Building for an agent-first world.
With a decade of hands-on engineering across global enterprise platforms and AI infrastructure, I focus on building AI agents and the systems that make them actually work.
Curious by default, grounded in engineering. I care about what’s next and the craft it takes to take things from research to production.
- AI Agents: Making intelligent systems reliable, autonomous, and useful in practice.
- Developer Infrastructure: Building solid foundations, runtimes, and developer tooling for AI.
- Open Source: Contributing back to the frameworks and libraries powering this ecosystem.
- Fintech & Value Rails: Exploring the underlying infrastructure that moves and settles value.
| Project | Technical Contribution & Impact |
|---|---|
Microsoft Agent Lightning #583 |
Added a clear native-Windows boundary for the local runner by failing fast before worker startup, keeping package imports and controller modes clean. |
Google MCP Security #287 |
Enabled end-to-end SecOps workflows by exposing alert IDs and triage verdicts without altering the existing response shape. |
NVIDIA SkillEvaluator #109 |
Expanded link validation across CommonMark references, HTML anchors, and images while filtering out comment/code false positives. |
Microsoft Agent Lightning #573 |
Prevented request drops when model providers return missing or malformed token IDs, preserving retry deduplication and VERL image alignment. |
NVIDIA SkillEvaluator #84 |
Fixed false agent-runtime failures caused by health checks matching raw transcript text, improving diagnostic accuracy. |
NVIDIA SkillEvaluator #106 |
Made Gitleaks checks deterministic and fail-safe on shallow histories while keeping repo-wide scheduled audits intact. |
Burn #5494 |
Ensured extensionless Burnpack paths survive atomic saves, overwrite protection, and store round-trips without silently falling back to .bpk files. |
Technocore #135 |
Fixed a side-effect issue where HEAD requests could append messages or burn nonces, keeping read-only routes strictly read-only. |
| Project | Technical Contribution & Impact |
|---|---|
NVIDIA SkillEvaluator #129 |
Replaced raw parser and I/O exceptions with clean, path-specific CLI errors to clearly pinpoint bad policy inputs. |
NVIDIA SkillSpector #467 |
Kept stdout clean and parseable for pipelines by redirecting progress indicators and child-scan warnings to stderr. |
NVIDIA SkillSpector #463 |
Restored dynamic model provider registry via SKILLSPECTOR_MODEL_REGISTRY across Claude, Codex, and Gemini with safe fallbacks. |
NVIDIA SkillEvaluator #107 |
Fixed a dependency blind spot where PEP 508 markers could hide unpinned packages, without changing direct-reference behavior. |
OpenAI Agents SDK #4739 |
Enforced numeric and string validation for *args and **kwargs in JSON schemas and at runtime, catching invalid tool inputs upfront. |
Claude Agent SDK #1237 |
Prevented broken session migrations by surfacing subagent I/O issues and blocking symlink loops and directory traversal. |
Claude Agent SDK #1238 |
Ensured one logical subagent ID per listing across duplicate disk paths, aligning store behavior while preserving discovery order. |
NVIDIA NeMo Evaluator #1153 |
Prevented wrong cache hits between requests with different tools, streaming modes, or response formats without needing schema migrations. |
Stripe AI #509 |
Stopped abandoned client streams from lingering in background metering tasks, closing upstream requests promptly. |
Tools change, but the interesting part is always making different, moving pieces fit together seamlessly.