Delegate & Orchestrate Justin Leopard
I build the connective tissue between planner models, tool-using agents, memory stores, and the humans they report to. Observability, evaluation, trajectory tracing — the boring parts that decide whether a multi-agent system clears a sprint or loops forever. The public path is inspectable: live demo, source repos, and field notes from the harness that ships them.
Where this helps
The work is not another chatbot layer. It is the operating surface around coding agents: the queue, trace, memory, review, routing, and escalation contract that keeps a team from re-learning the same failure every week.
Diagnostic
Inspect one real run: where it stalled, why it escalated, what context it lost, and which assertion should have caught it.
Build
Add the task model, trajectory capture, typed memory, review gate, and operator dashboard needed to trust repeated execution.
Policy
Separate planner and executor tiers, encode fallback rules, and use prior trajectories to decide when stronger models are justified.
Selected work
Flagship · Public demo
An enterprise observability layer for multi-agent engineering teams.
JustAi is a public project and demo: a fleet-observability layer for agents shipping software — planner, executor, reviewer — with cost, latency, trajectories, and learning signals as first-class data. The canonical visitor path is /demo/justai.
Prior work · 2024
A tri-agent harness built on intuition, before the literature caught up.
An Observer / Analyzer / Actor loop with an orchestrator underneath. It worked. It also taught me which parts of a multi-agent system are load-bearing and which are aesthetic — the lessons that now shape JustAi.
Public substrate
Minimal public references for the moving parts of an agent harness.
The *-mini family — minimal, MIT, well-tested public references for the moving parts of an agent harness. safe-mini (safety reference), lab-mini (data-science labbing), route-mini (multi-provider LLM routing with fallback), memory-mini (durable agent memory).
About
Software engineer, ten-plus years. The last two have been spent building agent systems that survive contact with real work — the kind where cost, trajectory, and escalation logic matter more than a clever prompt.
I read the papers the week they drop, then ship them as infrastructure the week after. More about how I work →