Context retrieval agent
Designed and built the orchestrator agent that, given a user query, plans and executes the right sequence of search / explore / file calls to assemble the context downstream AI features consume.
Core engineer at Atlassian building an enterprise-scale context platform for AI agents β end to end, from zero to release.
In a large enterprise, context is scattered across 10,000+ repos. AI made writing code in any one repo fast β so the bottleneck moved to cross-service context understanding and coordination. We build the engine that closes that gap β a small team of ~10 engineers that moves faster than any other: deep cross-repo code search, where an organization's business logic actually lives, fused with docs and other sources into the comprehensive context an agent needs to act.
I built an enterprise context engine for AI agents and took it from zero to external release β the thing an external-facing AI chat product and external customer launches now run on, and the SDLC agent products our company is building will rely on it, too. I worked as the connective engineer across 10+ partner teams to turn diverse business needs into one coherent, agent-facing platform. On the side I build Rederive and Cedartale, which keeps me sharp on both the agent-side ergonomics and the production-system constraints β at the same time.
Designed and built the orchestrator agent that, given a user query, plans and executes the right sequence of search / explore / file calls to assemble the context downstream AI features consume.
Designed the public API contract β versioning, errors, pagination, permission semantics, MCP-friendliness β that every agent, service, and external customer integrates against, exposed via MCP and a CLI agent's full-context mode. Reworked the querying and indexing pipeline to be pluggable across search providers and ranking algorithms, so quality and speed can keep improving behind a stable interface.
Took code search from one source host to multi-host (one third-party host launched, another in progress). Coordinated 10+ partner teams β source control, provisioning, billing, edge gateway, AI product β into a working end-to-end onboarding journey for external customers, including GitHub repo index onboarding.
Multi-tenant permission resolution, account-ID-to-tenant mapping for third-party code, and a governed service-to-service onboarding contract so downstream callers integrate through a documented process rather than ad hoc.
Multi-tier rate-limit policy (per-client Γ per-user Γ per-operation) distinguishing humans, internal bots, external clients, eval traffic, and load tests, plus a generous edge-gateway ceiling. Experience-id propagation for traffic attribution, an integrator troubleshooting runbook, and trace-first debugging for "why did the agent get nothing?" failures.
Built and shipped the user-facing surfaces for code search and the AI chat experiences that consume it (React/TypeScript) β so the same context engine powers both programmatic agents and end-user product flows.
Found and integrated the tools that multiply our team's agent workflow (on Rovodev, Atlassian's coding agent) by orders of magnitude: a Splunk MCP for agent-led debugging, a Slack integration that auto-answers and resolves support-channel questions, and a shared Confluence doc registry any agent can pick up to load full context on a highly complex project.
A "Roblox for education" platform with an agent harness for creation.
Anyone with an AI agent can author courses in their domain, and a Socratic teaching agent (also built by me) guides learners through them. The authoring side is a BYO-agent pipeline β fully autonomous (YOLO) or human-in-the-loop β that goes from one prompt to a fully animated, narrated video or interactive course.
Same problem shape as agent-coding harnesses β applied to education.
Voice-cloned AI storytelling app for kids.
A parent's own voice can read the story. Founder, sole engineer, sole product designer β the whole loop from idea to a shipped consumer app, including user research. In 3 weeks.
Founder Β· sole engineer Β· sole product designer.
CS coursework: Android, deep learning, computer vision, optimization, front-end. Pre-CS research: 2D organicβinorganic hybrid perovskite materials for optoelectronics (Harry Atwater Group, Caltech), copper nanowire synthesis for transparent electrodes (Peidong Yang Group, UCB), polymer solar cells (He Yan Group, HKUST). Publications include Giant Enhancement of Photoluminescence Emission in WS2βTwo-Dimensional Perovskite Heterostructures.