’ work and tell us a bit about what it takes to get a new product out into the world.
Ro is a direct-to-patient healthcare company revolutionizing the industry by providing telehealth, diagnostic, lab, pharmacy and in-home services nationwide.
Describe the product or feature you worked on. What was your role in creating it?
We launched Ro’s Body program earlier this year to help patients achieve their weight loss goals. The program treats patients holistically by combining expert provider care and coaching, diagnostic testing, access to the most effective prescription medication available, insurance concierge services, weight tracking and an educational curriculum.
Our Body program introduced new patterns and complexities that required us to rethink how our platform facilitates care. Almost every engineering team at Ro contributed to building new capabilities, supporting new ways of delivering care and breaking previous assumptions in pursuit of evolving our platform to support more flexible and complex treatment journeys. We’ve created new patterns for conveniently collecting and surfacing health data, the electronic delivery of prescriptions to external pharmacies, tracking insurance approval and progress in the program and more.
As a director of engineering, my role was to make sure our platform engineering teams had clarity on the problems and opportunities, had the prioritization and resources to be successful and built in a way that aligned with the long-term vision.
What was the most exciting or interesting aspect of working on this product?
I’m most excited about the new patterns we’ve created for tracking and surfacing important data points such as side effects, medication adherence, prescription history and time series data for weight and other vitals. These data points inform personalized adjustments to the patient’s treatment. They ultimately help providers support holistic patient-centric decisions.
We recently delivered new in-app workflows to improve how we collect and treat side effects by prompting patients who are at certain stages of their treatment to report side effects. Side effects are collected in a structured way that also collects their severity. Automatic task creation and routing sorted by priority let providers review everything in an efficient manner.
We’re now working on improving the quality of time series vital sign data such as weight and heart rate. Some Ro patients use smart scales to track their weight, which is shared with their provider. We’re building new capabilities to visualize that data more effectively for providers. We’re also working on detecting and removing invalid data points because it turns out many people use the same scale to weigh their kids, pets or suitcases.
How did your engineering team culture support the successful creation of this new product?
Thinking big to build new platform capabilities that support our patients today while making progress toward the future vision is a key aspect of how we approach problems and opportunities. It’s also very important to us to operate with urgency by building iteratively to both deliver value as quickly as possible and build for the long term. Most importantly, engineers at Ro frequently break down silos to own problems and opportunities that cross team and domain boundaries. Building the side effects reporting capability mentioned earlier is a great example of this. The project included enhancements to our patient intake/onboarding, web and mobile apps, provider-facing applications, tasks system and health data infrastructure. The team working on it owned the problem end-to-end, which was key to delivering a smooth experience for our patients and providers.
Keyway uses AI, machine learning and data science to empower smart real estate investment decisions for powerful outcomes.
Describe the product or feature you worked on. What does it do, and what was your role in creating it?
We are building the world's first real estate investment co-pilot named KeyPilot. KeyPilot uses AI, machine learning and data science to drive investment and operational performance.
Through both data and investor-driven insights, we find fragmented and mispriced real estate markets and assets. Then, we build and manage stabilized portfolios at scale and speed, delivering attractive returns for investors.
We use technology at every stage of the real estate lifecycle from sourcing to underwriting, buying, managing and selling to achieve smoother, faster and lower-cost deals.
As Co-Founder & Chief Operating Officer, I provide the vision for our technology and collaborate closely with our product and engineering teams.
What was the most exciting or interesting aspect of working on this product?
The most exciting aspect of our technology is the ability to unlock underlying real estate value and enhance returns by combining sourcing, underwriting and asset management on one AI-driven platform. That integration is key to making real estate investing and asset management simpler, faster and more efficient.
We can now analyze 300 different data sources and more than 12,000 data points for every single property we look at, which helps provide greater insights into fragmented markets and mispriced assets than ever before. This is a big win for investors because we can deploy capital more rapidly at scale.
We’re at the forefront of generative AI and machine learning, and every day we are expanding the boundaries of what technological breakthroughs are possible for real estate investing.
How did your engineering team culture support the successful creation of this new product?
Our culture of collaboration fosters close teamwork between our real estate investment and engineering teams. Together, they developed a way to identify acquisition targets fitting the value-add strategy at speed and scale for all properties in a given market.
To address this need, our data scientists, who are experts in AI and machine learning, created a proprietary tool called a rent thermometer that enables our investment team to assess whether a given property is a good value-add target given local market dynamics, individual property performance and characteristics.
With the rent thermometer, we achieved substantial advancements in identifying mispriced markets and assets, providing our real estate investment team with more robust and accurate investment recommendations. This successful partnership exemplifies our culture of collaboration where diverse expertise is harnessed to create innovative solutions that propel our business forward.
