Circle (circle.so)
Circle (circle.so) Innovation & Technology Culture
Frequently Asked Questions
Circle's philosophy when it comes to AI: AI or die. Our CEO, Sid, wrote a Notion memo with this exact title and included the preface that: the world is rapidly undergoing an AI transformation, and Circle will need to be a part of this transformation in order to survive and thrive.
This philosophy and the strategy that Sid lays out in the memo speak not only to several of our values – Product First, Grow Together, Long-Term Thinking – but also to the way we value the people that make Circle what it is, both as a team and as a broader community of Circle users, creators, and connectors. As Sid put it, the goal of using AI at Circle is to increase quality while decreasing human effort; not to replace humanness altogether.
Circle has given its employees a clear directive on the expected use of AI in all of our roles and functions. We’ve given people room to explore and try new AI tools, while also providing resources for employees to purchase these tools, attend a class or a course, and approach AI with intention and clarity. As we roll into 2026, we are actively implementing these AI-driven solutions into our workflows and day-to-day.
The way this looks in practice: teams at Circle are actively encouraged to seek out, or “vibe code” themselves, AI tools to improve their workflows and processes; Circle is hiring for a few roles to help us build applied AI models and agents for internal and external use; and we are constantly innovating and leveling up our industry, having just announced the launch of Circle’s AI Copilot!
Circle (circle.so) Employee Perspectives
How does your team stay ahead of emerging technology trends while scaling fast?
The AI landscape is evolving constantly, with new models, tools and techniques emerging faster than any organization can track. At Circle, we’ve leaned into that reality rather than try to manage it from the top down. We believe that the most successful engineering teams will be highly AI-leveraged, which means we’re working toward a model where we can scale our business with small, focused teams that can punch well above their weight. In practice, that looks like engineering leads who are expected to be hands-on with AI tooling themselves and a deliberate push to share what’s working across the org rather than letting learnings stay siloed.
What recent product or feature are you most proud of — and what impact has it had?
We launched Connect a few months ago. At its core, Connect helps community members find and build relationships with each other by using an AI-powered social graph. Rather than giving members access to the directory and hoping they figure it out, Connect surfaces personalized recommendations based on shared profiles, spaces and interests, and lowers the barrier to actually reaching out. The result is that meaningful member relationships can start forming naturally and at greater scale. Admins also have access to insights so they can see how relationships are forming, track engagement trends over time, and identify top connectors. Connect is a great example of how we are continually finding ways to enable our customers to build thriving communities. It’s also a good example of how we tackle genuine technical challenges, as it required the integration of a new graph database and AI alongside the existing relational database.
How do you create a culture where innovation and experimentation are encouraged daily?
Innovation isn’t just encouraged at Circle. In many ways, it’s expected, especially around AI. We hold regular show-and-tells in our engineering team meetings, where engineers demo whatever they’ve been experimenting with, no polish required: personal workflow improvements, novel MCP integrations and AI applied to places you wouldn’t expect. We share freely in Slack as well, from coding productivity wins to using automation to address sales questions and customer feedback.
What makes it work is that everyone, engineers and leaders alike, is genuinely learning and sharing those learnings publicly. Our co-founders constantly share how they keep up and experiment with AI, and when that kind of experimentation and curiosity is modeled at every level of the organization, it starts naturally feeling like it’s just how our work gets done.
