AI agents & LLM tooling
What I do now at SQL VIEW: self-hosted agents that answer questions over internal documents, chat interfaces wired into company workflows, & the prompt & model tuning that keeps the answers trustworthy.
I am currently an Artificial Intelligence Engineer Intern at SQL VIEW, building self-hosted AI agent tooling, while finishing my diploma in Cybersecurity & Digital Forensics. I am always up for a conversation about AI agents, CTFs, honeypots or network traffic that looks slightly wrong.
What I do now at SQL VIEW: self-hosted agents that answer questions over internal documents, chat interfaces wired into company workflows, & the prompt & model tuning that keeps the answers trustworthy.
I have spent a lot of time reading authentication logs & packet captures & building tools to summarise them, which is most of the work of working through a queue of alerts without burning out on it.
If a task is repetitive, I will usually write the script for it. That instinct is where most of my public repositories came from, including the honeypots, the converters & the monitors.
Penetration testing work that ends in a written report somebody can act on: what was found, how bad it actually is, & what to change first on Monday.
Sitting as a delegate in the MUN Crisis Committee at MUNch CTF meant arguing a position under time pressure in moderated caucus & negotiating it out with a room in unmoderated caucus. That is the same skill a team needs when a finding has to be explained to someone who was not in the room for it.
Fifty-seven projects are written up over on the projects page, & the rest of the repositories are public on GitHub.