Hi RADICL team,
I call myself a technomancer. Technology has felt like magic to me since I was a kid, and I still get excited when a complicated set of tools starts working together in a way that genuinely helps someone. AI has opened up a lot more of that possibility. It has also made me care even more about the boundaries around it: what the system knows, what it is allowed to do and how we can tell whether it did the right thing.
That is what interests me about your workflow role. You are not just putting a chat interface in front of security data. You are connecting context, reasoning and response actions into a system people have to be able to trust. My background brings together AI-enabled product work, authenticated service integration and years of being responsible for the systems behind a business. I would like to put those parts together with a team focused on protecting smaller organizations.
Through Technomancy IT, I build and operate tenant-aware services for client products and internal workflows. That includes OAuth/OIDC, access policy, authenticated connectors and MCP integrations. The platform I am building connects support, CRM, scheduling, billing and infrastructure context, so a problem can be understood alongside the customer and the systems it affects. I have also modeled connected experience, sources and product signals as a graph, with indexed retrieval and evaluation paths. Those are practical foundations for assembling useful context without losing track of where it came from.
Velatis is a completed client project where those boundaries mattered. I delivered a private research product connecting identity, notes, sharing, payments and administration with context-aware AI and deterministic chart services. The job was to make those capabilities work together without weakening ownership or privacy. The companion chart-service work made calculation and rendering reusable through typed, versioned contracts, with privacy-aware logging and a real calculation in its health checks. It is a different domain from security, but the discipline of keeping deterministic behavior around AI assistance is directly relevant to the systems your posting describes.
I also understand the operational side of a response workflow. At FRII, I ran the NOC, handled escalations and ran the SOC 1 and SOC 2 audits. I worked there from 2015 to 2020 and had already been a lead engineer through a company purchase before later taking sole systems-engineering responsibility for about a year. At Everon, I supported managed-service clients' networks and endpoints and worked with antivirus services. Those experiences keep me thinking about the person dealing with the incident, not just whether a service returned a successful response.
AI is now a substantial part of my engineering and creative work, and I enjoy building the surrounding tools as much as using the models. Kerf, my early-stage TSX framework with the Warp toolkit, is another expression of that interest in clear contracts and useful feedback for coding agents. I would bring that curiosity and hands-on ownership to RADICL, while learning the specifics of your Go services, streaming stack and security-analysis workflows rather than pretending every platform is already familiar.
Boulder is close enough for me to work alongside the team. I would welcome a conversation about where your automation needs the most help. Making a complicated system feel dependable to the people relying on it is the kind of magic I want to keep building.
Chad