AI Trailblazers: Chris Clarke of Second Nature on Building an AI Strategy from the Ground Up

In this installment of our AI Trailblazers series, we sat down with Chris Clarke, Vice President of Product at Second Nature, to discuss their journey with AI adoption. 

Second Nature's mission is to create "Triple Win" experiences where residents, property managers, and investors all benefit. They do this by offering fully managed resident onboarding and a services suite that solve household problems and increase financial health for everyone.

From AI POCs to strategic roadmaps, Chris shares valuable insights on how organizations can thoughtfully implement AI both internally and externally while navigating potential pitfalls. 

Getting Started with AI: Balancing Value and Risk

Can you tell us about Second Nature's AI journey so far?

Chris: Like many organizations, we started with some very specific ad hoc POCs (proof of concepts) to get going. Our first experiment was a RAG-based chat agent focused on the resident onboarding experience. The concept was to create an agent trained specifically on all of the information a resident would receive when they were onboarding into a new home and answer questions.

While it was pretty accurate, we still had hallucination concerns. When dealing with a legal document like a lease, there's simply no room for error. The liability exposure was really high, and the value was somewhat low to medium, so we decided to focus on some higher value opportunities. However, we learned a lot from the process.

How did your approach evolve after that initial experiment?

Chris: After that POC, I started looking across our business to identify opportunities where AI could unlock efficiency. Some of our sister portfolio companies had seen dramatic productivity increases of more than 10x by applying AI internally—across marketing, engineering, customer success, and more.

I realized that focusing AI internally provided lower liability with higher upside and allowed us to learn in a safe environment. So we shifted to a strategic posture of unlocking AI for internal use first.  Additionally, a colleague of mine branded an “AI for Everyone” campaign to encourage people to lean into AI to enhance their own productivity. On the product side, I developed about a dozen AI-related opportunities, both internal and external, to be put into a “discovery backlog” and shepherded forward by a product manager.

Strategic Framework for AI Implementation

What types of AI opportunities have you identified at Second Nature?

Chris: We've identified several promising use cases, including:

• Analyzing property manager and resident sentiment to help teams provide more proactive service
• Predicting the most impactful products to personalize to our customers
• Writing product and technical documentation with agent access
• Helping our customers stay up to speed in a changing regulatory environment
• Co-piloting an agent with our operations teams to recommend issues to address that aren’t immediately obvious but slows them down

How do you evaluate and prioritize these AI opportunities?

Chris: Similar to non-AI focused opportunities, one of the tools I use is a lean canvas to compare opportunities on an apples-to-apples basis.  This creates a baseline for charting the relative value of each opportunity rather than over-indexing on one dimension.

For a newly created AI-focused Product Manager role, I made the job description explicitly outcome-focused. Rather than just listing responsibilities or competencies, we included quantifiable OKRs like "drive NPS up using AI" or "drive internal efficiency by X percent." This helps candidates understand what success looks like from day one and also provides the hiring team a strong connection back to the results we want the role to achieve.

Building an AI-Focused Team

What prompted you to create a dedicated AI product role?

Chris: The reality is that while I can source ideas internally and externally all day long, if no one is tasked and accountable for driving outcomes, it's not going to get done. I simply don't have the time to drive the roadmap with effectiveness or dive deep with the level of thought required.

Seeing the significant impact—10X+ wins—that peers at other companies were achieving by applying AI convinced me we needed to invest in dedicated leadership. We needed someone with experience who could drive it from a product strategy perspective, alongside technical leadership to build the foundation for our AI platform.

What do you look for in candidates for AI-focused roles?

Chris: On the soft skills side, I wanted a good communicator and storyteller with the energy to be a change management leader. I could have hired a PM focused on specific use cases, but I wanted someone who could bring the entire company along with them—a bit of a salesperson who could tell the story and communicate confidently about what we're doing but also had the credibility to execute.

Intellectual curiosity about AI was essential—someone who could be passionate and excited about spending hours discussing the space. For applied experience, I was looking for one to two years working on Gen AI related projects. Given how new this space is, you can't expect much more than that, but I wanted someone who had actually built things with AI to minimize the learning curve.

Moving forward, I think you’ll find our teams adding an “AI Quotient” as part of the candidate review process, even if they're not explicitly in an "AI role."

AI Tools and Resources

What AI tools are you currently using at Second Nature?

Chris: I'm actually a power user of Dashworks at Second Nature. It's been tremendously helpful, especially if for example a team member is unavailable and I need to get up to speed quickly on technical concepts and systems. Instead of spending time meeting with others, or looking at technical documentation to connect the dots, I can access any data I have permission to through Dashworks.

I use Perplexity every day as my main search engine—I've set it up so when I type in the URL bar in Chrome, it goes straight to Perplexity. We have an enterprise version, which I find really helpful for competitive intelligence and market research.

I’ve just started exploring ChatPRD, and our engineering team uses an AI plugin integrated with Codeium for PR reviews. For an upcoming hackathon, I've compiled a list of tools for different functions to explore, including Synapse, WireGen and UIzard.  My peers are also adding their own tools to the list to give us a roadmap for applied learning with these tools.

How do you stay up-to-date with developments in AI?

Chris: You have to have a real interest and passion for the space to invest the time. I use AI tools as much as possible every day, depending on the use case—for writing, research, etc. I also encourage and set the expectation that my team members lean into the tools available to them.

My learning doesn’t just happen at work. For example, I recently built my own personal real estate app to look at local trends using Cursor. In just three hours, I had three different API integrations displaying real estate data in a nice Material UI design. It blew my mind because similar work would have taken me weeks or months when I was writing code in the early 2000s.

Advice for Organizations Starting Their AI Journey

Any parting thoughts for those who are just beginning to explore AI implementation?

Chris: My advice would be, as many people say, to just get going and do something. There's a great quote I've had on a T-shirt: "Build something today, even if it sucks." That would be my advice for AI adoption—don't overthink it, just start doing it.

There is always time to think more strategically, but you've got to get going. Give your team some buffer and make it an expectation that they're going to do something with AI, then follow through with it.