Agent engineering · Retrieval · Evaluation
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I like narrow, testable agents with explicit boundaries — then I spend more time on failure cases and evaluation than on demo polish.
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AI PR REVIEW AGENT Advisory PR review agent focused on behavioral regressions, test gaps, boundary conditions, and maintainability risks that conventional CI often misses.
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AI RESUME OPS AI-native resume pipeline that turns multiple job descriptions into role analysis, tailored resume variants, matching scores, and application prioritization.
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Quiet work, consistently. · A year of contributions, one bite at a time · Refreshed daily
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AI-native development I work with coding and research agents across architecture exploration, implementation, testing, and iteration — while keeping requirements, trade-offs, and final verification human-controlled. |
Evaluate before complexity I prefer baselines, golden sets, A/B tests, and failure analysis over adding complexity by default. If the simpler system performs better, I keep it. |
Ship the whole loop I care about the path from an agent idea to a usable service: tool boundaries, structured outputs, async APIs, observability, tests, Docker, and failure handling. |
I use open-source contribution as a production-engineering exercise: understand the issue, read the repository, make the smallest useful change, cover it with tests, pass CI, and iterate on maintainer feedback.
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TealTiger · merged PR #34 — add
formatCost()
Added a public cost-formatting helper, covered zero-cost / single-request / pricing-gap cases, and verified CommonJS + ESM packaging. -
OpenMed · merged PR #3079 — canonical governance identifiers
Added typed capability / purpose / policy / workflow / tool identifiers with strict canonical parsing, value-free diagnostics, documentation, and focused validation tests. -
Ruflo · merged PR #3331 — fix doctor memory diagnostics
Removed a misleading table-count heuristic that reported fresh databases as stale, tightened diagnostic claims, and added regression coverage across initialization and failure paths.
Three merged patches across agent security, healthcare AI governance, and agent-runtime diagnostics.
AI Application Development Intern
National Data Group · on-site via Aspire · 2026
Worked across enterprise AI application delivery, agent/RAG evaluation, platform validation, and lightweight reference implementations — with an emphasis on turning vague requirements into testable systems.
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Reliable agents Making agent behavior easier to inspect, constrain, evaluate, and recover when tools or evidence are imperfect. |
Code context Exploring graph-based repository context and skill retrieval so coding agents can load less, but understand more. |
Open-source engineering Using real issues and maintainer feedback to practice minimal changes, compatibility, tests, packaging, and CI discipline. |
Building MergeWarden, contributing to agent tooling, and documenting what I learn while turning AI-native development into a repeatable engineering workflow.
BUILD · EVALUATE · ITERATE