Backend and AI infrastructure at Sophos. Outside work I build local-first AI tools that turn messy real-world workflows into reliable software, across security, operations and music.
Summaries pile up and thinking stays still. So I built a pipeline where videos become typed challenges against a beliefs file capped at seven entries, checked for novelty against a knowledge graph, and judged by exactly one person: me.
I had memory, budgets, and guardrails, and I was still the one pressing go. Climbing from harness to loop turned out to be one timer, one snapshot file, and knowing which celebrated pattern to skip.
A hackathon build for shadow AI approvals: Tavily searches vendor evidence, Gemini extracts claims, deterministic policy rules make the decision, and ClickHouse-shaped audit rows preserve the trail.
A real LinkedIn recruiter message felt slightly off, so I checked the company, found the website did not resolve, and traced the role back to an expired job description. This is the local-first tool I built from that instinct.
I do not learn hard technical skills by covering topics. I break them into small movements and repeat those movements across scenarios until the pattern becomes automatic.
The follow-up to the memory-layer post. Persistent context worked too well: session start was burning 30-40K tokens before I typed a word. Four fixes — context is a budget, not a bucket.
A simple test for whether an internal platform is actually self-service, or just another queue developers have to wait in.
The Musician's Practice App is not public yet. This is a build note from getting it ready for early testing by using it like an actual musician, not a feature checklist.
Platform engineering only becomes visible when it breaks. This is the story of building reusable testing, compliance and production-gating infrastructure that multiple services could adopt without reinventing the same deployment safety work every time.
Stateless AI sessions waste engineering time. I built a context layer where sessions load relevant history, persist decisions, and traverse a knowledge graph instead of starting from zero.
Engineering work leaves traces everywhere: Jira, GitHub, Slack, incidents, notes. Career observability is about connecting them before performance review season turns you into an archaeologist.
You put a specific keyboard on the rider, get flown out to the gig, and when you arrive it's something completely different. That's the scenario this project solves.
Autonomous compliance approval agent for shadow AI tools. Searches vendor evidence, maps it to company policy, produces scoped decisions, and monitors approved tools for drift.
Local-first dashboard for checking recruiter outreach across legitimacy, security risk, original JD clues, opportunity fit, and safe reply strategy.
A grounded RAG system that answers questions about keyboard manuals using retrieved evidence, refusals, evals, and Langfuse tracing.
Practice app for musicians who can already play. Timer, YouTube player, metronome, tuner, sheet music, AI recommendations.
In progress
Automated stem loading for Ableton Live. The goal: send a message from your phone and open a prepared Ableton project later.
In progress
Automated morning email with high-signal cybersecurity threat items from trusted sources. Built for engineers and analysts.