Capability
Agentic AI & LLM Automation
LLM agents that take real action within tight limits: constrained configs, least-privilege access, and a human sign-off before anything ships.
Problems I Solve
Where this capability fits
Agents that can edit anything produce large, unreviewable changes.
Chat-only assistants cannot take multi-step action against real systems.
Automated drafts need review and an audit trail before they go public.
Pilots work in a demo and fall apart on real edge cases.
Scope
Capabilities
Claude skills and tool definitions for focused agent tasks
Constrained, validated configs so agent edits stay small, reviewable diffs
Least-privilege access, such as read-only database roles for agent sessions
Human-in-the-loop review and approval gates
Structured output written against a spec
Prompt-injection handling and scope checks
Example Systems
Systems I design and build
Agent-authored dashboards (yadash)
Drafting pipelines that queue work for human approval
Internal copilots for analyst and operations teams
Automated monitoring and research jobs
Technical Stack
Tools and platforms
Need this capability on your product?
Start with a technical scoping call focused on data sources, users, and success criteria.