Hamid Jafari-Zadeh
I’m an AI systems and reliability engineer. I wrote my first program when I was 12, and I’ve worked in IT for over 20 years. For the last 13+ of them I’ve run production systems at national and global scale: payment infrastructure, incident command for a global platform across five datacenters, and now AI agents.
Featured Projects & Research
AI Agent Control Layer
SEED
A control layer for AI agents near production.
Problem: AI agents become risky near production when their behavior is hard to observe, constrain, or change safely.
Approach: Building a control layer focused on observability, explicit boundaries, and practical operator control for agent workflows.
Outcome: A working sandbox demo: SEED finds the cause read-only, waits for a human to approve, applies one bounded fix, and records every step as a receipt.
Controlled AI Execution
Architect
An AI system for technical task execution under strict human control.
Problem: Most autonomous agents act as black boxes, making it difficult to inspect their logic, stop their actions, or reverse their mistakes.
Approach: Built an execution loop that gates and records actions, requires testing before capability promotion, and keeps higher-risk operations under explicit human control.
Outcome: A dependable system that can perform technical tasks while remaining observable, reviewable, and accountable to the operator.
Behavioral Analytics
NeuroTrace
A framework for analyzing how AI behavior changes over time.
Problem: AI personalization is often judged through intuition, making it hard to measure how an assistant actually adapts across many sessions.
Approach: Created a deterministic pipeline that turns conversation logs into structured behavioral data, mapping patterns such as planning, memory, feedback, and reflection.
Outcome: A repeatable way to inspect behavioral change over time and discuss personalization with evidence instead of guesswork.
Content Infrastructure
MD Grid Engine
A content engine for building fast, file-first websites. It also serves as the UI foundation for Architect, where the same system is used to present plans, execution traces, and decision outcomes in a structured way.
Problem: Traditional CMS platforms are often too rigid or heavy for technical sites that need structured content and more complex system views.
Approach: Engineered a custom Next.js engine that treats content as code, transforming Markdown and MDX into responsive layouts through a centralized component registry.
Outcome: A fast, maintainable system that powers this portfolio today and provides a UI foundation for future Architect interfaces.
Need AI systems you can trust in production?
I help teams make AI agents and production systems observable, controllable and safe to change. Open to roles, contract work and consulting.