Naoise Rush, Community Manager at Delphi, argues that trust‑centric user networks, not bigger language models, will determine the winners of the generative‑AI boom.
A year into the generative‑AI gold rush, startups keep releasing ever‑larger models and slicker user interfaces. Yet adoption often stalls at the first click because they still want to know there's real humans behind the operation. As Naoise Rush puts it, "the most difficult point is trying to convince people that you're not AI whenever they first initially talk to you."
Rush is a Community Manager at Delphi, a platform that creates "digital minds" mirroring an expert's knowledge and tone. Rush says the real bottleneck is emotional, not technical. Users must believe the tool is safe, useful and human‑aligned before they will share data or embed it into workflows. That's where community programs come in and supply that missing infrastructure. A sense of community contextualize the product, reassures newcomers, and provides peer proof that the technology works in practice.
From Hesitation to Advocacy: Humans at the Center
Unlike traditional SaaS, digital‑mind AI touches personal identity. And because of that personal experience, the first reaction is often wariness. Rush has seen the attitude shift once skeptics observe their peers succeeding with the tool. "I've seen people feel more confident talking to a Delphi clone rather than talking to the real person even," she notes.
As the platform's community manager, Rush focuses on creating a strategy that puts personal experience at the center with:
- Warm welcomes. New users meet experienced "alumni" in dedicated channels. This welcome normalizes questions and lowers social risk.
- Story‑led education. Case studies focus on outcomes, time saved, and reach extended. They shouldn't focus on how much you've trained your models.
- Plain‑English support. Community staff explain technical features in practical terms for non‑engineers. This natural communication prevents frustrations that arise when explanations "over‑complicate how to explain it."
The result is a measurable increase of confidence in the product. Once members understand Delphi, they become advocates who then help shorten the learning curve for the next wave of users.
Community‑Driven Growth: A Playbook for AI Founders
Rush and Delphi treat community not as a cost of doing business but as a growth engine. And since growth needs to be measured, she keeps an eye out for three main signals that suggest the community is moving in the right direction:
- Peer‑to‑peer answers exceeding staff replies, which is evidence of self‑sustaining expertise.
- User‑generated playbooks that surface real‑world workflows faster than official docs can ever be written.
- Referral velocity, or the speed in which a satisfied customer invites a colleague to create a digital mind on Delphi.
"Community isn't sales," Rush emphasizes, "but if it's done the right way, it will naturally lead to more growth." Feedback loops inside discussion forums also double as agile R&D signals. These loops enable product teams to spot feature requests even before they hit the support queue.
In the near future, Delphi is planning on taking their community efforts to the next level, developing initiatives like in-person meet-ups aimed at building stronger bonds and sparking new collaborations. In Rush's view, roles such as chief community officer will become standard at AI companies. Especially for those whose products and services rely on building and sustaining user trust.
Architecting Human Connection
Rush's credibility in this field comes from a decade in software, developer relations and global expansion. At Elastic and Enterprise Ireland, she watched community programs accelerate U.S. market entry for SaaS companies and cybersecurity firms. The AI sector, however, posed a unique challenge. The product is oftentimes deeply personal. Thereby, the success metric is psychological safety as much as it is feature adoption.
Furthermore, Rush has a background in judging hackathons, mentoring women in tech, and bridging networks between Dublin and Silicon Valley. All of which prepared her for the role of turning complex technical features and concepts into human stories. "As AI keeps evolving, I believe the purpose is to improve human connections and create a level playing field for everyone," she says.
Action Items for AI Operators
- Budget for community. Allocate headcount and resources to building community early. Retrofitting trust later on is costly and difficult to do.
- Measure confidence, not clicks. Track when people feel comfortable enough to the point of recommending the product publicly.
- Speak every stakeholder's language. Provide explanations that can be understood by non‑technical professionals and domain experts alike.
- Treat events like they're product features. Workshops, demo days and peer showcases should be embedded in the roadmap, not tacked on post‑launch.
Generative‑AI innovation will only continue to accelerate at breakneck speed. Companies that neglect the human part of the equation risk watching superior technology wither on the vine. Rush's solution is simple. Match every hour optimizing autonomous agents with an hour investing in human relationships. In an industry defined by commoditized intelligence, Rush believes that shared intelligence, cultivated through community, is the true advantage that wins.
