Building agentic AI systems and the platforms they run on.
- Agentic AI systems β production agents with retrieval, tools, governance, and eval gates.
- Agent harnesses β built on the Claude Agents SDK and the OpenAI Agents SDK, picking the right primitives for the job (subagents, tool use, structured outputs, long-running tasks).
- Data integration on Databricks β Mosaic AI Agent Framework, Vector Search, Lakeflow SDP, Unity Catalog, Lakebase. Where the agents get their grounded context.
- AI-assisted coding workflows β Claude Code and Codex as the implementation surface, Spec-Kit + constitutions as the design surface, eval suites as the merge gate.
- Container platforms β AKS (Azure) and EKS (AWS). Kubernetes-native deployment for everything that doesn't live inside Databricks.
- Agent SDKs β Claude Agents SDK, OpenAI Agents SDK, Mosaic AI Agent Framework. Comparative strengths: subagent isolation vs. handoffs, tool-use ergonomics, OBO identity, latency under realistic loads.
- Document intelligence β
ai_parse_document, layout-aware section explosion, typed KPI extraction, quality rubrics that decide what reaches the index. - AI-native developer tooling β Spec-Kit constitutions, Claude Code skill bundles, Codex orchestration, CLEARS eval gates as deploy promoters.
- Cloud-native platforms β AKS / EKS, Helm, Terraform, identity federation, secrets management. Boring, load-bearing.
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A Databricks-native document intelligence + agent reference implementation. Lakeflow SDP pipeline ( |
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Agent SDKs & runtimes
AI-assisted development
Data & lakehouse
Platform & cloud
Languages
The interesting question for the next few years isn't "which agent SDK wins" or "Claude Code vs. Codex." It's: what's the smallest, most testable unit of intent we can hand an AI implementer, and what's the eval surface that decides whether their output ships? The SDKs are tactical; specifications, constitutions, and eval gates are the actual leverage.
- πΌ LinkedIn β best for collaboration / consulting
- π Open issues on any of my repos
- π± Always open to: multi-SDK agent patterns, AI-assisted dev workflows, governed retrieval on Databricks, AKS/EKS at scale
