Commercial proof
$6.8M net-new ARR generated at Atlassian, representing 27% of team output.
Living Resume
I build local-first operating environments, recruiter-safe proof surfaces, and bounded AI systems that stay readable under real pressure. The value is not “using AI.” The value is the operating model around it: contracts, validation, risk control, and public proof that holds up.
Public version is intentionally redacted. Open to employee roles, with selective advisory conversations only where the work is architecture-led, risk-aware, and clearly bounded.
Start with the PDF if you need the standard version. Then use the living pages for the operating model and the deeper proof.
$6.8M net-new ARR generated at Atlassian, representing 27% of team output.
22% faster Time-to-Value through onboarding and workflow redesign at CleverTap.
A local-first operating environment with bounded agent lanes, public proof pages, and deterministic publication rules.
I run a governed local-first system for work, publishing, research, and operational follow-through. It uses queues, handoffs, bounded agents, and validation gates instead of vague “AI assistant” claims. Public pages expose the useful architecture and redact the risky part.
That same operating model is what powers the website work, the case studies, the architecture notes, and the more technical writing on AI orchestration, privacy, and workflow reliability.